· molecular conceptor 2 - table of contents pdf version last updated on june 2008 a - molecular...

Molecular Conceptor 2 - Table of Contents pdf version

Last updated on June 2008

A - MOLECULAR MODELING

1. Molecular Geometry

2. Molecular Properties

3. Stereochemistry

4. Molecular Energies

5. Conformational Analysis

6. Selected Examples in 3D Analysis

7. Molecular Graphics

B - PROTEIN STRUCTURE AND MODELING

1. Structural Bioinformatics (in progress) (*10)(*11)

2. Protein Structure (*)

3. Homology Modeling (in the pipeline)

4. Molecular Docking (*9)

5. Case Studies in Molecular Docking (in the pipeline)

6. Molecular Dynamics (*7)

C - DRUG DISCOVERY

1. Introduction to Drug Discovery (in the pipeline)

2. Principles of Rational Drug Design

3. Structure Activity Relationships (*3)

4. Bioisosterism (*8)

5. Success Stories in Drug Discovery (in progress) (*11)

6. Examples of Scaffold Morphing (*11)

D - STRUCTURE-BASED DRUG DESIGN

1. Structure-Based Drug Design: Analysis

2. Structure-Based Drug Design: Design

3. Structure-Based Drug Design: Examples

E - PHARMACOPHORE-BASED DRUG DESIGN

1. Pharmacophore-Based Drug Design: Analysis

2. Pharmacophore-Based Drug Design: Design

3. Pharmacophore-Based Drug Design: Examples

F - QSAR AND CHEMOMETRICS

1. QSAR Principles and Methods (*)

2. 3D-QSAR (*2)

G - SYNTHESIS AND LIBRARY DESIGN

1. Synthesis of Drugs (*4)

2. Library Design (*1)

H - PEPTIDOMIMETICS

1. Peptidomimetics

2. Peptidomimetics Examples (*)

I - ADME PROPERTIES AND PREDICTIONS

1. ADME Properties (*)

J - CHEMINFORMATICS

1. Cheminformatics, Principles and Applications (in progress) (*11)

2. Encoding Molecules (in the pipeline)

3. 3D Database Searching (*1)

4. Examples of 3D Database Searching (*6)

5. Molecular Similarity (*5)

K - GENERAL TOPICS

1. General Introduction on Drugs

2. Drug Discovery

3. Drug Development

(*) Released on Version 2.0 (*1) Released on Version 2.1 (*2) Released on Version 2.2 (*3) Released on Version 2.3 (*4) Released on Version 2.4 (*5) Released on Version 2.5 (*6) Released on Version 2.6 (*7) Released on Version 2.7 (*8) Released on Version 2.8

(*9) Released on Version 2.9 (*10) Released on Version 2.10 (*11) New: Released on Version 2.11

A. MOLECULAR MODELING

A1. MOLECULAR GEOMETRY

A1.1. 2D/3D A1.1.1 Molecules Considered as 2D Structures A1.1.2 The Three-Dimensional Shape of a Molecule A1.1.3 2D and 3D Representations A1.1.4 A Molecule: An Assembly of Atoms in 3D A1.1.5 Molecular Lego A1.1.6 Molecular Fragments for Constructing Molecules

A1.2. Conformers A1.2.1 A Molecule is a Flexible Entity A1.2.2 Conformation Definition A1.2.3 Example of Conformations of a Molecule A1.2.4 Bioactive Conformation

A1.3. Torsion Angles A1.3.1 Interconversion Between Conformers A1.3.2 How Do Interconversions Occur? A1.3.3 Definition of the Conformers of a Molecule A1.3.4 The Torsion Angle Concept A1.3.5 Definition of Torsion Angles A1.3.6 Monitoring Torsion Angles A1.3.7 Newman Projections and Torsion Angles A1.3.8 Convention for the Sign of Torsion Angles A1.3.9 Ring Conformations

A1.4. Conformational Complexity A1.4.1 Rigid and Flexible Molecules A1.4.2 Codeine and Fenoxedil A1.4.3 Monitoring Torsion Angle Combinations A1.4.4 Conformational Explosion

A1.5. Ratio of Conformers A1.5.1 Mixtures of Conformers A1.5.2 Ratio of Conformers and Population

A1.6. CHAPTER QUIZZES (Available only in Teaching Package) A1.6.1 Quiz 1 A1.6.2 Quiz 2 A1.6.3 Quiz 3 A1.6.4 Quiz 4 A1.6.5 Quiz 5 A1.6.6 Quiz 6 A1.6.7 Quiz 7 A1.6.8 Quiz 8

A1.6.9 Quiz 9 A1.6.10 Quiz 10 A1.6.11 Quiz 11 A1.6.12 Quiz 12 A1.6.13 Quiz 13 A1.6.14 Quiz 14 A1.6.15 Quiz 15 A1.6.16 Quiz 16 A1.6.17 Quiz 17 A1.6.18 Quiz 18 A1.6.19 Quiz 19 A1.6.20 Quiz 20 A1.6.21 Quiz 21

A2. MOLECULAR PROPERTIES

A2.1. Introduction A2.1.1 Properties of a Molecule A2.1.2 Average of a Conformational-Dependent Property A2.1.3 Importance of the 3D Molecular Geometries

A2.2. Biological Properties A2.2.1 Biological Properties of Proteins A2.2.2 Biological Properties of Chiral Analgesics

A2.3. Physical Properties A2.3.1 Physical Properties A2.3.2 Calculation of Other Physical Properties

A2.4. Chemical Properties A2.4.1 Chemical Properties A2.4.2 Enolization of Keto-3 Steroids A2.4.3 Relative Stability of Isomers A2.4.4 Reactivity of Alkyl Halides A2.4.5 SN2 Mechanism A2.4.6 E2 Elimination Mechanism A2.4.7 Molecular Geometries and Chemical Properties

A2.5. Many Properties A2.5.1 Many Properties of a Molecule

A2.6. CHAPTER QUIZZES (Available only in Teaching Package) A2.6.1 Quiz 1 A2.6.2 Quiz 2 A2.6.3 Quiz 3 A2.6.4 Quiz 4 A2.6.5 Quiz 5 A2.6.6 Quiz 6 A2.6.7 Quiz 7

A3. STEREOCHEMISTRY

A3.1. Introduction A3.1.1 Introduction on Stereochemistry

A3.1.2 Bond Lengths A3.1.3 Bond Multiplicity A3.1.4 Atom Size A3.1.5 Electronegativity A3.1.6 Hybridization A3.1.7 Bond Angles A3.1.8 Thorpe-Ingold Effect A3.1.9 Torsion Angles A3.1.10 Torsion Angle Sign Convention A3.1.11 Examples of Torsion Angles A3.1.12 Torsion Angle Descriptor (sp3-sp3) A3.1.13 Torsion Angle Descriptor (sp2-sp3)

A3.2. Chirality A3.2.1 Chirality A3.2.2 Example 1 A3.2.3 Example 2 A3.2.4 Chirality Descriptor: Optical Rotation A3.2.5 Chirality Nomenclature A3.2.6 The Order of Priority A3.2.7 Examples of R/S Assignments A3.2.8 The Newman Projection A3.2.9 The Fischer Projection A3.2.10 Chirality: D/L A3.2.11 D-alanine A3.2.12 L-alanine A3.2.13 Chirality: Erythro/Threo A3.2.14 Threo A3.2.15 Erythro A3.2.16 Other Examples of Chiral Molecules

A3.3. Double Bonds A3.3.1 Cis-Trans Stereochemistry of Double Bonds A3.3.2 E/Z Stereochemistry of Double Bonds A3.3.3 s-cis/s-trans Conformations A3.3.4 Re/Si Nomenclature of the Faces of Double Bonds

A3.4. Rings A3.4.1 Rings A3.4.2 Chair A3.4.3 Boat A3.4.4 Twist Boat A3.4.5 Crown A3.4.6 Rings: Axial and Equatorial Orientations

A3.5. Symmetry A3.5.1 Introduction on Symmetry Operations A3.5.2 Symmetry C2 A3.5.3 Symmetry C3 A3.5.4 Symmetry Sigma A3.5.5 Inversion (i) A3.5.6 Example of Inversion A3.5.7 Rotatory Reflection (Sn)

A3.6. CHAPTER QUIZZES (Available only in Teaching Package) A3.6.1 Quiz 1 A3.6.2 Quiz 2 A3.6.3 Quiz 3 A3.6.4 Quiz 4 A3.6.5 Quiz 5 A3.6.6 Quiz 6 A3.6.7 Quiz 7 A3.6.8 Quiz 8 A3.6.9 Quiz 9 A3.6.10 Quiz 10 A3.6.11 Quiz 11 A3.6.12 Quiz 12 A3.6.13 Quiz 13 A3.6.14 Quiz 14 A3.6.15 Quiz 15 A3.6.16 Quiz 16 A3.6.17 Quiz 17 A3.6.18 Quiz 18 A3.6.19 Quiz 19 A3.6.20 Quiz 20 A3.6.21 Quiz 21 A3.6.22 Quiz 22 A3.6.23 Quiz 23 A3.6.24 Quiz 24 A3.6.25 Quiz 25 A3.6.26 Quiz 26 A3.6.27 Quiz 27 A3.6.28 Quiz 28 A3.6.29 Quiz 29 A3.6.30 Quiz 30

A4. MOLECULAR ENERGIES

A4.1. Introduction A4.1.1 Internal Energy of a Molecule A4.1.2 Internal Energy Associated to a Conformation A4.1.3 Transition State A4.1.4 Potential Surface A4.1.5 Thermodynamics & Kinetics

A4.2. Thermodynamics A4.2.1 Thermodynamics: Conformer Populations A4.2.2 Thermodynamics: Boltzmann Equation A4.2.3 Boltzmann Population Analysis for Two Conformers A4.2.4 Boltzmann Population Analysis for 3 Conformers A4.2.5 Thermodynamics: Cyclohexane Example A4.2.6 Thermodynamics: Methylcyclohexane Example

A4.3. Kinetics A4.3.1 Kinetics A4.3.2 Kinetics: Arrhenius Equation

A4.3.3 Kinetics: Arrhenius Graph A4.3.4 Kinetics Ethane Example A4.3.5 Kinetics Cyclohexane Example A4.3.6 Kinetics Amide Bond Example

A4.4. Molecular Modeling A4.4.1 Molecular Modeling A4.4.2 Example of Kinetic or Thermodynamic Control A4.4.3 Lowering the Energy of the Transition State A4.4.4 Raising the Energy of the Transition State A4.4.5 Modifying Conformers Populations A4.4.6 Molecular Energies: The Key of Molecular Modeling

A4.5. Modeling in Drug Design A4.5.1 Molecular Modeling in Drug Design A4.5.2 Importance of Energies: the Morphinan Example A4.5.3 Morphinan and D-nor Morphinan Alignment A4.5.4 Conformational Analysis of Morphinan A4.5.5 Conformational Analysis of D-nor Morphinan A4.5.6 A Rationale for Explaining the Activities Observed A4.5.7 Morphinan: Validation and Design A4.5.8 Preferred Conformer of Active Enantiomer A4.5.9 Preferred Conformer of Inactive Enantiomer A4.5.10 Restoring Activities to the Inactive Analog? A4.5.11 Morphinan Browser A4.5.12 What We Can Learn From The Morphinan Example

A4.6. How to Calculate Energies A4.6.1 The Need of Tools for Calculating Energies A4.6.2 Two Methods for Calculating Energies

A4.7. Quantum Mechanics A4.7.1 Calculation of Energies by the Schrodinger Equation A4.7.2 Ab-Initio and Semi-empirical Calculations A4.7.3 Calculation of Energies A4.7.4 The Density Function Theory A4.7.5 The Choice of a Method

A4.8. Molecular Mechanics A4.8.1 Molecular Mechanics A4.8.2 Force-Field A4.8.3 Force Field Components A4.8.4 Bond Lengths: Stretching Contributions A4.8.5 Function A4.8.6 Examples of Elementary Stretching Contributions A4.8.7 Bond Angles: Bending Contributions A4.8.8 Function A4.8.9 Examples of Elementary Bending Contributions A4.8.10 Torsion Angles: Torsional Contributions A4.8.11 Function A4.8.12 Examples of Elementary Torsional Contributions A4.8.13 Van der Waals Interactions A4.8.14 Function A4.8.15 Examples of Elementary Van der Waals

A4.8.16 Electrostatic Dipolar Contributions A4.8.17 Function A4.8.18 Examples of Elementary Electrostatic Contributions A4.8.19 Hydrogen Bond Energy Contributions A4.8.20 Function A4.8.21 Examples of Elementary Hydrogen Bond Contributions A4.8.22 Total Energy in a Force Field Calculation A4.8.23 Main Force Fields A4.8.24 What One Should Remember A4.8.25 Relative Energies

A4.9. CHAPTER QUIZZES (Available only in Teaching Package) A4.9.1 Quiz 1 A4.9.2 Quiz 2 A4.9.3 Quiz 3 A4.9.4 Quiz 4 A4.9.5 Quiz 5 A4.9.6 Quiz 6 A4.9.7 Quiz 7 A4.9.8 Quiz 8 A4.9.9 Quiz 9 A4.9.10 Quiz 10 A4.9.11 Quiz 11 A4.9.12 Quiz 12 A4.9.13 Quiz 13 A4.9.14 Quiz 14 A4.9.15 Quiz 15 A4.9.16 Quiz 16 A4.9.17 Quiz 17 A4.9.18 Quiz 18 A4.9.19 Quiz 19 A4.9.20 Quiz 20 A4.9.21 Quiz 21 A4.9.22 Quiz 22 A4.9.23 Quiz 23 A4.9.24 Quiz 24 A4.9.25 Quiz 25 A4.9.26 Quiz 26 A4.9.27 Quiz 27 A4.9.28 Quiz 28 A4.9.29 Quiz 29 A4.9.30 Quiz 30 A4.9.31 Quiz 31 A4.9.32 Quiz 32 A4.9.33 Quiz 33 A4.9.34 Quiz 34 A4.9.35 Quiz 35 A4.9.36 Quiz 36 A4.9.37 Quiz 37 A4.9.38 Quiz 38 A4.9.39 Quiz 39 A4.9.40 Quiz 40

A5. CONFORMATIONAL ANALYSIS

A5.1. Introduction A5.1.1 Geometries, Energies and Conformational Analysis A5.1.2 Energy Profile: a Global Information A5.1.3 Definition of Conformational Analysis

A5.2. Potential Surface A5.2.1 Conformational Potential Surface: One Rotation A5.2.2 Conformational Potential Surface: Two Rotations A5.2.3 Conformational Potential Surface A5.2.4 Special Forms A5.2.5 Interconversion Between Conformers A5.2.6 Energy Barriers A5.2.7 Interconversion Pathway

A5.3. Conformational Analysis A5.3.1 Conformational Analysis Principles A5.3.2 Systematic Scanning of All Potential Surfaces A5.3.3 Systematic Scanning is Time Consuming A5.3.4 How to Reduce Conformational Search? A5.3.5 One Conformer Represents a Whole Family A5.3.6 Working with a Set of Representative Conformers A5.3.7 Sildenafil Example A5.3.8 Family Representatives: Small Rings A5.3.9 Family Representatives: Acyclic Bonds A5.3.10 Consequence: Minimization Treatments A5.3.11 Example: Analysis of Elementary Fragments A5.3.12 Example: Generation of Representative Conformers A5.3.13 Example: Results of Conformational Analysis A5.3.14 Conformational Analysis Principles: Summary

A5.4. Minimizations A5.4.1 Definition of the Minimization of a Conformer A5.4.2 Improved Geometries and Good Energies A5.4.3 The Minimization Treatment A5.4.4 How Does Minimization Works? A5.4.5 Minimization Methods A5.4.6 Many Variables Are Minimized A5.4.7 Minimization is a Time-Consuming Treatment

A5.5. Examples of Minimization A5.5.1 Minimization with Stretching Strain A5.5.2 Minimization with Bending Strain A5.5.3 Minimization with Torsional Strain A5.5.4 Minimization with Van der Waals Strain A5.5.5 Minimization with Electrostatic Component A5.5.6 Minimization with Hydrogen Bond Component A5.5.7 Typical Minimization Example A5.5.8 Distribution of Energy Strain

A5.6. Conformational Analysis in Drug Design A5.6.1 Conformational Analysis in Drug Design

A5.6.2 Energy of the Bioactive Form A5.6.3 Low Energy of the Bioactive Conformation A5.6.4 Geometry of the Bioactive Conformation A5.6.5 The Experienced Molecular Modeler A5.6.6 Common Errors Made with Minimization A5.6.7 Example 1 A5.6.8 Example 2

A5.7. Molecular Dynamics A5.7.1 Molecular Dynamics A5.7.2 Theoretical Basis of Molecular Dynamic Calculations A5.7.3 Local Minima and Global Minimum A5.7.4 Simulated Annealing, a Special Type of Dynamics A5.7.5 Coherency of Molecular Motions A5.7.6 A Typical Molecular Dynamics Run

A5.8. CHAPTER QUIZZES (Available only in Teaching Package) A5.8.1 Quiz 1 A5.8.2 Quiz 2 A5.8.3 Quiz 3 A5.8.4 Quiz 4 A5.8.5 Quiz 5 A5.8.6 Quiz 6 A5.8.7 Quiz 7 A5.8.8 Quiz 8 A5.8.9 Quiz 9 A5.8.10 Quiz 10 A5.8.11 Quiz 11 A5.8.12 Quiz 12 A5.8.13 Quiz 13 A5.8.14 Quiz 14 A5.8.15 Quiz 15 A5.8.16 Quiz 16 A5.8.17 Quiz 17 A5.8.18 Quiz 18 A5.8.19 Quiz 19 A5.8.20 Quiz 20 A5.8.21 Quiz 21 A5.8.22 Quiz 22 A5.8.23 Quiz 23 A5.8.24 Quiz 24 A5.8.25 Quiz 25 A5.8.26 Quiz 26 A5.8.27 Quiz 27 A5.8.28 Quiz 28 A5.8.29 Quiz 29 A5.8.30 Quiz 30 A5.8.31 Quiz 31 A5.8.32 Quiz 32 A5.8.33 Quiz 33 A5.8.34 Quiz 34 A5.8.35 Quiz 35

A5.8.36 Quiz 36 A5.8.37 Quiz 37 A5.8.38 Quiz 38 A5.8.39 Quiz 39 A5.8.40 Quiz 40 A5.8.41 Quiz 41

A6. SELECTED EXAMPLES IN 3D ANALYSIS

A6.1. Conformational Analysis A6.1.1 Ethane A6.1.2 n-Butane A6.1.3 1-Butene A6.1.4 Butadiene A6.1.5 Amide A6.1.6 Cyclohexane

A6.2. Conjugated Systems A6.2.1 Butadiene A6.2.2 Pentenone A6.2.3 Dipyrrole A6.2.4 Biphenyl A6.2.5 Atropisomerism of Biphenyls A6.2.6 Binaphthyl

A6.3. Aromatic Systems A6.3.1 Planarity of Polyaromatic Systems A6.3.2 Distorted Naphthalene A6.3.3 Annelated Polyaromatic Benzenes

A6.4. Cyclic Systems A6.4.1 Why Substituents Prefer to be Equatorial? A6.4.2 Mono-Substituted Cyclohexanes A6.4.3 t-Bu A6.4.4 Phenyl A6.4.5 Methyl A6.4.6 Hydroxy A6.4.7 Example of Preferred Axial Conformer A6.4.8 Di-Methyl-1,2-Cyclohexane A6.4.9 Trans A6.4.10 Cis A6.4.11 Di-Methyl-1,3-Cyclohexane A6.4.12 Trans A6.4.13 Cis A6.4.14 Di-Methyl-1,4-Cyclohexane A6.4.15 Trans A6.4.16 Cis A6.4.17 Trans 1,3-Di-t-Butyl-Cyclohexane A6.4.18 Chloro-2 Cyclohexanone

A6.5. Other Systems A6.5.1 Decalins A6.5.2 Cis-decalin

A6.5.3 Methyl-Cis-decalin A6.5.4 Trans-decalin A6.5.5 Interactions of Aromatic Rings A6.5.6 Geometry of Ester Groups A6.5.7 Cyclic Ester A6.5.8 Geometry of Amide Groups A6.5.9 Substituted Amide A6.5.10 Cyclic Amide

A7. MOLECULAR GRAPHICS

A7.1. Introduction A7.1.1 Importance of Molecular Graphics A7.1.2 Almost Science Fiction A7.1.3 History of Molecular Visualizations A7.1.4 Commercially Available Molecular Kits A7.1.5 Progress in Graphical Hardware and Algorithms A7.1.6 Algorithm 1 A7.1.7 Algorithm 2 A7.1.8 Molecular Graphics Functions

A7.2. 3D Perception A7.2.1 The Perception of the Third Dimension A7.2.2 From 3D Coordinates to Screen Coordinates A7.2.3 Real Time Manipulation A7.2.4 Depth Cueing A7.2.5 Perspective A7.2.6 Stereo A7.2.7 Hardware Stereo

A7.3. Visualization A7.3.1 3D Representation of Small Molecules A7.3.2 Line A7.3.3 Stick A7.3.4 Ball & Stick A7.3.5 CPK A7.3.6 Quality of Rendering A7.3.7 Atomic Color-Code Convention A7.3.8 Coloring Molecules or Sets of Atoms A7.3.9 By Atom-type A7.3.10 By Molecule A7.3.11 By Color A7.3.12 By Properties A7.3.13 Labeling Functionalities A7.3.14 Atom Labels A7.3.15 Atom Numbering A7.3.16 Proteins Representation A7.3.17 Carbon Alpha A7.3.18 Ribbon Representation A7.3.19 Ribbon Types A7.3.20 Visualization of Protein Properties

A7.4. Editing & Manipulation

A7.4.1 Structure Manipulation & Editing A7.4.2 Add Atoms Function A7.4.3 Delete Atoms Function A7.4.4 Fuse Atoms Function A7.4.5 Connect atoms Function A7.4.6 3D Molecular Constructions A7.4.7 Real-Time Rotations, Translations and Zoom A7.4.8 Translations A7.4.9 Rotations A7.4.10 Zoom A7.4.11 Control of Torsion Angles A7.4.12 Slab and Clip

A7.5. Surfaces & Volumes A7.5.1 Concept and Definition of Molecular Surfaces A7.5.2 Van der Waals A7.5.3 Solvent A7.5.4 Connolly A7.5.5 Surface Types A7.5.6 Normal A7.5.7 Transparent A7.5.8 Dots A7.5.9 Visualization of Properties on Molecular Surfaces A7.5.10 Color Coded A7.5.11 Visualization of Properties on Molecular Surfaces A7.5.12 The Visualization of Volumes A7.5.13 Mathematical Boolean Operations with Volumes

A7.6. Visualizing Interactions A7.6.1 Visualization of Hydrogen Bonds A7.6.2 Visualization of Molecular Bumps A7.6.3 Surface Representations for Bump Analyses A7.6.4 Complementary Surface Properties A7.6.5 Electrostatic Potentials A7.6.6 Lipophilicity Potentials A7.6.7 Visualization of Intramolecular Interaction A7.6.8 Schematic Complex Interaction A7.6.9 Visualization of a Complex Cavity A7.6.10 Results of Quantum Mechanical Calculations

A7.7. CHAPTER QUIZZES (Available only in Teaching Package) A7.7.1 Quiz 1 A7.7.2 Quiz 2 A7.7.3 Quiz 3 A7.7.4 Quiz 4 A7.7.5 Quiz 5 A7.7.6 Quiz 6 A7.7.7 Quiz 7 A7.7.8 Quiz 8 A7.7.9 Quiz 9 A7.7.10 Quiz 10 A7.7.11 Quiz 11 A7.7.12 Quiz 12

A7.7.13 Quiz 13 A7.7.14 Quiz 14 A7.7.15 Quiz 15 A7.7.16 Quiz 16 A7.7.17 Quiz 17 A7.7.18 Quiz 18 A7.7.19 Quiz 19 A7.7.20 Quiz 20 A7.7.21 Quiz 21 A7.7.22 Quiz 22 A7.7.23 Quiz 23 A7.7.24 Quiz 24 A7.7.25 Quiz 25 A7.7.26 Quiz 26 A7.7.27 Quiz 27 A7.7.28 Quiz 28 A7.7.29 Quiz 29

B. PROTEIN STRUCTURE AND MODELING

B1. STRUCTURAL BIOINFORMATICS

B1.1. Introduction to Structural Bioinformatics B1.1.1 Challenges in the Post Genomic Era B1.1.2 The Informational Chaos B1.1.3 Integration through Computational Science B1.1.4 Structural Bioinformatics B1.1.5 Grouping Fields into One Discipline B1.1.6 3D Basis of Structural Bioinformatics B1.1.7 The Structural Genomics Effort B1.1.8 The Protein Structure Initiative B1.1.9 Strategy of the Protein Structure Initiative B1.1.10 The Structural Genomics Consortium B1.1.11 Global Planning of Structural Genomics B1.1.12 The Impact of Structural Genomics B1.1.13 The Relationship between Structure and Function B1.1.14 Example of a Structure-Function Relationship B1.1.15 Learning from Evolution B1.1.16 Learning from Structural Folds B1.1.17 Learning from Molecular Shape B1.1.18 Example of Knowledge Derived from 3D Structure B1.1.19 Is Structure Sufficient to Predict Function? B1.1.20 Exploiting Knowledge to Design New Drugs B1.1.21 Bridge between Genomics and Drug Discovery B1.1.22 Tools Developed by Structural Bioinformatics

B1.2. Architecture of Biomolecules B1.2.1 Biomolecules in the Cell B1.2.2 DNA/RNA Structure B1.2.3 DNA is the Genetic Material B1.2.4 DNA Variability

B1.2.5 Importance of the DNA 3D Structure B1.2.6 The Building Blocks B1.2.7 Base B1.2.8 Sugar B1.2.9 Phosphate B1.2.10 Putting the Building Blocks Together B1.2.11 Nomenclature of Nucleotides and Nucleosides B1.2.12 Nucleotides of Nucleic Acids B1.2.13 The Double Helix Structure B1.2.14 DNA Helices are Antiparallel B1.2.15 Hydrogen Bonding Pattern B1.2.16 Aromatic Base Stacking B1.2.17 Major and Minor Grooves B1.2.18 DNA forms B1.2.19 G-Quadruplex Conformation B1.2.20 DNA versus RNA B1.2.21 3D Folds of RNA B1.2.22 Protein Structure B1.2.23 Proteins are Fundamental to Life B1.2.24 Structural Diversity of Proteins B1.2.25 Importance of Protein 3D Structures B1.2.26 Chemical Nature of Proteins B1.2.27 Challenges in Understanding Protein Structure B1.2.28 Protein Structure Complexity B1.2.29 The Four Levels of Protein Architecture B1.2.30 Primary Structure B1.2.31 Secondary Structure B1.2.32 Tertiary Structure B1.2.33 Quaternary Structure

B1.3. Biomolecular Properties B1.3.1 Protein Flexibility and Motion B1.3.2 Importance of Dynamic Motions in Biological Processes B1.3.3 Example of Function: ATP Synthase B1.3.4 Example of Function: DNA Biosynthesis B1.3.5 Example of Function: Molecular Switch B1.3.6 Example of Induced-Fit: RNA-Protein Recognition B1.3.7 Example of Induced-Fit: Ubiquitous Proteins B1.3.8 Types of Molecular Motions B1.3.9 Time Scale of Protein Motion B1.3.10 Methods to Study Protein Motions B1.3.11 Experimental Techniques to Study Protein Motions B1.3.12 Simulation Methods to Study Protein Motions B1.3.13 Normal Mode Analyses (NMA) B1.3.14 Molecular Dynamics vs Normal Mode Analyses B1.3.15 Database of Macromolecular Movements

B1.4. Assembly of Biomolecules B1.4.1 Biological Molecule Association B1.4.2 Molecular Recognition B1.4.3 The Recognition Process B1.4.4 Complementary Features Upon Binding

B1.4.5 Role of Native Protein Configuration B1.4.6 Tolerance Upon Binding B1.4.7 The "Induced-Fit" Theory B1.4.8 Example of Enzyme Adaptation to Inhibitor Binding B1.4.9 Example of Ligand Adaptation upon Binding B1.4.10 Maximizing Surface Contacts B1.4.11 Motions Associated to Induced-Fit B1.4.12 Experimental Evidence of the Induced-Fit Model B1.4.13 Large Rearrangements B1.4.14 Role of Large Rearrangements B1.4.15 The Domino Effect B1.4.16 Proteins Described as Ensemble of Conformations B1.4.17 Energy Landscape of a Protein B1.4.18 Conformational Selection Operated by a Ligand B1.4.19 Energetic Induction Upon Binding B1.4.20 Forces Involved in Molecular Recognition B1.4.21 Van der Waals Forces B1.4.22 Electrostatic Interactions B1.4.23 Hydrogen Bonds B1.4.24 Solvent Effect B1.4.25 The Role of the Solvent B1.4.26 The Hydrophobic Effect B1.4.27 The Entropic Effects B1.4.28 Enthalpy-Entropy Compensation B1.4.29 Assessing Binding Interactions B1.4.30 Free Energy of Binding B1.4.31 Importance of Free Energy of Binding B1.4.32 Experimental Measures of Binding Affinities B1.4.33 Titration Curve to Measure Kd B1.4.34 Scatchard-Rosenthal Plots B1.4.35 Conversion of Kd into Energies B1.4.36 Theoretical Prediction of Binding Energies B1.4.37 Solving the Schrodinger Equation B1.4.38 Molecular Mechanics B1.4.39 Force-Field B1.4.40 Example of Force-Fields B1.4.41 Other Methods B1.4.42 Incorporation of the Solvent

B1.5. Obtaining Macromolecular 3D-Structures B1.5.1 Experimental Methods B1.5.2 X-ray Crystallography B1.5.3 Protein Production and Purification B1.5.4 Growing of Single Crystal B1.5.5 The Single Crystal B1.5.6 Collecting the Diffraction Data B1.5.7 Recovering the Phase Angle B1.5.8 Structure Determination and Refinement B1.5.9 Atomic Coordinates B1.5.10 The Advantages of X-ray Crystallography B1.5.11 The Limitations of X-ray Crystallography B1.5.12 NMR Spectroscopy

B1.5.13 NMR Concepts B1.5.14 Spin-Spin Coupling B1.5.15 Data Collection B1.5.16 Structure Determination B1.5.17 Analysis B1.5.18 The Advantages of NMR B1.5.19 The Limitations of NMR B1.5.20 Electron Microscopy B1.5.21 Basic Concept B1.5.22 The Advantages of Electron Microscopy B1.5.23 The Limitations of Electron Microscopy

B2. PROTEIN STRUCTURE

B2.1. Structural and Functional Diversity of Proteins B2.1.1 Proteins are Fundamental to Life B2.1.2 Great Diversity of Protein Biological Functions B2.1.3 Chemical Nature of Proteins B2.1.4 Structural Diversity of Proteins

B2.2. Link between Protein Sequence, Folding and Function B2.2.1 Importance of Protein 3D Structures B2.2.2 Protein Folding B2.2.3 Anfinsen's Dogma B2.2.4 Anfinsen's Dogma and Levinthal's Paradox B2.2.5 The Pathway Theory and Energy Funnels B2.2.6 Mechanisms of Protein Folding B2.2.7 The Protein Misfolding Problem B2.2.8 Challenge in Understanding Protein Structure

B2.3. Amino Acids: Building Blocks of Proteins B2.3.1 Amino acids: Building Blocks of Proteins B2.3.2 α-Amino Acids B2.3.3 α-Amino Acid Stereoisomers B2.3.4 Diversity of the Properties of Amino Acids B2.3.5 Amino Acids Properties B2.3.6 Classification of Amino Acids Properties B2.3.7 Non-Standard Amino Acids

B2.4. From Amino Acids to Proteins B2.4.1 Amino Acids are Linked by Peptide Bonds B2.4.2 Peptide Biosynthesis B2.4.3 Polymer Amino-Acids B2.4.4 Length of Proteins B2.4.5 More than One Polypeptide Chain B2.4.6 Conjugated Proteins B2.4.7 Examples of Conjugated Proteins B2.4.8 Cross-Linked Polypeptide Chains

B2.5. Geometry of Proteins and Peptides B2.5.1 Peptide Bonds are Planar B2.5.2 Why the Peptide Bond is Planar? B2.5.3 Cis and Trans Isomers of the Peptide Bond

B2.5.4 Trans Isomer Favored B2.5.5 Isomers of Proline B2.5.6 Peptide Torsion Angles B2.5.7 Conformational Freedom B2.5.8 Conformational Complexity of Polypeptide Chains B2.5.9 Not All φ/ψ Torsion Angles are Possible B2.5.10 The Ramachandran Plot B2.5.11 φ and ψ Distribution B2.5.12 Interactive Ramachandran Plot B2.5.13 Torsion Angles Observed in Proteins B2.5.14 Glycine Residue Torsion Angles B2.5.15 Side Chain Conformations B2.5.16 Side Chain Atomic and 3D Nomenclature B2.5.17 Side Chain Conformations B2.5.18 Non-Rotameric Side Chain Conformations

B2.6. Protein Structure Overview B2.6.1 Protein Structure Complexity B2.6.2 The Four Levels of Protein Architecture B2.6.3 Primary Structure B2.6.4 Secondary Structure B2.6.5 Tertiary Structure B2.6.6 Quaternary Structure B2.6.7 Forces Involved in Protein Stability B2.6.8 Proteins are not Static B2.6.9 Representing Protein Structures B2.6.10 Wireframe Representation B2.6.11 Ball and Stick Representation B2.6.12 Cα Trace Representation B2.6.13 Ribbon Representation B2.6.14 Cartoon Representation B2.6.15 Space Filling - CPK Representation B2.6.16 Surface Representation

B2.7. Primary Structure B2.7.1 Primary Structure B2.7.2 Unique Primary Structure for Each Protein B2.7.3 Primary Sequence and Protein Properties

B2.8. Secondary Structure B2.8.1 Secondary Structure B2.8.2 Periodic and Non Periodic Secondary Structure Elements B2.8.3 Hydrogen Bonds in Secondary Structure Elements B2.8.4 The α-Helix B2.8.5 Packing of the α-Helix B2.8.6 φ and ψ Torsion Angles of the α-Helix B2.8.7 Two Enantiomeric α-Helices B2.8.8 Geometry Described with Pitch and Rise B2.8.9 Helix Macro-Dipole B2.8.10 Amphipathic Character of the α Helix B2.8.11 3(10)-Helix and π-Helix B2.8.12 Helices Geometrical Parameters B2.8.13 Occurrence of Helices in Proteins

B2.8.14 The β-Sheet B2.8.15 The β-Strand Unit B2.8.16 φ and ψ Torsion Angles in β-Sheets B2.8.17 Stability of the β-Sheet B2.8.18 Parallel and Anti-Parallel β-Sheets B2.8.19 Occurrence of β-Sheets in Proteins B2.8.20 Twist of the β-sheet B2.8.21 Turns B2.8.22 β-Turns B2.8.23 φ and ψ Torsion Angles of β Turns B2.8.24 Non-Regular Coil and Loops B2.8.25 Coil B2.8.26 Loops

B2.9. Super-Secondary Structure (Motifs) B2.9.1 Super-Secondary Structures and Motifs B2.9.2 Classification of Super-Secondary Structures B2.9.3 All β super-secondary structures B2.9.4 β-Hairpin B2.9.5 β-Meander B2.9.6 Greek-Key B2.9.7 All α Super-Secondary Structures B2.9.8 αα-Hairpin B2.9.9 αα-Corners B2.9.10 EF Hand B2.9.11 Helix-Turn-Helix B2.9.12 Four-Helix Bundle B2.9.13 Mixed α & β Super-Secondary Structures B2.9.14 β-α-β Motif B2.9.15 Rossmann Fold

B2.10. Tertiary Structure B2.10.1 Tertiary Structure B2.10.2 Domains in the Tertiary Structure B2.10.3 Domains and Sequence B2.10.4 Domains and Function B2.10.5 New Look on Proteins Levels of Architecture B2.10.6 Blurred Boundaries B2.10.7 Tertiary Structure Patterns: Folds B2.10.8 Fold Diversity B2.10.9 Protein Folds and Function B2.10.10 Classification of Protein Folds B2.10.11 Mainly α Folds B2.10.12 Mainly β Folds B2.10.13 Mixed α-β Folds B2.10.14 Databases of Folds

B2.11. Quaternary Structure B2.11.1 Quaternary Structure B2.11.2 Dimers, Trimers, Tetramers etc... B2.11.3 Homo-Oligomers: Identical Polypeptide Chains B2.11.4 Hetero-Oligomers: Different Polypeptide Chains

B2.12. Structural Classification of Proteins B2.12.1 Structural Classification of Proteins B2.12.2 Globular Proteins B2.12.3 Hydrophilic Surface and Hydrophobic Core B2.12.4 Hydrophobic Effect B2.12.5 Hydration Layer B2.12.6 Membrane Proteins B2.12.7 The Lipid Bilayer B2.12.8 Membrane Model B2.12.9 Membrane Proteins Types B2.12.10 Transmembrane Protein Surface B2.12.11 Transmembrane Protein Folds B2.12.12 Fibrous Proteins B2.12.13 Collagen B2.12.14 α-Keratin B2.12.15 Silk Fibroin

B2.13. Perspectives B2.13.1 The History B2.13.2 The Pharmaceutical Connection B2.13.3 A Fascinating Field

B2.14. CHAPTER QUIZZES (Available only in Teaching Package) B2.14.1 Quiz 1 B2.14.2 Quiz 2 B2.14.3 Quiz 3 B2.14.4 Quiz 4 B2.14.5 Quiz 5 B2.14.6 Quiz 6 B2.14.7 Quiz 7 B2.14.8 Quiz 8 B2.14.9 Quiz 9 B2.14.10 Quiz 10 B2.14.11 Quiz 11 B2.14.12 Quiz 12 B2.14.13 Quiz 13 B2.14.14 Quiz 14 B2.14.15 Quiz 15 B2.14.16 Quiz 16 B2.14.17 Quiz 17 B2.14.18 Quiz 18 B2.14.19 Quiz 19 B2.14.20 Quiz 20 B2.14.21 Quiz 21 B2.14.22 Quiz 22 B2.14.23 Quiz 23 B2.14.24 Quiz 24 B2.14.25 Quiz 25 B2.14.26 Quiz 26 B2.14.27 Quiz 27 B2.14.28 Quiz 28 B2.14.29 Quiz 29

B2.14.30 Quiz 30 B2.14.31 Quiz 31 B2.14.32 Quiz 32 B2.14.33 Quiz 33 B2.14.34 Quiz 34 B2.14.35 Quiz 35 B2.14.36 Quiz 36 B2.14.37 Quiz 37 B2.14.38 Quiz 38 B2.14.39 Quiz 39 B2.14.40 Quiz 40 B2.14.41 Quiz 41 B2.14.42 Quiz 42 B2.14.43 Quiz 43 B2.14.44 Quiz 44 B2.14.45 Quiz 45 B2.14.46 Quiz 46 B2.14.47 Quiz 47 B2.14.48 Quiz 48 B2.14.49 Quiz 49 B2.14.50 Quiz 50 B2.14.51 Quiz 51 B2.14.52 Quiz 52 B2.14.53 Quiz 53 B2.14.54 Quiz 54 B2.14.55 Quiz 55 B2.14.56 Quiz 56 B2.14.57 Quiz 57 B2.14.58 Quiz 58 B2.14.59 Quiz 59 B2.14.60 Quiz 60 B2.14.61 Quiz 61 B2.14.62 Quiz 62 B2.14.63 Quiz 63 B2.14.64 Quiz 64 B2.14.65 Quiz 65 B2.14.66 Quiz 66 B2.14.67 Quiz 67 B2.14.68 Quiz 68 B2.14.69 Quiz 69 B2.14.70 Quiz 70 B2.14.71 Quiz 71 B2.14.72 Quiz 72 B2.14.73 Quiz 73 B2.14.74 Quiz 74 B2.14.75 Quiz 75 B2.14.76 Quiz 76 B2.14.77 Quiz 77 B2.14.78 Quiz 78 B2.14.79 Quiz 79 B2.14.80 Quiz 80

B2.14.81 Quiz 81 B2.14.82 Quiz 82 B2.14.83 Quiz 83 B2.14.84 Quiz 84 B2.14.85 Quiz 85 B2.14.86 Quiz 86 B2.14.87 Quiz 87 B2.14.88 Quiz 88 B2.14.89 Quiz 89

B4. MOLECULAR DOCKING

B4.1. Introduction to Computational Docking B4.1.1 Molecular Recognition B4.1.2 Molecular Recognition Process: Molecular Docking B4.1.3 Understanding Molecular Recognition B4.1.4 Molecular Docking Models B4.1.5 The Lock and Key Theory B4.1.6 The Induced-Fit Theory B4.1.7 The Conformation Ensemble Model B4.1.8 From the Lock and Key to the Ensemble Model B4.1.9 Experimental Methods to Study Molecular Docking B4.1.10 Limitations of Experimental Techniques B4.1.11 A Bottleneck in Drug Discovery B4.1.12 Triggering the Computational Docking Discipline B4.1.13 Definition of Computational Docking B4.1.14 Applications of Computational Docking

B4.2. The Docking Problem B4.2.1 The Docking Problem B4.2.2 Great Diversity of Molecular Interactions B4.2.3 Atomic Basis of Molecular Recognition B4.2.4 Definition of the "Pose" B4.2.5 Docking Viewed as a Black Box B4.2.6 Current Computational Docking Programs B4.2.7 Simulation and non-Simulation Approaches B4.2.8 Simulation Approaches B4.2.9 Non-Simulation Approaches B4.2.10 Molecular Complementarity in Computational Docking B4.2.11 Shape Complementarity B4.2.12 Chemical Complementarity B4.2.13 Energy Dictates Molecular Associations B4.2.14 Find a Complex that Minimizes the Energy B4.2.15 Accounting for Molecular Flexibility in Docking B4.2.16 Flexible Docking: Increasing Levels of Complexity B4.2.17 Initial Data and Nature of the Docking Difficulty B4.2.18 Bound Docking B4.2.19 Unbound Docking B4.2.20 Modeled Docking B4.2.21 The Three Generations in Computational Docking B4.2.22 Three Components of Docking Software

B4.3. System Representation B4.3.1 Molecular Representation B4.3.2 Atomic Representation B4.3.3 Complexity of the Atomic Repesentation B4.3.4 Internal Coordinates B4.3.5 Protein Preparation B4.3.6 Small Molecule Preparation B4.3.7 Surface Representation B4.3.8 Molecular Surface Matching B4.3.9 Surface-Based Representation B4.3.10 Accessible Surface Area B4.3.11 Solvent Contact & Reentrant Surfaces B4.3.12 Example of Contact & Reentrant Surface B4.3.13 Describing the Molecular Shape B4.3.14 Connolly's Contact and Reentrant Surfaces B4.3.15 Sparse Surface B4.3.16 Delaunay Triangulation B4.3.17 "Knob" and "Hole" Descriptors B4.3.18 Using Knobs and Holes for Complementarity B4.3.19 Other Examples of Shape Descriptors B4.3.20 Grid Representation B4.3.21 Use of GRID Potentials to Simplify the Docking B4.3.22 Assessing Shape Complementarity Using Grid

B4.4. Scoring Methods B4.4.1 Need to Assess the Quality of Docked Complexes B4.4.2 A Good Understanding of the Binding B4.4.3 Important Questions B4.4.4 Molecular Determinants for Binding B4.4.5 Interaction Forces and Binding Energies B4.4.6 Favorable Forces B4.4.7 Unfavorable Forces B4.4.8 Desolvation Energies B4.4.9 Entropic Effects B4.4.10 Calculation of the Binding Energies B4.4.11 Free Energy Equations B4.4.12 Conversion of K to Energies B4.4.13 Difficulty of Calculating Free Energies of Binding ∆G B4.4.14 Approximating ∆G by Molecular Mechanics B4.4.15 Force-Field Calculations B4.4.16 CHARMM Force Field to Score the Docking B4.4.17 Approximating ∆G by Quantum Mechanics B4.4.18 Development of Scoring Functions for Docking B4.4.19 Scoring Functions B4.4.20 Empirical Scoring Functions B4.4.21 Example of Empirical Scoring Function B4.4.22 Knowledge-Based Scoring Functions B4.4.23 The Statistical Analyses B4.4.24 Knowledge-Based Potentials B4.4.25 The DrugScore Program B4.4.26 DrugScore: The Thrombin Example B4.4.27 Refinement of Scoring Functions

B4.4.28 Other Scoring Methods B4.4.29 Shape and Property Complementarity Scoring B4.4.30 Method to Measure Shape Complementarity B4.4.31 Free Energy Perturbation

B4.5. Rigid Docking Methods B4.5.1 Docking Algorithms B4.5.2 The Mathematical Problem B4.5.3 Two Docking Philosophies B4.5.4 The Feature-Based Matching Approach B4.5.5 Docking Using Feature-Based Methods B4.5.6 Match Complementarity or Similarity Features B4.5.7 Components of Feature-Based Matching Methods B4.5.8 Step 1: Feature Extraction B4.5.9 Step 2: Feature Matching B4.5.10 Step 3: Transformation (Assembly) B4.5.11 Step 4: Filtering and Scoring B4.5.12 Virtual Screening and De Novo Design B4.5.13 Programs with Feature-Based Matching Methods B4.5.14 Algorithms of Matching B4.5.15 Clique-Search Based Approaches B4.5.16 Goal of the Docking Algorithm B4.5.17 Distance Compatibility Graph B4.5.18 Clique Detection Methods B4.5.19 Pose-Clustering B4.5.20 Searching for Compatible Triangles B4.5.21 Transformation that Align a Maximum of Triangles B4.5.22 Complementarity and Similarity Matching B4.5.23 Speed up of Pose-Clustering B4.5.24 The Bottleneck of Pose-Clustering B4.5.25 Geometric Hashing B4.5.26 Fast Retrieval of Matching Features B4.5.27 Invariant Representation of Features B4.5.28 Improvement of Pose-Clustering B4.5.29 PatchDock Example B4.5.30 The Stepwise Search Approach B4.5.31 Components of a Stepwise Docking Program B4.5.32 Exhaustive and Stochastic Search B4.5.33 Exhaustive vs. Stochastic Search B4.5.34 Exhaustive Search B4.5.35 Mapped-Grid Method B4.5.36 Physico-Chemical Properties of the Receptor B4.5.37 Assessing Shape Complementarity B4.5.38 Fast-Fourier Transform (FFT) Method B4.5.39 FFT vs. Exhaustive Method B4.5.40 FFT - Geometric Shape Complementarity B4.5.41 FFT - Different Scores B4.5.42 Docking of Plastocyanin and Cytochrome C B4.5.43 Spherical Polar Fourier Correlations - Fast FFT B4.5.44 Stochastic Algorithms B4.5.45 A Typical Computational Docking Program B4.5.46 Optimization Methods to Find the Best Solution

B4.5.47 Monte Carlo Methods B4.5.48 Simulated Annealing B4.5.49 Genetic Algorithms (GA) B4.5.50 General Principle of GA B4.5.51 Creating a New Generation B4.5.52 Simulating the Reproduction Process B4.5.53 Steps in Genetic Algorithms B4.5.54 Lamarckian Genetic Algorithm B4.5.55 Tabu Search B4.5.56 Tabu Algorithm B4.5.57 Avoiding Being Trapped in a Local Minimum B4.5.58 Better Exploration of the Space B4.5.59 The Hybrid Docking Method

B4.6. Methods for Incorporating Flexibility B4.6.1 Implementation of Flexibility into Docking Software B4.6.2 Degrees of Freedom in Flexible Docking B4.6.3 Possible Classification of Methods for Flexibility B4.6.4 Classification of Methods B4.6.5 Incorporating Small Molecule Flexibility B4.6.6 Modeling Small Molecules as Flexible Entities B4.6.7 Small Molecule Flexibility B4.6.8 Integration of Ligand Flexibility and Protein Structure B4.6.9 Methods for Handling Ligand Flexibility Explicitly B4.6.10 The Ensemble Docking Method B4.6.11 Advantage of the Ensemble Docking Method B4.6.12 The FLOG Software B4.6.13 Problem of the Ensemble Docking Approach B4.6.14 The Improved Ensemble Docking Method B4.6.15 Remove Redundancy in the Rigid Fragment B4.6.16 Remove Redundancy in the Flexible Fragment B4.6.17 Score: Sum of Atom Interactions B4.6.18 Step-1: Conformational Analysis B4.6.19 Step-2: Superimposition and Positioning B4.6.20 Step-3: Conformational Analysis B4.6.21 Dramatic Improvement in Computing Time B4.6.22 Efficient Treatment of Clashes B4.6.23 Validation of the Lorber-Shoichet Method B4.6.24 Extension to Analog Compounds B4.6.25 The Fragmentation Docking Method B4.6.26 Place-and-Join Algorithm B4.6.27 Principle of the Place-and-Join Method B4.6.28 Difficulty of the Place and Join Method B4.6.29 Incremental-Based Methods B4.6.30 Incremental Algorithm B4.6.31 Stochastic Search Methods B4.6.32 GOLD B4.6.33 Incorporating Protein Flexibility B4.6.34 Importance of Modeling Protein Flexibility B4.6.35 Historical Note B4.6.36 Flexibility Through Soft Scoring Functions B4.6.37 Reduce the Importance of Steric Clashes

B4.6.38 Soft Van der Waals Repulsion Functions B4.6.39 Decreasing Van der Waals Radii B4.6.40 Soft Electrostatic Repulsion Potentials B4.6.41 Soft Scoring Functions in Protein-Protein Docking B4.6.42 Implicit Flexibility in Protein-Protein Docking B4.6.43 Problems with Soft Scoring B4.6.44 Soft Scoring as a First Filtering Method B4.6.45 Protein Side-Chains Flexibility B4.6.46 Importance of Modeling Side-Chain Mobility B4.6.47 Determine the Optimum Combination of Side-Chains B4.6.48 Combinatorial Explosion B4.6.49 Side Chain Rotamer Libraries B4.6.50 From Folding to Docking B4.6.51 The Leach Algorithm B4.6.52 Generation and Minimization of Complexes B4.6.53 Other Optimization Methods B4.6.54 Restricting Searches and Minimizations B4.6.55 Identify Key Residues for the Interaction B4.6.56 Restrict the Search to Exposed Side Chains B4.6.57 Backbone and Side Chain Flexibility B4.6.58 Conventional Methods not Adapted B4.6.59 The Multiple Protein Structure (MPS) Approach B4.6.60 Principle of the MPS Approach B4.6.61 Sources of Multiple Protein Structures B4.6.62 MPS: a Good Model for the Recognition Process B4.6.63 How the MPS are Exploited? B4.6.64 Successive and Independent Docking Treatments B4.6.65 Acetylcholinesterase Example B4.6.66 The United Protein Approach B4.6.67 Key Concept of FlexE B4.6.68 Remove Redundant Information B4.6.69 FlexE: Incompatibility Graph B4.6.70 FlexE: Search & Scoring B4.6.71 The Average Grid Approach B4.6.72 Single Grid Combining MPS Information B4.6.73 Scoring Tolerance with MPS-based Grids B4.6.74 Average Grid Approach vs. Soft Scoring B4.6.75 Dynamic Pharmacophore-Based Approach B4.6.76 Dynamic Pharmacophore Model for HIV-1 Integrase B4.6.77 Domain Movements B4.6.78 Example of Calmodulin Domain Movements B4.6.79 Conventional Modeling Methods are not Suited B4.6.80 Intrinsic Flexibility B4.6.81 Hinge-Bent Movements B4.6.82 Automated Methods for Hinge Detection B4.6.83 Incorporating Hinge-Bent Movements in Docking B4.6.84 Docking with Hinge-Bent Movements B4.6.85 Ball-and-Socket Motions

B4.7. Uses of Docking in Research B4.7.1 Computational Docking in Drug Discovery B4.7.2 Virtual Screening

B4.7.3 Increasing HTS Hit Rates B4.7.4 Confirm Choice of Prototype Structure B4.7.5 Manual Design of a New Scaffold B4.7.6 New Cores from a Database of Scaffolds B4.7.7 De Novo Design of Spacers B4.7.8 Modulating Protein-Protein Interactions B4.7.9 Query for 3D Database Searching B4.7.10 Creative Molecular Design Conditions B4.7.11 Design of Combinatorial Libraries B4.7.12 Understanding SAR B4.7.13 Reducing Multiple Hypotheses to a Single One B4.7.14 Series Optimization B4.7.15 Explaining Incomprehensible Observations B4.7.16 Identifying Incorrect Working Hypotheses B4.7.17 Align Chemically Unrelated Molecules in 3D B4.7.18 Improving the Solubility of a Ligand B4.7.19 Understand the Intrinsic Limitations of a Scaffold B4.7.20 Assessing the Potential of a Hit B4.7.21 Elucidating Exact Mode of Action B4.7.22 Assessing Multiple Alignment Hypotheses B4.7.23 Molecular Mimicry B4.7.24 Computational Validation of Hypotheses

B4.8. Docking Softwares B4.8.1 Docking Programs B4.8.2 Dock B4.8.3 Autodock B4.8.4 DockVision B4.8.5 DockIt B4.8.6 FlexX B4.8.7 Ligin B4.8.8 FT-Dock B4.8.9 GOLD B4.8.10 GRAMM B4.8.11 Hex B4.8.12 eHiTS B4.8.13 LigandFit B4.8.14 FRED B4.8.15 Glide B4.8.16 Which Software is Better?

B4.9. Future and Perspectives B4.9.1 Limitations in Computational Docking B4.9.2 Trade Off Between Efficiency and Accuracy B4.9.3 Screening Large Chemical Libraries B4.9.4 A Two Step Strategy B4.9.5 High-throughput Docking Using Grid-Computing B4.9.6 How Does it Work? B4.9.7 Wide In Silico Docking On Malaria (WISDOM) B4.9.8 Enrichment Factor B4.9.9 Current Status of the Docking Problem B4.9.10 The Docking Bottlenecks

B4.9.11 More Effective Scoring Functions B4.9.12 Modeling the Solvent B4.9.13 Validation of Scoring Functions B4.9.14 Target Trainable Scoring Functions B4.9.15 Database of Decoys B4.9.16 Consensus Scoring B4.9.17 The Molecular Flexibility Challenge B4.9.18 Developing Better Models of Flexibility B4.9.19 Importance of Visual Docking B4.9.20 Requirement for Manual Docking B4.9.21 Illustration of Manual Docking B4.9.22 Manual Docking with Solid Models B4.9.23 Virtual Reality Docking System B4.9.24 Example of Docking using CAVE B4.9.25 Synergy Between Interactive & Automated Docking B4.9.26 Interactive Computer-Guided Docking B4.9.27 Protein-Protein Docking Benchmarks B4.9.28 The CAPRI Competition B4.9.29 Six Weeks for Submitting Predicted Complexes B4.9.30 Assessment of the Predictions B4.9.31 A New CAPRI Scoring Category B4.9.32 CAPRI History and Experience B4.9.33 Perspectives

B4.10. CHAPTER QUIZZES (Available only in Teaching Package) B4.10.1 Quiz 1 B4.10.2 Quiz 2 B4.10.3 Quiz 3 B4.10.4 Quiz 4 B4.10.5 Quiz 5 B4.10.6 Quiz 6 B4.10.7 Quiz 7 B4.10.8 Quiz 8 B4.10.9 Quiz 9 B4.10.10 Quiz 10 B4.10.11 Quiz 11 B4.10.12 Quiz 12 B4.10.13 Quiz 13 B4.10.14 Quiz 14 B4.10.15 Quiz 15 B4.10.16 Quiz 16 B4.10.17 Quiz 17 B4.10.18 Quiz 18 B4.10.19 Quiz 19 B4.10.20 Quiz 20 B4.10.21 Quiz 21 B4.10.22 Quiz 22 B4.10.23 Quiz 23 B4.10.24 Quiz 24 B4.10.25 Quiz 25 B4.10.26 Quiz 26 B4.10.27 Quiz 27

B4.10.130 Quiz 130 B4.10.131 Quiz 131 B4.10.132 Quiz 132 B4.10.133 Quiz 133 B4.10.134 Quiz 134 B4.10.135 Quiz 135 B4.10.136 Quiz 136 B4.10.137 Quiz 137 B4.10.138 Quiz 138

B6. MOLECULAR DYNAMICS

B6.1. Introduction B6.1.1 What is Molecular Dynamics? B6.1.2 Ergodicity Assumption B6.1.3 Historical Note B6.1.4 Four Types of Applications of MD Simulation B6.1.5 Macroscopic Behavior B6.1.6 MD Between Experiment and Theory B6.1.7 Refinement and Validation of MD B6.1.8 Access to Unavailable Data B6.1.9 MD Applied to Living Systems B6.1.10 Example 1: Relation between Structure and Function B6.1.11 Example 2: Relation between Structure and Function B6.1.12 Example 3: Relation between Structure and Function B6.1.13 Proteins are not Static B6.1.14 Thermal Fluctuations B6.1.15 Conformational Changes B6.1.16 MD as a Way to Study Molecular Motions B6.1.17 Mimicking the Way a Molecule Moves B6.1.18 Average Properties Derived from MD Trajectories B6.1.19 Calculating Molecular Properties of a System B6.1.20 Studying Thermodynamic Properties B6.1.21 Studying Kinetic Properties B6.1.22 Studying Conformational Changes

B6.2. Energy Calculations B6.2.1 Calculation of Forces & Energies B6.2.2 Two Families of MD Methods B6.2.3 The Quantum Mechanics Approach B6.2.4 Quantum Methods are Computationally Expensive B6.2.5 The Classical Mechanics Approach B6.2.6 Classical vs. Quantum Methods B6.2.7 Classical MD Simulates the Dynamics of the Nuclei B6.2.8 The Born-Oppenheimer Approximation B6.2.9 Force Field for Classical MD B6.2.10 General Force Field Equation B6.2.11 Stretching Term B6.2.12 Bending Term B6.2.13 Torsional Term B6.2.14 Van der Waals Term

B6.2.15 Electrostatic Term B6.2.16 A Couple of Practical Remarks B6.2.17 The Link between Forces and Potential Energies

B6.3. MD Algorithm B6.3.1 Newton's Equation of Motion B6.3.2 Prediction of Next Position B6.3.3 Integration Step B6.3.4 Molecular Dynamics Algorithm B6.3.5 Trajectories: List of Positions and Velocities B6.3.6 Atomic Positions at Time (t+∆t) B6.3.7 Solving Newton's Equations B6.3.8 Numerical Integration with the Verlet Formula B6.3.9 Summary of the MD Algorithm

B6.4. Fundamental Issues B6.4.1 Time Step B6.4.2 Choice of Time Step B6.4.3 Time-Scale of Molecular Motions B6.4.4 Method for Increasing the Time Step: Constrained MD B6.4.5 Periodic Boundary Condition B6.4.6 Importance of Long Range Forces B6.4.7 The Distance Cutoff Concept B6.4.8 Problems with Cutoffs B6.4.9 Switching Functions B6.4.10 Choice of the Cutoff B6.4.11 Strategies to Incorporate the Solvent B6.4.12 Implicit Solvent Model B6.4.13 Explicit Solvent Molecules B6.4.14 The Ewald Summation Method

B6.5. MD Protocols B6.5.1 Typical Steps for MD Simulation B6.5.2 Define and Prepare the Molecular System B6.5.3 Preparing the Coordinates B6.5.4 Manual Assembly of a Complex Molecular System B6.5.5 Solvating the System B6.5.6 Addition of Counterions B6.5.7 Choose the MD Package & Force-Field B6.5.8 Extending the Parameterization of the Force Field B6.5.9 Configuration Parameters of the MD Simulation B6.5.10 Time-step B6.5.11 Length of the Simulation B6.5.12 Distance Cutoffs B6.5.13 Reassigning the List of Non-Bonded Atom Pairs B6.5.14 Initial Velocities B6.5.15 SHAKE Parameters B6.5.16 Preliminary Treatments: Minimization & Equilibration B6.5.17 Minimization of Initial Coordinates B6.5.18 Thermal Equilibration of the System B6.5.19 Maxwell-Boltzmann Equation B6.5.20 Molecular Dynamics Run B6.5.21 Conservation of the Total Energy

B6.5.22 Test Energy Fluctuation B6.5.23 Possible Crash of the Program

B6.6. Analysis of the Results of the MD Simulation B6.6.1 Analysis of the Results B6.6.2 Thermodynamic Properties B6.6.3 Kinetic Properties B6.6.4 Visualization of Time Dependent Properties B6.6.5 Deriving Average Properties from the Trajectory B6.6.6 Average Energies B6.6.7 Specific Heat B6.6.8 Radius of Gyration B6.6.9 Local Motions B6.6.10 Interesting Motions B6.6.11 Movies

B6.7. Examples of MD Applications B6.7.1 First µs MD Simulation of Protein Folding B6.7.2 Protein-Folding Dynamics using Folding@Home B6.7.3 MD of the Complete Satellite Tobacco Mosaic Virus B6.7.4 How Does RNA Moves Along DNA?

B6.8. Using MD for Conformational Sampling B6.8.1 The Sampling Approach in Optimization Problems B6.8.2 MD as a Tool for Sampling the Space B6.8.3 Sampling to Find the Global Minimum B6.8.4 Conformational Analysis of a Small Molecule B6.8.5 Conformational Analysis of Biomolecules B6.8.6 Loop Conformation in Proteins B6.8.7 How Do Ligands and Receptors Bind Together? B6.8.8 Protein Folding Problem B6.8.9 Systematic and Random Sampling B6.8.10 Alternative Methods for Sampling B6.8.11 Monte Carlo Random Search B6.8.12 Monte Carlo Algorithm B6.8.13 Metropolis Monte Carlo Approach B6.8.14 Simulated Annealing B6.8.15 Diffusion Equation Methods B6.8.16 Replica Exchange MD Method

B6.9. MD for the Calculation of Binding Energies B6.9.1 In Silico Drug Design B6.9.2 FEP Approach for Calculating Binding Energies B6.9.3 FEP Thermodynamic Cycle B6.9.4 Exploiting the Thermodynamic Cycle B6.9.5 FEP: Computational Alchemy B6.9.6 Limitation of FEP Method B6.9.7 FEP Study: Example 1 B6.9.8 FEP Study: Example 2

B6.10. MD Packages B6.10.1 Examples of Popular MD Packages B6.10.2 NAMD B6.10.3 VMD

B6.10.4 TINKER B6.10.5 AMBER B6.10.6 CHARMM B6.10.7 GROMACS B6.10.8 MOIL B6.10.9 GROMOS

B6.11. Limitations and Perspectives B6.11.1 Limitations of MD B6.11.2 Error Introduced by Empirical Potentials? B6.11.3 Trade Off Between Efficiency and Accuracy B6.11.4 Supramolecular Systems B6.11.5 Long Range Forces as a Computational Bottleneck B6.11.6 Time and Size Limitations B6.11.7 Alternative Techniques for Long Time Dynamics B6.11.8 From Impossible to Feasible B6.11.9 Classical MD is not for Bond Breaking Mechanisms B6.11.10 Present and Future

B6.12. CHAPTER QUIZZES (Available only in Teaching Package) B6.12.1 Quiz 1 B6.12.2 Quiz 2 B6.12.3 Quiz 3 B6.12.4 Quiz 4 B6.12.5 Quiz 5 B6.12.6 Quiz 6 B6.12.7 Quiz 7 B6.12.8 Quiz 8 B6.12.9 Quiz 9 B6.12.10 Quiz 10 B6.12.11 Quiz 11 B6.12.12 Quiz 12 B6.12.13 Quiz 13 B6.12.14 Quiz 14 B6.12.15 Quiz 15 B6.12.16 Quiz 16 B6.12.17 Quiz 17 B6.12.18 Quiz 18 B6.12.19 Quiz 19 B6.12.20 Quiz 20 B6.12.21 Quiz 21 B6.12.22 Quiz 22 B6.12.23 Quiz 23 B6.12.24 Quiz 24 B6.12.25 Quiz 25 B6.12.26 Quiz 26 B6.12.27 Quiz 27 B6.12.28 Quiz 28 B6.12.29 Quiz 29 B6.12.30 Quiz 30 B6.12.31 Quiz 31 B6.12.32 Quiz 32

B6.12.84 Quiz 84 B6.12.85 Quiz 85 B6.12.86 Quiz 86 B6.12.87 Quiz 87 B6.12.88 Quiz 88 B6.12.89 Quiz 89 B6.12.90 Quiz 90 B6.12.91 Quiz 91 B6.12.92 Quiz 92 B6.12.93 Quiz 93 B6.12.94 Quiz 94 B6.12.95 Quiz 95 B6.12.96 Quiz 96 B6.12.97 Quiz 97 B6.12.98 Quiz 98 B6.12.99 Quiz 99 B6.12.100 Quiz 100 B6.12.101 Quiz 101 B6.12.102 Quiz 102 B6.12.103 Quiz 103 B6.12.104 Quiz 104 B6.12.105 Quiz 105 B6.12.106 Quiz 106 B6.12.107 Quiz 107 B6.12.108 Quiz 108 B6.12.109 Quiz 109 B6.12.110 Quiz 110 B6.12.111 Quiz 111 B6.12.112 Quiz 112 B6.12.113 Quiz 113

C. DRUG DISCOVERY

C2. PRINCIPLES OF RATIONAL DRUG DESIGN

C2.1. Rational Drug Design C2.1.1 Drug Design Basis: Molecular Recognition C2.1.2 Lock-and-Key Model C2.1.3 Induced-Fit Model C2.1.4 Rational Drug Design C2.1.5 Rational Drug Design Process C2.1.6 Receptor-Based Drug Design C2.1.7 Pharmacophore-Based Drug Design

C2.2. Pharmacophore-Based Design C2.2.1 Pharmacophore-Based Drug Design Approach C2.2.2 Similarity Concepts and Molecular Mimicry C2.2.3 Examples of Molecular Mimicry C2.2.4 ATP C2.2.5 Dopamine C2.2.6 Histamine

C2.2.7 Estradiol C2.2.8 Peptidomimetics C2.2.9 Strengths of Pharmacophore-Based Drug Design

C2.3. Receptor-Based Design C2.3.1 Design by Direct Interaction with Receptor Sites C2.3.2 Exploiting the Receptor Recognition Concepts C2.3.3 Initial Data in Receptor-Based Drug Design C2.3.4 Strengths of Receptor Based Drug Design

C2.4. Integration in a Global Perspective C2.4.1 Typical Projects C2.4.2 Exploit the Two Methods, Independently C2.4.3 Synergy Between the Two Approaches C2.4.4 Good Binding Models, the Synergy Condition C2.4.5 Ideal Situation C2.4.6 Example 1 C2.4.7 Example 2 C2.4.8 Integration in a Global Perspective C2.4.9 Pharmacophore-Based Drug Design C2.4.10 Receptor-Based Drug Design C2.4.11 Integrated Global Approach

C2.5. Challenge of the Genomics Era C2.5.1 The Genomic Era C2.5.2 A New Challenge in Drug Design

C2.6. Typical Projects C2.6.1 Typical Pharmacophore-Based Project C2.6.2 Typical Receptor-Based Project C2.6.3 Typical Genomic Project

C2.7. Perspectives C2.7.1 Retrospective Analysis of Drug Discovery C2.7.2 Initial Skepticism Towards Rational Drug Design C2.7.3 Success Stories in Rational Drug Design C2.7.4 Future Perspectives

C2.8. CHAPTER QUIZZES (Available only in Teaching Package) C2.8.1 Quiz 1 C2.8.2 Quiz 2 C2.8.3 Quiz 3 C2.8.4 Quiz 4 C2.8.5 Quiz 5 C2.8.6 Quiz 6 C2.8.7 Quiz 7 C2.8.8 Quiz 8 C2.8.9 Quiz 9 C2.8.10 Quiz 10 C2.8.11 Quiz 11 C2.8.12 Quiz 12 C2.8.13 Quiz 13 C2.8.14 Quiz 14 C2.8.15 Quiz 15

C2.8.16 Quiz 16 C2.8.17 Quiz 17 C2.8.18 Quiz 18 C2.8.19 Quiz 19 C2.8.20 Quiz 20 C2.8.21 Quiz 21 C2.8.22 Quiz 22

C3. STRUCTURE ACTIVITY RELATIONSHIPS

C3.1. Introduction C3.1.1 Structure Activity Relationships (SAR) C3.1.2 Aim of SAR Analyses C3.1.3 Results of a SAR Analysis C3.1.4 Principle: Alteration of an Active Substance C3.1.5 Development: a Single Modification at a Time C3.1.6 Iterative Process C3.1.7 Chemical Modifications and Medicinal Chemist Tools C3.1.8 Chemistry is the Limiting Factor C3.1.9 Role of the Functional Groups in the Reference Structure

C3.2. Probing H-Bond Interactions C3.2.1 Principle for Probing Hydrogen Bond Interactions C3.2.2 Hydroxyl: Hypothetical H-Bond Interactions C3.2.3 Testing the Existence of H-Bond Interactions C3.2.4 Testing H-Bond Donor Capability of the Hydroxyl C3.2.5 Testing H-Bond Acceptor Capability of the Hydroxyl C3.2.6 Example 1: Pyrazolopyrimidines C3.2.7 Example 2: Benzimidazoles C3.2.8 Example 3: Pyrrolopyrimidine C3.2.9 Example 4: Salicylanilides C3.2.10 Example 5: Isoflavones C3.2.11 Carbonyl: Hypothetical H-Bond Interactions C3.2.12 Testing the Existence of H-Bond Interactions C3.2.13 Example 1: Aminobenzophenones C3.2.14 Example 2: Thiazolidine-dione C3.2.15 Example 3: Pyrazolopyridines C3.2.16 Example 4: Naphthyl Ketones C3.2.17 Example 5: Cyclic Peptides C3.2.18 Amide C3.2.19 Testing the Existence of H-Bond Interactions C3.2.20 Testing H-Bond Acceptor Capability of the Carbonyl C3.2.21 Testing H-Bond Donor Capability of the Nitrogen C3.2.22 Example 1: Lactam Tricylic C3.2.23 Example 2: Pyrrolopyrimidinones C3.2.24 Primary Amines C3.2.25 Testing the Existence of H-Bond Interactions C3.2.26 Testing H-Bond Donor Capability of the Amines C3.2.27 Example 1: Imidazole Acetic Acids C3.2.28 Example 2: Salicylanilides C3.2.29 Secondary Amines

C3.2.30 Testing the Existence of H-Bond Interactions C3.2.31 Testing H-Bond Donor Capability of the Amines C3.2.32 Example 1: Imidazoquinoxalines C3.2.33 Example 2: Anilinopyrimidines C3.2.34 Example 3: Aminoquinazolines C3.2.35 Tertiary Amines C3.2.36 Testing the Existence of H-Bond Interactions C3.2.37 Example Dihydropyridopyrimidones C3.2.38 Aromatic Nitrogens C3.2.39 Testing the Existence of H-Bond Interactions C3.2.40 Testing H-Bond Donor Capability of the Amines C3.2.41 Example 1: Imidazoles and Oxazoles C3.2.42 Example 2: Pyrrolyl Ureas C3.2.43 Example 3: Anilinoquinazolines C3.2.44 Carboxylic Acids C3.2.45 Testing the Existence of H-Bond Interactions C3.2.46 Testing H-Bond Donor Capability of the COOH C3.2.47 Example 1: Imidazole Carboxylic Acids C3.2.48 Example 2: Pyrrolopyrimidines C3.2.49 Example 3: Peptide-Based Structures C3.2.50 Example 4: Aminoquinolones C3.2.51 Ethers C3.2.52 Testing the Existence of H-Bond Interactions C3.2.53 Example 1: Epothilone A C3.2.54 Example 2: Clofibrate C3.2.55 Example 3: Piperidine Renin Inhibitors C3.2.56 Cyano C3.2.57 Testing the Existence of H-Bond Interactions C3.2.58 Example 1: Anilinopyrimidines C3.2.59 Example 2: Quinolinecarbonitriles C3.2.60 Example 3: Pyrrolopyrimidines

C3.3. Probing Ionic Interactions C3.3.1 Principle for Probing Ionic Interactions C3.3.2 Carboxylates C3.3.3 Amines

C3.4. Probing Hydrophobic Interactions C3.4.1 Importance of Hydrophobic Interactions C3.4.2 Principles for Probing Hydrophobic Interactions C3.4.3 Alteration of Ring Size C3.4.4 Example 1: Probing of a Hydrophobic Pocket C3.4.5 Example 2 : Varying Ring Size C3.4.6 Example 3: Probing a Hydrophobic Pocket C3.4.7 Example 4: Fusion with Additional Rings C3.4.8 Homologation of Alkyl Chains C3.4.9 Example 1 of Homologation C3.4.10 Example 2 of Homologation C3.4.11 Example 3 of Homologation C3.4.12 Exploring the Width of a Hydrophobic Pocket C3.4.13 Example 1: Pyrazoles C3.4.14 Example 2: Indolinones

C3.4.15 Example 3: Pyridopyrimidines C3.4.16 Probing the Polarity of a Pocket C3.4.17 Example: Dopamine Antagonists

C3.5. Probing Other Interactions C3.5.1 Halogens C3.5.2 Example 1: COX-2 C3.5.3 Example 2: MDM2 C3.5.4 Example 3: Glycine Antagonists C3.5.5 Example 4: EGF-R Kinase Inhibitors C3.5.6 Probing Aromatic Ring Positions C3.5.7 KDR Inhibitors C3.5.8 Anthranilamide - Factor Xa Inhibitors C3.5.9 Tetrahydroisoquinoline - Serotonin 5-HT2A Ligands

C3.6. Modifications to Alter the Geometry of the Ligand C3.6.1 Modification to Alter the Geometry of the Ligand C3.6.2 The Amide Function C3.6.3 SAR Example with an Amide Moiety C3.6.4 Ortho Substitution of Aromatic Ring C3.6.5 Cis-Trans Isomers C3.6.6 Example 1: Cis and Trans Isomers C3.6.7 Example 2: Cis and Trans Isomers C3.6.8 Alter Stereochemistry C3.6.9 Rigid Analogs: SAR Principle C3.6.10 Example 1: GnRH Antagonists Rigidification C3.6.11 Example 2: AChE Rigidification C3.6.12 Example 3: p56-lck Inhibitors Rigidification C3.6.13 Example 4: Angiotensin-II Receptor Antagonists C3.6.14 Example 5: Dopaminergics Rigidification C3.6.15 Examples 6: Pseudo Rings C3.6.16 Anthranilamides C3.6.17 Phenoxyphenyltriazoles C3.6.18 Salicylanilides C3.6.19 Example 7: Good and Bad Rigidification C3.6.20 Example 8: Rigidification of a Flexible Molecule C3.6.21 Flexible Analogs: SAR Principle C3.6.22 Ring Suppression: Doxepin C3.6.23 Alteration of Interatomic Distances C3.6.24 Alteration of the Stereochemistry of the Ligand

C3.7. Complexity of SAR Analyses C3.7.1 Complexity of the Structures Concerned C3.7.2 Observations with no Explanations C3.7.3 Local Changes and Global Consequences C3.7.4 Small Modification that Substantially Alters the Geometry C3.7.5 Small Modification that Interferes with Other Interactions C3.7.6 Modification that Alters the Binding Orientation C3.7.7 Change that Alters a Characteristic of the Substance C3.7.8 pKa C3.7.9 LogP C3.7.10 Non Additivity of Biological Effects C3.7.11 Additivity in Steroids: Norethisterone

C3.7.12 Furanyl Example: Non-Additivity C3.7.13 Phenoxypyrimidines: Non Additivity C3.7.14 Being Trapped with Poor Biological Activities C3.7.15 The Dioxobenzothiazole Scaffold C3.7.16 The Combinatorial Era

C3.8. Example of Good Exploitation of SAR Complexity C3.8.1 The Banyu Story with the Urea Structure C3.8.2 Importance of the Entire Urea Moiety C3.8.3 Bioactive Conformation? C3.8.4 Design of Compounds with a Cis Conformation C3.8.5 Good Exploitation of the SAR Analyses

C3.9. CHAPTER QUIZZES (Available only in Teaching Package) C3.9.1 Quiz 1 C3.9.2 Quiz 2 C3.9.3 Quiz 3 C3.9.4 Quiz 4 C3.9.5 Quiz 5 C3.9.6 Quiz 6 C3.9.7 Quiz 7 C3.9.8 Quiz 8 C3.9.9 Quiz 9 C3.9.10 Quiz 10 C3.9.11 Quiz 11 C3.9.12 Quiz 12 C3.9.13 Quiz 13 C3.9.14 Quiz 14 C3.9.15 Quiz 15 C3.9.16 Quiz 16 C3.9.17 Quiz 17 C3.9.18 Quiz 18 C3.9.19 Quiz 19

C4. BIOISOSTERISM

C4.1. Introduction C4.1.1 What is Bioisosterism? C4.1.2 History of the Concept of Bioisosterism C4.1.3 Langmuir (1919): Comolecules and Isosteres C4.1.4 Grimm (1925) C4.1.5 Erlenmeyer (1932) C4.1.6 Friedman (1951): Concept of Bioisosteres C4.1.7 Thornber (1979) C4.1.8 Burger (1991) C4.1.9 Cheminformatics Era (1993) C4.1.10 Remark on Stereochemical Aspects

C4.2. Typical Isosteres C4.2.1 Classification of Typical Isosteres C4.2.2 Monovalent Atoms or Groups C4.2.3 Divalent Isosteres C4.2.4 Trivalent Atoms or Groups

C4.2.5 Tetrasubstituted Atoms C4.2.6 Ring Equivalents

C4.3. Medicinal Chemistry Use C4.3.1 A Simple Concept for Many Applications C4.3.2 Adapt Chemical Structures to Feasible Syntheses C4.3.3 Change the Type of Biological Activity C4.3.4 Example 1: Tricyclic Structures C4.3.5 Example 2: Angiotensin-II Receptor Ligands C4.3.6 Example 3: Steroid Analogs C4.3.7 Achieve Patentability C4.3.8 Mimic an Endogenous Ligand C4.3.9 Improve Potency C4.3.10 Improve Selectivity C4.3.11 Reduce Side Effects C4.3.12 Reduce Toxicity C4.3.13 Improve Bioavailability C4.3.14 Exploit Metabolism C4.3.15 Modify pKa C4.3.16 Increase Chemical Stability C4.3.17 Combinatorial Chemistry

C4.4. Examples of Natural Bioisosteres C4.4.1 Bioisosteres in Nature C4.4.2 Aminoacids C4.4.3 Nucleotides C4.4.4 Sugars C4.4.5 Lipids C4.4.6 Steroid Hormones C4.4.7 Carbohydrates C4.4.8 Catecholamines C4.4.9 Penicillins and Cephalosporins

C4.5. Dictionary of Bioisosteres C4.5.1 Dictionary of Bioisosteric Replacements C4.5.2 Allyl C4.5.3 Amide C4.5.4 Amino-Acids C4.5.5 Azomethine C4.5.6 Benzene C4.5.7 Carbonyl C4.5.8 Carboxylic Acid C4.5.9 Catechol C4.5.10 Ester C4.5.11 Halogen C4.5.12 Hydrogen C4.5.13 Hydroxyl C4.5.14 Indole C4.5.15 Isopropyl C4.5.16 Naphthalene C4.5.17 Peptide Surrogates C4.5.18 Phenol C4.5.19 Pyridine

C4.5.20 Ring C4.5.21 Sulfonyl C4.5.22 Spacer C4.5.23 Thioether C4.5.24 Thiourea

C4.6. Examples of Bioisosteric Transformations C4.6.1 Four Types of Bioisosteric Transformations C4.6.2 Ring-to-Ring Transformations C4.6.3 Example 1 C4.6.4 Example 2 C4.6.5 Example 3 C4.6.6 Chain-to-Ring Transformations C4.6.7 Example 1 C4.6.8 Example 2 C4.6.9 Example 3 C4.6.10 Ring-to-Chain Transformations C4.6.11 Example 1 C4.6.12 Example 2 C4.6.13 Example 3 C4.6.14 Chain-to-Chain Transformations C4.6.15 Example 1 C4.6.16 Example 2 C4.6.17 Example 3

C4.7. Commercial Bioisosteric Drugs: Examples C4.7.1 Angiotensin Receptor Blockers (ARBs) C4.7.2 COX-2 Inhibitors C4.7.3 Anti-Inflammatory NSAIDs C4.7.4 Antiarrhytmic Beta-Adrenergics C4.7.5 Neuroleptics C4.7.6 Anti-Ulcers C4.7.7 Male Erectile Dysfunction Drugs C4.7.8 Benzodiazepines C4.7.9 Antibacterial Sulfonamides C4.7.10 Beta-Lactam Antibiotics C4.7.11 Local Anesthetics C4.7.12 Glucocorticoid Steroids C4.7.13 Statin Drugs

C4.8. Patent Issues with Bioisosterism C4.8.1 Limits of Patent Infringements on Structures? C4.8.2 The Viagra-Levitra Case C4.8.3 The Diazepam-Clobazam Example C4.8.4 Patent Issues with Chiral Enantiomers C4.8.5 Patentable Drugs by Bioisosterism

C4.9. Programs and Databases on Bioisosterism C4.9.1 Computerized Systems C4.9.2 EMIL Program C4.9.3 BIOISOSTER Program and BIOSTER Database C4.9.4 The BIOISOSTER Program C4.9.5 Bioisosteric Morphing of the Query

C4.9.6 The Accelrys BIOSTER Database C4.9.7 Example of BIOSTER Database Content C4.9.8 BROOD Program C4.9.9 Brood Program for Bradykinin Antagonists C4.9.10 Organon IBIS Program C4.9.11 Novartis Program for Ring Bioisosteres C4.9.12 GlaxoSmithKline Program for Ring Replacements C4.9.13 COSMOsim Program for Bioisosteric Similarity C4.9.14 Cheminformatics Software C4.9.15 Daylight: MERLIN Program C4.9.16 Tripos: SYBYL Platform C4.9.17 MDL: ISENTRIS Program C4.9.18 MDL: DiscoveryGate Program C4.9.19 CAS: SciFinder Program

C4.10. Review Articles and Books C4.10.1 Review Articles on Bioisosterism C4.10.2 Books on Bioisosterism

C4.11. Limitations and the Future C4.11.1 The Receptor is the Ultimate Decider C4.11.2 The Multidimensional Nature of Bioisosterism C4.11.3 Shape C4.11.4 Lipophilicity C4.11.5 Electronic Distribution C4.11.6 Hydrogen-Bond Capacity C4.11.7 Can Bioisosterism be Quantified? C4.11.8 The Cheminformatics Era C4.11.9 Docking can be used to Generate Bioisosteres C4.11.10 Strategic and Financial Considerations C4.11.11 Examples of Success and Failures

C4.12. CHAPTER QUIZZES (Available only in Teaching Package) C4.12.1 Quiz 1 C4.12.2 Quiz 2 C4.12.3 Quiz 3 C4.12.4 Quiz 4 C4.12.5 Quiz 5 C4.12.6 Quiz 6 C4.12.7 Quiz 7 C4.12.8 Quiz 8 C4.12.9 Quiz 9 C4.12.10 Quiz 10 C4.12.11 Quiz 11 C4.12.12 Quiz 12 C4.12.13 Quiz 13 C4.12.14 Quiz 14 C4.12.15 Quiz 15 C4.12.16 Quiz 16 C4.12.17 Quiz 17 C4.12.18 Quiz 18 C4.12.19 Quiz 19 C4.12.20 Quiz 20

C4.12.21 Quiz 21 C4.12.22 Quiz 22 C4.12.23 Quiz 23 C4.12.24 Quiz 24 C4.12.25 Quiz 25 C4.12.26 Quiz 26 C4.12.27 Quiz 27 C4.12.28 Quiz 28 C4.12.29 Quiz 29 C4.12.30 Quiz 30 C4.12.31 Quiz 31 C4.12.32 Quiz 32 C4.12.33 Quiz 33 C4.12.34 Quiz 34 C4.12.35 Quiz 35 C4.12.36 Quiz 36 C4.12.37 Quiz 37 C4.12.38 Quiz 38 C4.12.39 Quiz 39 C4.12.40 Quiz 40 C4.12.41 Quiz 41 C4.12.42 Quiz 42 C4.12.43 Quiz 43

C5. SUCCESS STORIES IN DRUG DISCOVERY

C5.1. Captopril C5.1.1 Captopril C5.1.2 Captopril Target - ACE C5.1.3 Starting Point: Venom Causes Drop in Blood Pressure C5.1.4 Snake Venom Acts on the ACE Cascade C5.1.5 The Captopril Story C5.1.6 Developing an Assay for ACE C5.1.7 Isolating and Purifying the Venom Peptides C5.1.8 Encouraging Clinical Trial Results C5.1.9 Project Virtually Abandoned at Squibb C5.1.10 Back to the Project C5.1.11 Applying the Concepts to ACE C5.1.12 The Basis of ACE and CPA Similarity C5.1.13 X-ray Structure of CPA C5.1.14 Modeling the Active Site of ACE C5.1.15 Design of a Novel ACE Inhibitor C5.1.16 The Phe-Ala-Pro Pharmacophore C5.1.17 Finding a Lead Compound C5.1.18 The Discovery of Captopril C5.1.19 The Captopril Project Timeline C5.1.20 What Made the Success of the Project Possible? C5.1.21 Structure-Based Component C5.1.22 Ligand-Based Component C5.1.23 Following the Discovery C5.1.24 Recent Structure of Captopril-ACE Complex

C5.1.25 Other Drugs in This Class

C5.2. Aliskiren C5.2.1 Aliskiren C5.2.2 Aliskiren Target - Renin C5.2.3 Starting Point C5.2.4 The Aliskiren Story C5.2.5 The First Generation of Renin Inhibitors C5.2.6 The Second Generation of Renin Inhibitors C5.2.7 Peptidomimetic Approach was Unsuccessful C5.2.8 The Need for a New Non-Peptidic Scaffold C5.2.9 Novartis's New Rational Approach C5.2.10 3D Model of the Enzyme C5.2.11 Predicting the Bioactive Conformation of CGP38560 C5.2.12 The Design Strategy C5.2.13 Finding a Feasible Scaffold C5.2.14 Criteria for Good Candidate Molecules C5.2.15 The Parallel Design of Non-Peptide Renin Inhibitors C5.2.16 The THQ Series C5.2.17 Validation of the Design Strategy C5.2.18 The Phenoxy Series C5.2.19 Optimization of the Phenoxy Lead C5.2.20 The Indole Series C5.2.21 The Salicylamide Series C5.2.22 A Docking Experiment C5.2.23 Design of the Salicylamide Molecule C5.2.24 Transferrable SAR's C5.2.25 Example of Transferrable SAR's C5.2.26 Four Unrelated Lead Compounds C5.2.27 Browser of the Novartis Renin Inhibitor Leads C5.2.28 From Initial Lead to Aliskiren C5.2.29 The Aliskiren Project Timeline C5.2.30 What Made the Success of the Project Possible? C5.2.31 The Incorporation of Modeling C5.2.32 Modeling - The Key to Aliskiren's Success C5.2.33 Historical Document C5.2.34 Good Teamwork C5.2.35 Following the Discovery C5.2.36 X-rays of Complex with CGP38560 C5.2.37 X-ray Determination of Lead Inhibitors C5.2.38 The Indole X-ray C5.2.39 The S3sp sub-Pocket C5.2.40 Other Work on Drugs in this Class

C6. EXAMPLES OF SCAFFOLD MORPHING

C6.1. Introduction C6.1.1 Analog Design in Drug Discovery C6.1.2 Scaffold Morphing C6.1.3 Methods in Scaffold Morphing C6.1.4 Morphing by Elementary Modifications

C6.1.5 Morphing: From Real to Pseudo-Ring C6.1.6 Morphing: From Pseudo to Real Ring C6.1.7 Morphing by Bioisosteric Replacements C6.1.8 Drug Design Guided by Modeling Considerations C6.1.9 Case Studies in Ring Morphing

C6.2. Morphing by Elementary Modifications C6.2.1 EGF-R Protein Kinase Inhibitor Scaffold Morphing C6.2.2 Structure-Based Interpretation of Good Morphing

C6.3. Morphing: From Real to Pseudo-Ring C6.3.1 Morphing by Breaking a Bond in a Ring C6.3.2 Breaking a Bond in a Ring Creates Steric Repulsions C6.3.3 Ring Morphing with Pseudo Ring Concept C6.3.4 Pyrimidin-4-yl-ureas C6.3.5 PD-166285 Reference and Novartis Design C6.3.6 A Search in the Cambridge Structural Database C6.3.7 Ab-Initio Calculations C6.3.8 Synthesis of the Prototype Molecule C6.3.9 Biological Assays for Compound 1 C6.3.10 Docking of Compound 1 in c-Abl C6.3.11 Correlation of the Activities with Size of Gatekeeper C6.3.12 Alignment of Pyrimidin-4-yl urea and PD-166285 C6.3.13 P&G Discovered Independently the Same Molecule C6.3.14 Optimization Towards Lck Kinase Inhibition C6.3.15 Summary C6.3.16 Anthranilamide Scaffold C6.3.17 Structural Determinants of Anilinophtalazine Activity ? C6.3.18 Conformational Analyses C6.3.19 Bidentate Binding Mode Unlikely to Occur C6.3.20 Role of the Nitrogen Phtalazine Atoms C6.3.21 Database Searching C6.3.22 3D Electrostatic Potential C6.3.23 Synthesis of the Exact Anthranilamide Mimetic C6.3.24 Biological Tests C6.3.25 3D Overlay of Mimic Structures C6.3.26 Determinants for Anilinophtalazine KDR/Flt-1 Activities C6.3.27 Summary C6.3.28 Phenoxyphenyltriazoles C6.3.29 Requirements for Binding to the BZD Receptor C6.3.30 Design of an Estazolam Mimic C6.3.31 Conformational Analyses and Overlay with Diazepam C6.3.32 Chemical Synthesis of the Mimics C6.3.33 Confirmation of the Design Hypothesis C6.3.34 Summary C6.3.35 Salicylanilides C6.3.36 Genistein Structure and Alignment with Quinazoline 1 C6.3.37 3D Design of a Salicylanilide Scaffold C6.3.38 Possible Intramolecular H-Bonds in Salicylanilides C6.3.39 Synthesis of the Molecules C6.3.40 Biological Assays C6.3.41 Validity of the Hypotheses

C6.3.42 Summary

C6.4. Morphing: From Pseudo to Real Ring C6.4.1 Principle of Replacing a Pseudo-Ring by a Real one C6.4.2 Salicylamide Mimics C6.4.3 SAR of Salicylamide 1 C6.4.4 Removing the Hydroxyl or the Carbonyl C6.4.5 Analyzing if Ortho Electron Lone-Pair is Sufficient C6.4.6 Potent Inhibition at Ki at Different pH C6.4.7 Pseudo-Ring of 1 Binds as a Whole Unit C6.4.8 Design of Quinazoline Mimic C6.4.9 3D Alignment of Salicylamide 1 and Quinazoiline 2 C6.4.10 Conclusion C6.4.11 Summary C6.4.12 Pro-Leu-Gly-NH2 Peptide C6.4.13 The γ-Lactam Analog of Pro-Leu-Gly-NH2 C6.4.14 Design of Imidazolidinone and Diketopiperazine C6.4.15 Biological Tests C6.4.16 3D Alignment of Pro-Leu-Gly-NH2 and Mimics C6.4.17 Summary C6.4.18 Remoxipride Mimic C6.4.19 Bioactive Conformation of Desmethylremoxipride C6.4.20 Design of Rigid Analog C6.4.21 Chemical Synthesis C6.4.22 Biological Tests C6.4.23 3D Alignments C6.4.24 Summary C6.4.25 Rimonabant Mimic C6.4.26 Conformational Analysis of Rimonabant C6.4.27 Design of Rigid Analog C6.4.28 Chemical Synthesis C6.4.29 Biological Tests C6.4.30 3D Alignment of Rimonabant and Mimic C6.4.31 Summary

C6.5. Morphing by Bioisosteric Replacements C6.5.1 Bioisosterism C6.5.2 Bradykinin Antagonists C6.5.3 The Problem C6.5.4 The Stepwise Discovery of Cyclopropylamide C6.5.5 Retaining the two N-H groups C6.5.6 Mimicking the Nitrogen Pyridine Atom by a Carbonyl C6.5.7 Conformational Considerations C6.5.8 First Molecules Synthesized C6.5.9 Restoring Lipophilic Interactions C6.5.10 Reducing Ring Size C6.5.11 The Best Replacement C6.5.12 Additional Factors in Cyclopropyl Replacement C6.5.13 Torsion Angle N-C-C-N C6.5.14 Smaller Rings have Increasing π Character C6.5.15 Ring Strain and Geometry of Cyclopropyl C6.5.16 Bulkiness of the Hydrophobic Ring

C6.5.17 3D Alignment of 1 and the Cyclopropyl Surrogate C6.5.18 Summary C6.5.19 Factor Xa Inhibitors C6.5.20 Factor Xa Inhibitors with 2,3-Diaminopyridine Core C6.5.21 Replacement May be of General Utility C6.5.22 Surrogates Generated by Computer

C6.6. Conclusion C6.6.1 Concluding Remarks

D. STRUCTURE-BASED DRUG DESIGN

D1. STRUCTURE-BASED DRUG DESIGN: ANALYSIS

D1.1. Introduction D1.1.1 Receptor-Based Drug Design D1.1.2 Macromolecular Targets D1.1.3 Operational Strategy: Docking

D1.2. Analytical Process D1.2.1 The Analytical Process D1.2.2 Data Collection D1.2.3 Analysis D1.2.4 Design Phase

D1.3. Principles of Analysis D1.3.1 Analysis of the Morphology of the Active Site D1.3.2 Complexes with Ligands D1.3.3 Forces That Contribute to the Binding D1.3.4 The Molecular Recognition Process D1.3.5 Electrostatic D1.3.6 Hydrogen Bonding D1.3.7 Hydrophobic D1.3.8 Hydrophobic Interactions D1.3.9 Consider Hydrophobic Interactions D1.3.10 Elementary Hydrophobic Interactions D1.3.11 Example of Hydrophobic Binding D1.3.12 Strengthening Hydrophobic Interactions D1.3.13 Hydrogen Bond Features D1.3.14 Proteins Capabilities in Hydrogen Bonding D1.3.15 Consider Hydrogen Bond Formations D1.3.16 Elementary Hydrogen Bond Interactions D1.3.17 Example of the Hydrogen Bond Binding D1.3.18 Electrostatic Interactions D1.3.19 Elementary Electrostatic Interactions D1.3.20 Strength of Electrostatic Interactions D1.3.21 Example of Electrostatic Interactions

D1.4. Example of Tight Interactions D1.4.1 An Example of a Tight Ligand-Receptor Interaction D1.4.2 The X-ray Structure of the Biotin/Streptavidin D1.4.3 The Binding Mode of Biotin with Streptavidin

D1.5. Receptor & Ligand Flexibility D1.5.1 Flexibility of the Receptor D1.5.2 Flexibility of The Ligand D1.5.3 Entropic Effects

D1.6. Role of the Solvent D1.6.1 Solvation and Desolvation D1.6.2 The Role of the Solvent D1.6.3 Relay with Water Molecules

D1.7. Prediction of Binding Modes D1.7.1 Binding Modes Predicted by Analogy D1.7.2 Inversion of Binding Modes D1.7.3 Inverted Binding Mode of Olomoucine D1.7.4 Inverted Binding Mode of Methotrexate D1.7.5 Binding Mode Predicted from SAR

D1.8. Example of Binding Prediction D1.8.1 Pyrrolo-Pyrimidine & Quinazoline EGF-R Inhibitors D1.8.2 Novartis and Parke-Davis Opposite Binding Models D1.8.3 Controversy: Novartis & Parke-Davis Binding Modes D1.8.4 The Rational Drug Design Strategies D1.8.5 Binding Mode of ATP and Staurosporine D1.8.6 From Staurosporine to Pyrrolo-pyrimidine D1.8.7 The Novartis Binding Mode of Pyrrolo-pyrimidine D1.8.8 Parke-Davis Analyses the Quinazoline Scaffold D1.8.9 Parke-Davis Model of the Quinazoline Analogs D1.8.10 Parke-Davis Model Consistent with Observed SAR D1.8.11 The Controversy and the Correct Solution D1.8.12 Novartis-Like Binding Mode D1.8.13 Parke-Davis-Like Binding Mode D1.8.14 Conclusion

D1.9. Example of 3D SAR Analyses D1.9.1 Therapeutic Utility of EGF-R Kinase Inhibitors D1.9.2 Amino-4 Quinazoline Inhibitors: Iressa and Tarceva D1.9.3 Analysis of Tarceva Binding to the EGF-R Kinase D1.9.4 SAR of the Quinazoline Scaffold D1.9.5 Analysis of a Surprising Observation

D1.10. Methods for Analyzing Binding D1.10.1 Analyzing Ligand-Receptor Binding D1.10.2 Ligand-Binding Predictions D1.10.3 Visual Analyses D1.10.4 Docking Analyses D1.10.5 Calculation of Binding Energies D1.10.6 Free Energy Perturbation Techniques D1.10.7 Energies from Force Field Calculations D1.10.8 Energies from Scoring Functions D1.10.9 Limitations of Scoring Functions D1.10.10 Calculating Desolvation Energies

D1.11. Conclusion D1.11.1 Conclusion

D1.12. CHAPTER QUIZZES (Available only in Teaching Package) D1.12.1 Quiz 1 D1.12.2 Quiz 2 D1.12.3 Quiz 3 D1.12.4 Quiz 4 D1.12.5 Quiz 5 D1.12.6 Quiz 6 D1.12.7 Quiz 7 D1.12.8 Quiz 8 D1.12.9 Quiz 9 D1.12.10 Quiz 10 D1.12.11 Quiz 11 D1.12.12 Quiz 12 D1.12.13 Quiz 13 D1.12.14 Quiz 14 D1.12.15 Quiz 15 D1.12.16 Quiz 16 D1.12.17 Quiz 17 D1.12.18 Quiz 18 D1.12.19 Quiz 19 D1.12.20 Quiz 20 D1.12.21 Quiz 21 D1.12.22 Quiz 22 D1.12.23 Quiz 23 D1.12.24 Quiz 24 D1.12.25 Quiz 25 D1.12.26 Quiz 26 D1.12.27 Quiz 27 D1.12.28 Quiz 28 D1.12.29 Quiz 29 D1.12.30 Quiz 30 D1.12.31 Quiz 31 D1.12.32 Quiz 32 D1.12.33 Quiz 33 D1.12.34 Quiz 34 D1.12.35 Quiz 35 D1.12.36 Quiz 36 D1.12.37 Quiz 37 D1.12.38 Quiz 38 D1.12.39 Quiz 39 D1.12.40 Quiz 40 D1.12.41 Quiz 41 D1.12.42 Quiz 42 D1.12.43 Quiz 43 D1.12.44 Quiz 44 D1.12.45 Quiz 45 D1.12.46 Quiz 46 D1.12.47 Quiz 47 D1.12.48 Quiz 48 D1.12.49 Quiz 49 D1.12.50 Quiz 50

D1.12.51 Quiz 51 D1.12.52 Quiz 52 D1.12.53 Quiz 53 D1.12.54 Quiz 54

D2. STRUCTURE-BASED DRUG DESIGN: DESIGN

D2.1. Introduction D2.1.1 Design of Drug Candidates: An Iterative Process D2.1.2 Steps in Structure-Based Drug Design D2.1.3 Small Changes Can Produce Huge Effects D2.1.4 p38 Wild D2.1.5 p38 Mutant D2.1.6 ERK-2 Wild D2.1.7 ERK-2 Mutant D2.1.8 Increasing Biological Activity D2.1.9 Beginning the Design Phase D2.1.10 A Simple Example of Design D2.1.11 Definition of Docking D2.1.12 Docking Treatments

D2.2. Eight Golden Rules D2.2.1 Eight Golden Rules in Receptor-Based Ligand Design D2.2.2 Rule 1: Coordinate to Key Anchoring Sites D2.2.3 Rule 2: Exploit Hydrophobic Interactions D2.2.4 Rule 3: Exploit Hydrogen Bonding Capabilities D2.2.5 Hydrogen Bonds with Backbone Atoms D2.2.6 Hydrogen Bonds with Residue Atoms D2.2.7 Rule 4: Exploit Electrostatic Interactions D2.2.8 Rule 5: Favor Bioactive Form & Avoid Energy Strain D2.2.9 Rule 6: Optimize VDW Contacts and Avoid Bumps D2.2.10 Rule 7: Structural Water Molecules and Solvation D2.2.11 Rule 8: Consider Entropic Effect D2.2.12 Gaining Binding by Reduction of Entropy

D2.3. The Four Design Methods D2.3.1 The Four Design Methods

D2.4. Analog Design D2.4.1 Principles of Analog Design D2.4.2 Example of Analog Design

D2.5. Database Searching D2.5.1 3D Database Searching D2.5.2 Advantages of Database Searching D2.5.3 Problems of Conformational Complexity D2.5.4 Example of Database Searching D2.5.5 Limitations in Data Base Approaches D2.5.6 Databases of Molecules in 3D D2.5.7 The Main Purpose of a 3D-Database Search

D2.6. De-Novo Design D2.6.1 Automated Construction Approaches D2.6.2 Molecule Generated by an Automated Method

D2.7. Manual Design D2.7.1 Manual Design D2.7.2 Importance of Visualization D2.7.3 Tools in Manual Design D2.7.4 Fully Exploiting the Fruits of the Analyses

D2.8. Another Iteration D2.8.1 Another Round of Analysis & Design

D2.9. A Success Story D2.9.1 Example Of Successful Structure-Based Design D2.9.2 Mechanism of Action of the HIV-1 Protease D2.9.3 The Crystallographic Structure of the HIV-1 Protease D2.9.4 Transition State Concept for the Design of Inhibitors D2.9.5 Topography of the Active Site of the Enzyme D2.9.6 The MVT-101 Inhibitor D2.9.7 Crystallographic Resolution of the HIV-1 Protease D2.9.8 X-ray of the Complex of MVT-101 with the Enzyme D2.9.9 Design of Peptide-Like Structures D2.9.10 X-ray Structure of the A-77003 Complex D2.9.11 A Drug Design Solution Using Database Searching D2.9.12 The Terphenyl Hit D2.9.13 In Depth Analysis of the Hit D2.9.14 The Design of Cyclic Ureas D2.9.15 The Crystallographic Structure of XK-263 Complex D2.9.16 Lessons From HIV-1 Protease Inhibition

D2.10. Conclusion D2.10.1 Conclusion

D2.11. CHAPTER QUIZZES (Available only in Teaching Package) D2.11.1 Quiz 1 D2.11.2 Quiz 2 D2.11.3 Quiz 3 D2.11.4 Quiz 4 D2.11.5 Quiz 5 D2.11.6 Quiz 6 D2.11.7 Quiz 7 D2.11.8 Quiz 8 D2.11.9 Quiz 9 D2.11.10 Quiz 10 D2.11.11 Quiz 11 D2.11.12 Quiz 12 D2.11.13 Quiz 13 D2.11.14 Quiz 14 D2.11.15 Quiz 15 D2.11.16 Quiz 16 D2.11.17 Quiz 17 D2.11.18 Quiz 18 D2.11.19 Quiz 19 D2.11.20 Quiz 20 D2.11.21 Quiz 21 D2.11.22 Quiz 22

D2.11.23 Quiz 23 D2.11.24 Quiz 24 D2.11.25 Quiz 25 D2.11.26 Quiz 26 D2.11.27 Quiz 27 D2.11.28 Quiz 28 D2.11.29 Quiz 29 D2.11.30 Quiz 30 D2.11.31 Quiz 31 D2.11.32 Quiz 32 D2.11.33 Quiz 33 D2.11.34 Quiz 34 D2.11.35 Quiz 35 D2.11.36 Quiz 36 D2.11.37 Quiz 37 D2.11.38 Quiz 38 D2.11.39 Quiz 39 D2.11.40 Quiz 40 D2.11.41 Quiz 41 D2.11.42 Quiz 42 D2.11.43 Quiz 43 D2.11.44 Quiz 44 D2.11.45 Quiz 45 D2.11.46 Quiz 46 D2.11.47 Quiz 47 D2.11.48 Quiz 48 D2.11.49 Quiz 49 D2.11.50 Quiz 50 D2.11.51 Quiz 51 D2.11.52 Quiz 52 D2.11.53 Quiz 53 D2.11.54 Quiz 54

D3. STRUCTURE-BASED DRUG DESIGN: EXAMPLES

D3.1. Inhibitors of PNP D3.1.1 The Purine Nucleoside Phosphorylase Protease D3.1.2 Therapeutic Utility of PNP Inhibitors D3.1.3 The Complex of Guanine with PNP D3.1.4 Analysis of the Active Site of PNP D3.1.5 Strategy for the Design of PNP Inhibitors D3.1.6 Design of 9-Deazaguanine Derivatives D3.1.7 Binding of 9-Deaza-Guanine Candidate D3.1.8 Browser of PNP Inhibitors

D3.2. Intercalating Antibiotics D3.2.1 Therapeutic Utility of Intercalating Agents D3.2.2 Daunorubicin a Potent Anthracycline Antibiotic D3.2.3 Complex of Daunorubicin with a Hexanucleotide D3.2.4 Analysis of the Binding of Daunorubicin D3.2.5 Design of Novel Intercalating Agents

D3.3. Thymidylate Synthase Inhibitors D3.3.1 The Thymidylate Synthase Enzyme D3.3.2 Two Possible Strategies for Inhibiting TS D3.3.3 Inhibition by Binding to the Substrate Site D3.3.4 Inhibition by Binding to Cofactor Site D3.3.5 Complex of CB3717 with Thymidylate Synthase D3.3.6 Analysis of the Binding of CB3717 D3.3.7 Design of a New TS Inhibitor

D3.4. Inhibitors of Phospholipase A-2 D3.4.1 Phospholipase A2 D3.4.2 PLA2 Transition State Analogues D3.4.3 Complex of an Inhibitor with PLA2 D3.4.4 Analysis of the Binding of the Inhibitor D3.4.5 Design of a New Class of PLA2 Inhibitors D3.4.6 Binding of Acenaphtene with PLA2

D3.5. Thrombin Inhibitors D3.5.1 Therapeutic Utility of Thrombin Inhibitors D3.5.2 Examples of Thrombin Inhibitors D3.5.3 The Catalytic Mechanism of Thrombin D3.5.4 The Complex of Thrombin with NAPAP D3.5.5 Analysis of the NAPAP-Thrombin Complex D3.5.6 The Design of a New Thrombin Inhibitor

D3.6. Elastase Inhibitors D3.6.1 Therapeutic Utility of Elastase Inhibitors D3.6.2 Analysis of the HLE Active Site D3.6.3 Complex of MSACK with HLE D3.6.4 Analysis of the Binding of MSACK D3.6.5 The Design of a New Elastase Inhibitor D3.6.6 Complex of Inhibitor with PPE Elastase D3.6.7 Binding of Aminopyrimidone Candidate

D3.7. Human Rhinovirus Inhibitors D3.7.1 Inhibition of Human Rhinovirus Protein D3.7.2 The Mechanism of Action of WIN54954 D3.7.3 Complex of WIN54954 with Rhinovirus HRV14 D3.7.4 Binding of WIN54954 with Rhinovirus HRV14 D3.7.5 Optimization of WIN54954

D3.8. Rotamase Inhibitors D3.8.1 Utility of Rotamase Inhibitors D3.8.2 Complex of FK506 with FKBP D3.8.3 Analysis of the Binding of FK506 D3.8.4 Design of a New Rotamase Inhibitor D3.8.5 The Pipecolyl Inhibitor Mimics FK506 D3.8.6 Binding of the Pipecolyl Inhibitor

D3.9. Renin Inhibitors D3.9.1 Therapeutic Utility of Renin Inhibitors D3.9.2 The Design of Renin Inhibitors D3.9.3 Complex of Statine with Rhizopuspepsin D3.9.4 Analysis of the Binding of Statine

D3.9.5 Design of a Macrocyclic Renin Inhibitor D3.9.6 Inaccuracies in Homology Models

D3.10. Dihydrofolate Reductase Inhibitors D3.10.1 Utility of Dihydrofolate Reductase Inhibitors D3.10.2 Complex of Methotrexate with DHFR D3.10.3 Binding Mode of Methotrexate with DHFR D3.10.4 Trimethoprim: a DHFR Inhibitor D3.10.5 The Design of a Novel DHFR-Inhibitor D3.10.6 Complex of Brodimoprim with DHFR D3.10.7 Binding of Brodimoprim with DHFR

D3.11. Sialidase Inhibitors D3.11.1 The Sialidase Enzyme D3.11.2 Therapeutic Utility of Sialidase Inhibitors D3.11.3 Complex of Sialic Acid with Sialidase D3.11.4 Analysis of Sialic Acid Binding D3.11.5 The Design of a Potent Sialidase Inhibitor

D3.12. Inhibitors of Carbonic Anhydrase D3.12.1 The Carbonic Anhydrase Protein D3.12.2 Therapeutic Utility of CA Inhibitors D3.12.3 MK-417 is a Potent Inhibitor of CA D3.12.4 Binding of MK-417 with CA Protein D3.12.5 S Enantiomer is more Potent than the R D3.12.6 Optimization of MK-417 D3.12.7 Dorzolamide, a Potent Inhibitor of CA D3.12.8 Complex of CA with Dorzolamide D3.12.9 Binding of Dorzolamide with CA Protein

D3.13. Factor Xa Inhibitors D3.13.1 Therapeutic Utility of Factor Xa Inhibitors D3.13.2 DX-9065a : a Factor Xa Inhibitor D3.13.3 Complex Between Factor Xa and DX-9065a D3.13.4 Analysis of the Factor Xa and DX-9065a Complex D3.13.5 Role of the Carboxylic Acid in Selectivity D3.13.6 Initial Inhibitor Design D3.13.7 Design (step 1): Structural Moiety for Pocket S1 D3.13.8 Design (step 2): Structural Moiety for Pocket S4 D3.13.9 Design (step 3): Design of the Spacer D3.13.10 Design (step 4): Positioning of the Carboxylate D3.13.11 Discovery of a Lead Compound D3.13.12 Optimization of the Designed Series

D3.14. CHAPTER QUIZZES (Available only in Teaching Package) D3.14.1 Quiz 1 D3.14.2 Quiz 2 D3.14.3 Quiz 3 D3.14.4 Quiz 4 D3.14.5 Quiz 5 D3.14.6 Quiz 6 D3.14.7 Quiz 7 D3.14.8 Quiz 8 D3.14.9 Quiz 9

D3.14.10 Quiz 10 D3.14.11 Quiz 11 D3.14.12 Quiz 12 D3.14.13 Quiz 13 D3.14.14 Quiz 14 D3.14.15 Quiz 15 D3.14.16 Quiz 16 D3.14.17 Quiz 17 D3.14.18 Quiz 18 D3.14.19 Quiz 19 D3.14.20 Quiz 20 D3.14.21 Quiz 21 D3.14.22 Quiz 22 D3.14.23 Quiz 23 D3.14.24 Quiz 24 D3.14.25 Quiz 25 D3.14.26 Quiz 26 D3.14.27 Quiz 27

E. PHARMACOPHORE-BASED DRUG DESIGN

E1. PHARMACOPHORE-BASED DRUG DESIGN: ANALYSIS

E1.1. Introduction E1.1.1 Pharmacophore-Based Drug Design E1.1.2 Operational Strategy: Molecular Mimicry E1.1.3 Analogy with Keys E1.1.4 Active Molecules are Complicated Keys E1.1.5 Definition of a Pharmacophore

E1.2. Analytical Process E1.2.1 The Analytical Process E1.2.2 Data Collection Stage E1.2.3 Analysis Stage E1.2.4 Design Phase

E1.3. Simple Case E1.3.1 Introduction with a Simple Case E1.3.2 Molecular Similarity E1.3.3 Superimpositions E1.3.4 Goal of Superimposition Procedures E1.3.5 Summary of the Example E1.3.6 Superimposition Technique E1.3.7 Dummy Atoms

E1.4. Typical Example E1.4.1 A More Typical Example E1.4.2 Identification of the Bioactive Conformation E1.4.3 Conformational Example E1.4.4 Bioactive Conformation: Geometry E1.4.5 Bioactive Conformation: Energy E1.4.6 Reduction of the Complexity

E1.4.7 Bioactive Conformations Must be Superimposable E1.4.8 Systematic Superimposition of Conformers E1.4.9 Results with High Informational Content E1.4.10 Summary

E1.5. Complexity Levels E1.5.1 Rigid and Flexible Molecules E1.5.2 Bioactive Conformation of GABA E1.5.3 Superimposition in the Space of Properties E1.5.4 Superimposition in the Space of Properties : Example

E1.6. Principles of Analysis E1.6.1 Complexity of Analyses E1.6.2 Six Rules for Analyses E1.6.3 Common Structural Features: Rule 1 E1.6.4 Multiple Hypotheses: Rule 2 E1.6.5 Inactive Molecules: Rule 3 E1.6.6 Closely Related Molecules: Rule 4 E1.6.7 Molecules With No Common Features: Rule 5 E1.6.8 Mapping the Receptor: Rule 6

E1.7. Conformational Control E1.7.1 Control of the Molecular Geometries E1.7.2 3D Considerations E1.7.3 Example E1.7.4 2D Considerations E1.7.5 Example E1.7.6 Misuse of Structural Information

E1.8. Managing Hypotheses E1.8.1 Initial Requirements E1.8.2 Same Mechanism of Action? E1.8.3 Chlorpromazine Example E1.8.4 Tracking & Reconsidering Hypotheses E1.8.5 Incorrect Hypotheses E1.8.6 Example 1 E1.8.7 Example 2 E1.8.8 Multiple Pharmacophore Hypotheses E1.8.9 Multiple Pharmacophore Hypotheses: Example E1.8.10 Poor Initial Data: Too Many Hypotheses E1.8.11 Validating Hypotheses by Chemical Syntheses E1.8.12 Browser of Dopamine D2 Agents

E1.9. Molecular Similarities Limitations E1.9.1 Limitations of Molecular Similarities E1.9.2 Phenyl-Imidazole Example E1.9.3 Phenyl-Imidazole Browser

E1.10. Receptor Mapping E1.10.1 The Role of Inactive Molecules E1.10.2 Inactive Analog of Nifedipine E1.10.3 Rearrangement of the Bioactive Conformation E1.10.4 Judging with Discernment E1.10.5 The Active Analog Principle

E1.10.6 Active Analog Approach Browser E1.10.7 Example of Receptor Mapping

E1.11. Two Generations of Pharmacophores E1.11.1 The Two Generations of Pharmacophores E1.11.2 The First Generation of Pharmacophores E1.11.3 The Second Generation of Pharmacophores E1.11.4 Future

E1.12. Example of Analysis E1.12.1 Antibiotic Activities in the Cephalosporin Series E1.12.2 Stereochemical Hypothesis E1.12.3 Attempts Towards a Geometrical Interpretation E1.12.4 The Lactam Nitrogen Pyramidality Hypothesis E1.12.5 Deficiency of the Nitrogen Pyramidality Hypothesis E1.12.6 Bioactive Conformation of Penicillins? E1.12.7 Revealing Bioactive Conformation of Penicillins E1.12.8 Separation Between Active and Inactive Molecules E1.12.9 Other Beta-Lactam Antibiotic Structures E1.12.10 Browser of Beta-Lactam Antibiotics E1.12.11 Validation and Perspectives

E1.13. Summary E1.13.1 Pharmacophore-Based Drug Design Summary

E1.14. CHAPTER QUIZZES (Available only in Teaching Package) E1.14.1 Quiz 1 E1.14.2 Quiz 2 E1.14.3 Quiz 3 E1.14.4 Quiz 4 E1.14.5 Quiz 5 E1.14.6 Quiz 6 E1.14.7 Quiz 7 E1.14.8 Quiz 8 E1.14.9 Quiz 9 E1.14.10 Quiz 10 E1.14.11 Quiz 11 E1.14.12 Quiz 12 E1.14.13 Quiz 13 E1.14.14 Quiz 14 E1.14.15 Quiz 15 E1.14.16 Quiz 16 E1.14.17 Quiz 17 E1.14.18 Quiz 18 E1.14.19 Quiz 19 E1.14.20 Quiz 20 E1.14.21 Quiz 21 E1.14.22 Quiz 22 E1.14.23 Quiz 23 E1.14.24 Quiz 24 E1.14.25 Quiz 25 E1.14.26 Quiz 26 E1.14.27 Quiz 27

E1.14.28 Quiz 28 E1.14.29 Quiz 29 E1.14.30 Quiz 30 E1.14.31 Quiz 31 E1.14.32 Quiz 32 E1.14.33 Quiz 33 E1.14.34 Quiz 34 E1.14.35 Quiz 35 E1.14.36 Quiz 36 E1.14.37 Quiz 37 E1.14.38 Quiz 38 E1.14.39 Quiz 39 E1.14.40 Quiz 40 E1.14.41 Quiz 41 E1.14.42 Quiz 42 E1.14.43 Quiz 43 E1.14.44 Quiz 44 E1.14.45 Quiz 45 E1.14.46 Quiz 46 E1.14.47 Quiz 47 E1.14.48 Quiz 48 E1.14.49 Quiz 49 E1.14.50 Quiz 50 E1.14.51 Quiz 51 E1.14.52 Quiz 52 E1.14.53 Quiz 53 E1.14.54 Quiz 54 E1.14.55 Quiz 55 E1.14.56 Quiz 56 E1.14.57 Quiz 57 E1.14.58 Quiz 58 E1.14.59 Quiz 59

E2. PHARMACOPHORE-BASED DRUG DESIGN: DESIGN

E2.1. Introduction E2.1.1 Beginning the Design Phase E2.1.2 Creativity of the Design E2.1.3 Good Control of the Conformational Features E2.1.4 Butaclamol Example (Bad Design & Bad Results) E2.1.5 Staurosporine Example (Bad Design & Good Results) E2.1.6 Obvious Design E2.1.7 Design of Cholecystokinin Receptor Ligands E2.1.8 Pharmacophore Analysis: CCK-A Antagonists E2.1.9 Design of a New Lorglumide Analog

E2.2. The Four Design Methods E2.2.1 The Four Design Methods

E2.3. Chemical Modifications E2.3.1 Principles of Analog Design E2.3.2 Bioisosteric Replacements: Principle

E2.3.3 Bioisosteric Replacements: Diazepam E2.3.4 Bioisosteric Replacements : Beta-Blockers E2.3.5 Rigid Analogs: Principle E2.3.6 Rigid Analogs : Dopaminergics E2.3.7 Alteration of Ring Size: Principle E2.3.8 Alteration of Ring Size: Imipramine E2.3.9 Ring Suppression: Principle E2.3.10 Ring Suppression: Doxepin E2.3.11 Homologation of Alkyl Chains: Principle E2.3.12 Homologation of Alkyl Chains: Apomorphine E2.3.13 Alteration of Stereochemistry: Principle E2.3.14 Alteration of Stereochemistry: Progesterone E2.3.15 Homologation by Simplification: Bromocryptine E2.3.16 Altering Interatomic Distances E2.3.17 Aromatic Ring Position Isomers: Principle E2.3.18 Aromatic Ring Position Isomers : b Adrenergic Drugs E2.3.19 Chemical Modifications for SAR Information

E2.4. Database Searching E2.4.1 3D Database Searching E2.4.2 Problems of Conformational Complexity E2.4.3 Example of 3D Searching: Pharmacophore Query E2.4.4 Hit Obtained by 3D Database Searching E2.4.5 Example of 3D Database Searching: Shape Query E2.4.6 Molecules Obtained by Shape Searching E2.4.7 Databases of Molecules in 3D E2.4.8 Databases of Commercial Molecules

E2.5. De-Novo Design E2.5.1 Automated Construction Approaches E2.5.2 Algorithm Based Approaches E2.5.3 Example of Construction Approach E2.5.4 Query Pharmacophore: 5-Alfa Reductase Example E2.5.5 A Generated Solution E2.5.6 Automated Construction Approach: Example

E2.6. Manual Design E2.6.1 Introduction to Manual Design E2.6.2 Importance of the Visualization E2.6.3 Tools in Manual Design E2.6.4 Fully Exploiting the Fruits of the Analyses E2.6.5 Creativity E2.6.6 Design of a Spacer: a Step-by-Step Process E2.6.7 Manual Mimicking

E2.7. Examples of Design E2.7.1 EGFR Protein Tyrosine Kinase Inhibitors E2.7.2 Comparing the Structures of Staurosporine and ATP E2.7.3 CGP52411 a Simplified Staurosporine Molecule E2.7.4 Bidentate Anchorage of CGP52411 E2.7.5 The Design of a New EGF-R PTK Inhibitor E2.7.6 Browser of EGF-R Protein Kinase Inhibitors

E2.8. Conclusion

E2.8.1 Conclusion

E2.9. CHAPTER QUIZZES (Available only in Teaching Package) E2.9.1 Quiz 1 E2.9.2 Quiz 2 E2.9.3 Quiz 3 E2.9.4 Quiz 4 E2.9.5 Quiz 5 E2.9.6 Quiz 6 E2.9.7 Quiz 7 E2.9.8 Quiz 8 E2.9.9 Quiz 9 E2.9.10 Quiz 10 E2.9.11 Quiz 11 E2.9.12 Quiz 12 E2.9.13 Quiz 13 E2.9.14 Quiz 14 E2.9.15 Quiz 15 E2.9.16 Quiz 16 E2.9.17 Quiz 17 E2.9.18 Quiz 18 E2.9.19 Quiz 19 E2.9.20 Quiz 20 E2.9.21 Quiz 21 E2.9.22 Quiz 22 E2.9.23 Quiz 23 E2.9.24 Quiz 24 E2.9.25 Quiz 25 E2.9.26 Quiz 26 E2.9.27 Quiz 27 E2.9.28 Quiz 28 E2.9.29 Quiz 29 E2.9.30 Quiz 30 E2.9.31 Quiz 31 E2.9.32 Quiz 32 E2.9.33 Quiz 33 E2.9.34 Quiz 34 E2.9.35 Quiz 35

E3. PHARMACOPHORE-BASED DRUG DESIGN: EXAMPLES

E3.1. Substance P Antagonists E3.1.1 Therapeutic Utility of Substance P Antagonists E3.1.2 Reference Set of Substance P Antagonists E3.1.3 Pharmacophore for Substance P Antagonists E3.1.4 Origin of the Poor Activity of SP4 E3.1.5 Constrained Boat Conformation of CP96345 E3.1.6 The Design of a Potent Substance P Antagonist E3.1.7 The Superimposition of CP96345 and CP99994 E3.1.8 Browser of Substance P Antagonists

E3.2. Dopamine D-1 Agonists

E3.2.1 Therapeutic Utility of Dopamine D1 Agonists E3.2.2 Pharmacophore for Dopamine D1 Agonists E3.2.3 Browser of Dopamine Receptor D1 Agonists

E3.3. Non-Tricyclic Antidepressants E3.3.1 Mode of Action of Tricyclic Antidepressants E3.3.2 Reference Set of Antidepressant Molecules E3.3.3 Invalidation of the "Butterfly" Model E3.3.4 Pharmacophore for Antidepressants E3.3.5 Browser for Antidepressant Agents E3.3.6 The Design of RU-22249 E3.3.7 Browser for Antidepressant Agents

E3.4. Hypolipemic Agents E3.4.1 Reference Set of Hypolipemic Agents E3.4.2 Design of a New Hypolipemic Agent E3.4.3 RU 25961 is a 3D Mimic of Treloxinate E3.4.4 Browser of Hypolipemic Agents E3.4.5 Methyl Treloxinate E3.4.6 Browser of Hypolipemic Agents

E3.5. ACE Inhibitors E3.5.1 Therapeutic Utility of ACE Inhibitors E3.5.2 The ACE Enzyme E3.5.3 Discovery of the First ACE Inhibitor E3.5.4 Design of New ACE Inhibitors E3.5.5 Pharmacophore for ACE Inhibition E3.5.6 Browser for ACE Inhibition

E3.6. Anti-Histaminic H-2 Antagonists E3.6.1 Therapeutic Utility of H-2 Receptor Antagonists E3.6.2 Design of an Antiulcer Lead Compound E3.6.3 Pharmacophore for H-2 Antagonists E3.6.4 Browser of H-2 Receptor Antagonists

E3.7. Aromatase Inhibitors E3.7.1 Therapeutic Utility of Aromatase Inhibitors E3.7.2 Reference Set of Aromatase Inhibitors E3.7.3 Pharmacophore for Aromatase Inhibitors E3.7.4 The Design of a New Inhibitor of Aromatase E3.7.5 Browser of Aromatase Inhibitors

E3.8. Dopamine D-2 Antagonists E3.8.1 Utility of Dopamine D2 Receptor Antagonists E3.8.2 Some Antipsychotic Agents E3.8.3 Reference Set of D2 Receptor Antagonists E3.8.4 Pharmacophore for Dopamine D2 Antagonists E3.8.5 The Design of RO-221319 E3.8.6 Browser of D2 Receptor Antagonists

E3.9. Serotonin Antagonists E3.9.1 Therapeutic Utility of Serotonin Antagonists E3.9.2 Superimposition of Serotonin Receptor Antagonists E3.9.3 Pharmacophore for Serotonin Antagonists E3.9.4 The Design of MDL 72832

E3.9.5 Browser of Serotonin Receptor Antagonists

E3.10. Aldose Reductase Inhibitors E3.10.1 Therapeutic Utility of Aldose Reductase Inhibitors E3.10.2 Pharmacophore for Aldose Reductase Inhibitors E3.10.3 Browser of Aldose Reductase Inhibitors E3.10.4 The Design of AY31358 E3.10.5 Browser of Aldose Reductase Inhibitors

E3.11. GABA-Uptake Inhibitors E3.11.1 Therapeutic Utility of GABA-Uptake Inhibitors E3.11.2 Reference Set of GABA-Uptake Inhibitors E3.11.3 Pharmacophore of GABA-Uptake Inhibitors E3.11.4 Browser of GABA-Uptake Inhibitors E3.11.5 Design of a New GABA-Uptake Inhibitor E3.11.6 Browser of GABA-Uptake Inhibitors

E3.12. Beta-Lactam Antibiotics E3.12.1 Biological Action of Beta-Lactam Antibiotics E3.12.2 Does Penicillin Mimic an Endogenous Peptide? E3.12.3 Attempts to Increase Antibacterial Activities E3.12.4 A Good Hypothesis with a Bad Design! E3.12.5 An Example of a Good Hypothesis Well Exploited E3.12.6 Browser of Beta-Lactam Antibiotics

E3.13. Polymerase-1 Inhibitors E3.13.1 Therapeutic utility of PARP-1 Inhibitors E3.13.2 3-Amino Benzamide PARP-1 Inhibitor E3.13.3 Design with Carboxamide Geometry Locked E3.13.4 Synthesis of the Designed Tricyclic Compounds E3.13.5 Validation of the Concept by X-Ray Crystallography E3.13.6 Browser

E3.14. CHAPTER QUIZZES (Available only in Teaching Package) E3.14.1 Quiz 1 E3.14.2 Quiz 2 E3.14.3 Quiz 3 E3.14.4 Quiz 4 E3.14.5 Quiz 5 E3.14.6 Quiz 6 E3.14.7 Quiz 7 E3.14.8 Quiz 8 E3.14.9 Quiz 9 E3.14.10 Quiz 10 E3.14.11 Quiz 11 E3.14.12 Quiz 12 E3.14.13 Quiz 13 E3.14.14 Quiz 14 E3.14.15 Quiz 15 E3.14.16 Quiz 16 E3.14.17 Quiz 17 E3.14.18 Quiz 18 E3.14.19 Quiz 19 E3.14.20 Quiz 20

E3.14.21 Quiz 21 E3.14.22 Quiz 22 E3.14.23 Quiz 23 E3.14.24 Quiz 24 E3.14.25 Quiz 25 E3.14.26 Quiz 26 E3.14.27 Quiz 27

F. QSAR AND CHEMOMETRICS

F1. QSAR PRINCIPLES AND METHODS

F1.1. Introduction to QSAR F1.1.1 Molecular Structure and Molecular Properties F1.1.2 Structure-Property Relationships: Example 1 F1.1.3 Structure-Property Relationships: Example 2 F1.1.4 Structure-Property Relationships: Example 3 F1.1.5 What is QSAR? F1.1.6 What is QSPR? F1.1.7 Focus on a Single Property at a Time F1.1.8 Molecular Descriptors F1.1.9 Examples of Molecular Descriptors F1.1.10 The QSAR Equations F1.1.11 Types of Molecular Descriptors F1.1.12 Molecular Descriptors: 1D F1.1.13 Molecular Descriptors: 2D F1.1.14 Molecular Descriptors: 3D F1.1.15 A Multitude of Molecular Descriptors F1.1.16 Biologically Relevant Descriptors F1.1.17 Application of QSAR F1.1.18 Understanding Structure-Activity Relationships F1.1.19 Designing Compounds with Improved Activities F1.1.20 Reducing a Virtual Library to a Practical Size

F1.2. The Foundations of QSAR F1.2.1 Birth of QSAR F1.2.2 The Foundations of QSAR F1.2.3 The Hammett Contribution F1.2.4 Dissociation Constants of Substituted Benzoic Acids F1.2.5 Dissociation of Substituted Phenylacetic Acids F1.2.6 Linear Free Energy Relationship F1.2.7 The Hammett Equation F1.2.8 The Meaning of ρ F1.2.9 The Meaning of σ F1.2.10 Examples of σ Constants F1.2.11 Predicting the pKa of Benzoic Acid Compounds F1.2.12 Hansch Contribution F1.2.13 The Importance of Lipophilicity F1.2.14 LogP is a Measure of Compounds Lipophilicity F1.2.15 Correlation of LogP with Biological Activities F1.2.16 Example of Correlation with LogP

F1.2.17 Improvements of the Initial Model F1.2.18 The π Descriptor F1.2.19 The MR Descriptor F1.2.20 The Taft Descriptor (ES) F1.2.21 Meaning of Parabolic Dependence on LogP F1.2.22 The Free-Wilson Analysis F1.2.23 Indicator Variables and Substituent Weights F1.2.24 Free-Wilson Structural Matrix F1.2.25 Example of Structural Matrix F1.2.26 Example of Free-Wilson Equation F1.2.27 Predictability of the Model F1.2.28 Understanding the Molecular Determinants

F1.3. Design of a QSAR Model F1.3.1 Embarking on the Design of a QSAR Model F1.3.2 The Four Steps F1.3.3 An Iterative Process

F1.4. Compounds Selection: Step 1 F1.4.1 Compounds Selection F1.4.2 Predictions by Interpolation F1.4.3 Example of Extrapolative Model F1.4.4 Identification of Outliers F1.4.5 Biological Activities in Terms of Log 1/C

F1.5. Descriptors Selection: Step 2 F1.5.1 Descriptors Selection F1.5.2 Methods for Selecting Relevant Descriptors F1.5.3 Manual Selection of Descriptors F1.5.4 Automated Selection of Descriptors F1.5.5 Systematic Combination of Descriptors F1.5.6 Methods for Selecting a Subset of Descriptor F1.5.7 Forward Selection F1.5.8 Backward Elimination F1.5.9 Stepwise Regression F1.5.10 Scaling Descriptors F1.5.11 Correlation Between Descriptors F1.5.12 Example of Correlated Descriptors F1.5.13 Solution to the Problem of Correlated Descriptors F1.5.14 The Holy Grail in QSAR

F1.6. Deriving the Equation: Step 3 F1.6.1 Deriving The QSAR Equation F1.6.2 The Starting Point: The Study Table F1.6.3 Graphical Analysis of the Data F1.6.4 Choice of the Mathematical Equation F1.6.5 Complexity Levels and Data Overfitting F1.6.6 Mathematics are Very (too) Powerful F1.6.7 Illustration with an Example F1.6.8 A Simple Model F1.6.9 A Complex Model F1.6.10 Comparing the Two Models F1.6.11 Predictive Power of the Simple Model

F1.6.12 Predictive Power of the Complex Model F1.6.13 Complexity Dictated by Predictability of the Model F1.6.14 Single Linear Equation: Mathematical Outline F1.6.15 Calculating b0 and b1 F1.6.16 Multiple Linear Regression: Mathematical Outline F1.6.17 Example: MLR vs. Single Linear Models F1.6.18 The Mathematics of MLR: a Single Sample F1.6.19 The Mathematics of MLR: Many Molecules F1.6.20 The Solution of MLR F1.6.21 Analysis of the MLR Equation F1.6.22 Non-Linear Equations F1.6.23 Example of Non-Linear Model F1.6.24 Typical Non-Linear Equations

F1.7. Validating the Model: Step 4 F1.7.1 Tools for Assessing the Quality of a Model F1.7.2 Predictive and non-Predictive Models F1.7.3 The Standard Deviation F1.7.4 Correlation Index r² F1.7.5 The Mathematics of r² F1.7.6 TSS, the Total Variance F1.7.7 RSS, the Explained Variance F1.7.8 t-test for Single Descriptors and Significance of r² F1.7.9 Shape of t-distribution and Number of Molecules F1.7.10 Student's t-test Procedure F1.7.11 F-test for Assessing the Significance of r² F1.7.12 Performing the F-test F1.7.13 F-test Procedure F1.7.14 Assessing the Predictive Power of a Model F1.7.15 The Test Set Method F1.7.16 The Cross Validation Method F1.7.17 Limits of the Cross Validation Method F1.7.18 The Predictive Index Q² F1.7.19 Summary

F1.8. Example of Simple Linear Regression F1.8.1 Example of Capsaicin Analogs F1.8.2 Relevant Descriptors of Capsaicin Analogs F1.8.3 The Capsaicin Study Table F1.8.4 Graphical Analysis of Capsaicin Analogs F1.8.5 Deriving a QSAR Linear Equation F1.8.6 Experimental vs. Calculated Values F1.8.7 Calculating r² for the Capsaicin analogs F1.8.8 t-test for the Capsaicin Analogs F1.8.9 F-test for a Series of the Capsaicin Analogs F1.8.10 The QSAR Equation for the Capsaicin Analogs F1.8.11 Predicting the Activities of Unknown Compounds

F1.9. CHAPTER QUIZZES (Available only in Teaching Package) F1.9.1 Quiz 1 F1.9.2 Quiz 2 F1.9.3 Quiz 3 F1.9.4 Quiz 4

F1.9.5 Quiz 5 F1.9.6 Quiz 6 F1.9.7 Quiz 7 F1.9.8 Quiz 8 F1.9.9 Quiz 9 F1.9.10 Quiz 10 F1.9.11 Quiz 11 F1.9.12 Quiz 12 F1.9.13 Quiz 13 F1.9.14 Quiz 14 F1.9.15 Quiz 15 F1.9.16 Quiz 16 F1.9.17 Quiz 17 F1.9.18 Quiz 18 F1.9.19 Quiz 19 F1.9.20 Quiz 20 F1.9.21 Quiz 21 F1.9.22 Quiz 22 F1.9.23 Quiz 23 F1.9.24 Quiz 24 F1.9.25 Quiz 25 F1.9.26 Quiz 26 F1.9.27 Quiz 27 F1.9.28 Quiz 28 F1.9.29 Quiz 29 F1.9.30 Quiz 30 F1.9.31 Quiz 31 F1.9.32 Quiz 32 F1.9.33 Quiz 33 F1.9.34 Quiz 34 F1.9.35 Quiz 35 F1.9.36 Quiz 36 F1.9.37 Quiz 37 F1.9.38 Quiz 38 F1.9.39 Quiz 39 F1.9.40 Quiz 40 F1.9.41 Quiz 41 F1.9.42 Quiz 1 F1.9.43 Quiz 43 F1.9.44 Quiz 44 F1.9.45 Quiz 45 F1.9.46 Quiz 46 F1.9.47 Quiz 47 F1.9.48 Quiz 48 F1.9.49 Quiz 49 F1.9.50 Quiz 50 F1.9.51 Quiz 51 F1.9.52 Quiz 52 F1.9.53 Quiz 53 F1.9.54 Quiz 54 F1.9.55 Quiz 55

F1.9.56 Quiz 56 F1.9.57 Quiz 57 F1.9.58 Quiz 58 F1.9.59 Quiz 59 F1.9.60 Quiz 60 F1.9.61 Quiz 61 F1.9.62 Quiz 62 F1.9.63 Quiz 63 F1.9.64 Quiz 64 F1.9.65 Quiz 65 F1.9.66 Quiz 66 F1.9.67 Quiz 67

F2. 3D-QSAR

F2.1. Introduction F2.1.1 Molecular Binding Occurs in 3D F2.1.2 How Does the Receptor Perceives the Ligand? F2.1.3 What is 3D-QSAR? F2.1.4 Principle of 3D-QSAR Approach F2.1.5 Intermolecular Forces F2.1.6 Electrostatic Field F2.1.7 Steric Field F2.1.8 Difference between 2D-QSAR and 3D-QSAR

F2.2. Molecular Interaction Fields (MIF) F2.2.1 Interaction Field Surrounding a Molecule F2.2.2 Perception of Interaction Fields F2.2.3 The Probe Concept F2.2.4 Probing Steric Field with Single Atom Probe F2.2.5 Probing Electrostatic Field with Single Atom Probe F2.2.6 Multi-Atom Probes F2.2.7 3D Lattice and Grid Points to Capture the MIFs F2.2.8 Calculating the Electrostatic Field F2.2.9 Calculating the Steric Field F2.2.10 Visualization of MIFs with Iso-Potential Surfaces F2.2.11 Other Molecular Interaction Fields

F2.3. The GRID Approach F2.3.1 The GRID Approach F2.3.2 GRID: a Structure-Based Approach F2.3.3 Probing the Nature of the Active Site F2.3.4 The GRID Probes F2.3.5 Integration of GRID with Other Programs F2.3.6 Typical Use of GRID F2.3.7 Outline of a GRID Calculation F2.3.8 3D Coordinates of the Protein F2.3.9 Binding Site to be Explored F2.3.10 Selection of Probes F2.3.11 Run of GRID F2.3.12 Output of GRID F2.3.13 Total Number of Calculations

F2.3.14 De Novo Design of New Scaffolds

F2.4. CoMFA: First 3D-QSAR Method F2.4.1 From GRID to 3D-QSAR F2.4.2 Comparative Molecular Field Analyses (CoMFA) F2.4.3 Development of a Correlation Function F2.4.4 Rapid Outline of a CoMFA Calculation F2.4.5 Reference Compounds and Initial Assumptions F2.4.6 Superimpose the Structures F2.4.7 Calculate the MIF at Grid Each Points F2.4.8 Derive a Correlation Function F2.4.9 Molecular Alignment Issues F2.4.10 Template or Atom Alignments F2.4.11 Pharmacophore Alignments F2.4.12 Shape Alignments F2.4.13 Field Fitting F2.4.14 Electrostatic Field Alignment F2.4.15 Moment Alignments F2.4.16 Receptor Based Alignments F2.4.17 Alignment from X-ray Data F2.4.18 The Bioactive Conformation Issue F2.4.19 Deriving the 3D-QSAR Correlation Function F2.4.20 Problem of Number of CoMFA Descriptors F2.4.21 PLS: the Partial Least-Squares Method F2.4.22 Geometrical Interpretation of PLS F2.4.23 The First PLS Component F2.4.24 The Second PLS Component F2.4.25 3D-QSAR Equation in the PLS Space F2.4.26 Back to Space of Original Descriptors F2.4.27 The 3D-QSAR Equation in the Original Data Space F2.4.28 Many Terms in the 3D-QSAR Equation F2.4.29 Measuring the Quality of the Relationship F2.4.30 Total Number of PLS Components F2.4.31 Two Equivalent 3D-QSAR Equations F2.4.32 Predicting the Activities of New Compounds F2.4.33 CoMFA Coefficient Contour Maps F2.4.34 CoMFA Steric Contour Map F2.4.35 CoMFA Electrostatic Contour Map F2.4.36 CoMFA Contour Maps vs. MIF Contour Maps F2.4.37 Analysis of Steric Contour Maps F2.4.38 Analysis of Electrostatic Contour Maps F2.4.39 Exploitation of the Steric Contour Map F2.4.40 Exploitation of the Electrostatic Contour Map F2.4.41 Stability Problem of CoMFA Models

F2.5. Example of CoMFA Analysis: Steroids F2.5.1 The Reference Compounds F2.5.2 The Biological Data F2.5.3 Molecular Alignment F2.5.4 CoMFA Field Calculations F2.5.5 CoMFA and PLS Results vs. Classical QSAR F2.5.6 Steric CoMFA Map for Binding to TBG

F2.5.7 Electrostatic CoMFA Map for Binding to TBG F2.5.8 CBG Affinities of New Steroids F2.5.9 Predicting the CBG Affinities of New Steroids F2.5.10 A Benchmark Set for 3D-QSAR

F2.6. Other 3D-QSAR Methods F2.6.1 3D-QSAR Programs F2.6.2 Best Method? F2.6.3 CoMFA F2.6.4 HASL F2.6.5 CoMSIA F2.6.6 CoMMA F2.6.7 MS-WHIM F2.6.8 SOMFA F2.6.9 HQSAR F2.6.10 GRIND F2.6.11 Quasar F2.6.12 CoMASA F2.6.13 WeP

F2.7. Conclusion F2.7.1 Conclusion

F2.8. CHAPTER QUIZZES (Available only in Teaching Package) F2.8.1 Quiz 1 F2.8.2 Quiz 2 F2.8.3 Quiz 3 F2.8.4 Quiz 4 F2.8.5 Quiz 5 F2.8.6 Quiz 6 F2.8.7 Quiz 7 F2.8.8 Quiz 8 F2.8.9 Quiz 9 F2.8.10 Quiz 10 F2.8.11 Quiz 11 F2.8.12 Quiz 12 F2.8.13 Quiz 13 F2.8.14 Quiz 14 F2.8.15 Quiz 15 F2.8.16 Quiz 16 F2.8.17 Quiz 17 F2.8.18 Quiz 18 F2.8.19 Quiz 19 F2.8.20 Quiz 20 F2.8.21 Quiz 21 F2.8.22 Quiz 22 F2.8.23 Quiz 23 F2.8.24 Quiz 24 F2.8.25 Quiz 25 F2.8.26 Quiz 26 F2.8.27 Quiz 27 F2.8.28 Quiz 28 F2.8.29 Quiz 29

F2.8.30 Quiz 30 F2.8.31 Quiz 31 F2.8.32 Quiz 32 F2.8.33 Quiz 33 F2.8.34 Quiz 34 F2.8.35 Quiz 35 F2.8.36 Quiz 36

G. SYNTHESIS AND LIBRARY DESIGN

G1. SYNTHESIS OF DRUGS

G1.1. Introduction G1.1.1 Why to Synthesize a New Molecule? G1.1.2 Drug Discovery G1.1.3 Bulk Production G1.1.4 Goal of the Synthesis G1.1.5 General Requirements before Starting G1.1.6 Number of Steps and Intermediates G1.1.7 Measurable Reaction's Characteristics G1.1.8 Yield G1.1.9 Reaction Rate G1.1.10 Product Selectivity G1.1.11 Regioselectivity and Regiospecificity G1.1.12 Stereoselectivity and Stereospecificity G1.1.13 Thermodynamic and Kinetic Properties of the Reaction G1.1.14 Thermodynamics G1.1.15 Kinetics G1.1.16 Determinants of a Chemical Reaction G1.1.17 Steric Effects G1.1.18 Electronics Effects G1.1.19 Solvent Effects G1.1.20 How to Influence a Reaction? G1.1.21 Reactant Choice G1.1.22 Reagent Choice G1.1.23 Reaction Conditions G1.1.24 Influence of pH G1.1.25 Influence of the Solvent G1.1.26 Catalysts G1.1.27 Tools for Following the Progression of a Reaction G1.1.28 Spectroscopy G1.1.29 Mass Spectra (MS) G1.1.30 Infrared (IR) G1.1.31 Nuclear Magnetic Resonance (NMR) G1.1.32 Ultraviolet (UV) G1.1.33 Circular Dichroism (CD) and Optical Rotatory Dispersion (ORD) G1.1.34 X-rays G1.1.35 Chromatography G1.1.36 High Performance Liquid Chromatography (HPLC) G1.1.37 Chiral Chromatography

G1.2. Design Strategy G1.2.1 Strategy Like a General in the Battle G1.2.2 Flexibility in the Strategy G1.2.3 Flexibility in the Synthetic Program G1.2.4 Flexibility in the Target Molecule G1.2.5 Nicolaou Statement on the Trip to Ithaca G1.2.6 Linear and Convergent Strategy G1.2.7 Linear Strategy G1.2.8 Example: Captopril Linear Synthesis G1.2.9 Convergent Strategy G1.2.10 Convergent Advantage G1.2.11 Example: Losartan Convergent Synthesis G1.2.12 How to Analyze a Molecule for Synthesis? G1.2.13 Three Methods for the Design of a Synthetic Program G1.2.14 Adapt Known Synthetic Schemes G1.2.15 Literature and Patent Searches G1.2.16 Database Searching with Computer Programs G1.2.17 Consider a Building Block Strategy G1.2.18 Small Commercial Building Blocks G1.2.19 Elaborated Building Blocks G1.2.20 Starting from Scratch - Retrosynthetic Analysis G1.2.21 Retrosynthetic Strategy G1.2.22 Disconnection of Strategic Bonds G1.2.23 Strategic Bonds Revealed by Small Modifications G1.2.24 FGA G1.2.25 FGI G1.2.26 FGR G1.2.27 The Retrosynthetic Process G1.2.28 From TC to SM G1.2.29 The Synthetic Program G1.2.30 The Tetrodotoxin Example G1.2.31 Simple Exercise in Retrosynthesis G1.2.32 Retrosynthesis G1.2.33 Synthesis G1.2.34 Disconnection Methods for Retrosynthesis G1.2.35 Homolytic Disconnection G1.2.36 Heterolytic Disconnection G1.2.37 Pericyclic Bond Disconnection G1.2.38 Combining the Three Synthetic Methods

G1.3. Synthetic Tactic G1.3.1 Principles of Synthetic Tactics G1.3.2 Reaction Classifications G1.3.3 By Changes Occurring in the Reactant Molecules G1.3.4 By Reaction Types G1.3.5 By Functional Groups G1.3.6 Protecting Groups G1.3.7 Protecting Reactive Centers G1.3.8 Requirements for Protecting Groups G1.3.9 Protection and Deprotection of Amino Acids G1.3.10 Examples of Protecting Groups G1.3.11 Alcohol Protection

G1.3.12 Carboxylic Acid Protection G1.3.13 Amine Protection G1.3.14 Phenol Protection G1.3.15 How to Assess the Quality of a Synthesis? G1.3.16 Syntheses of Swainsonine

G1.4. Stereochemical Issues G1.4.1 Why Chiral Drugs? G1.4.2 Examples of Chiral Drugs G1.4.3 Multiple Aspects of Molecular Chirality G1.4.4 Active and Inactive Enantiomers G1.4.5 'Chiral Switch' : From a Racemic to a Chiral Drug G1.4.6 Advantages of Single Enantiomer Drugs G1.4.7 Pharmacokinetic Properties G1.4.8 Perhexiline G1.4.9 Selectivity G1.4.10 Ritalin G1.4.11 Penicillamine G1.4.12 Ethambutol G1.4.13 Ketamine G1.4.14 L-Dopa G1.4.15 Patent Position G1.4.16 Three Methods to Obtain Chiral Molecules G1.4.17 Racemic Route G1.4.18 Resolution of Racemates G1.4.19 Example of Industrial Racemate Separation G1.4.20 Recycling Undesired Enantiomer G1.4.21 Sometimes Separation very Difficult G1.4.22 When Too Many Chiral Centers G1.4.23 Asymmetric Route G1.4.24 Chiral Reagents and Reactants G1.4.25 Chiral Catalysts G1.4.26 Asymmetric Synthesis in R&D. G1.4.27 Extraction From Natural Sources G1.4.28 Stereoselectivity of Action not Always Predictable G1.4.29 Spontaneous Enantiomer Interconversion

G1.5. Structural Diversity and Higher Level Synthetic Strategies G1.5.1 Diverse Strategy in Drug Discovery G1.5.2 Introducing Diversity in the Reagents G1.5.3 Introducing Diversity at the Proper Time G1.5.4 Late Stage Introduction of Diversity G1.5.5 Early Stage Introduction of Diversity G1.5.6 Diversity Space Restricted by Synthetic Route G1.5.7 Consider Alternative Syntheses G1.5.8 Example of Introduction of Diversity G1.5.9 Combinatorial Chemistry G1.5.10 Diversity-Oriented Synthesis (DOS) G1.5.11 Maximizing the Chance to Find a Hit G1.5.12 Example of Diversity-Oriented Synthesis G1.5.13 Higher Level Strategies in Organic Synthesis

G1.6. Synthesis of Some Common Drugs

G1.6.1 Introduction to Synthetic Schemes G1.6.2 Benzocaine G1.6.3 Retrosynthetic Scheme G1.6.4 Benzocaine Synthesis G1.6.5 Physico-Chemical Properties of Benzocaine G1.6.6 Aspirin G1.6.7 Aspirin Synthesis G1.6.8 Physico-Chemical Properties of Aspirin G1.6.9 Nalidixic Acid G1.6.10 Retrosynthetic Scheme G1.6.11 Nalidixic Acid Synthesis G1.6.12 Physico-Chemical Properties of Nalidixic Acid G1.6.13 Zidovudine (AZT) G1.6.14 Retrosynthetic Scheme G1.6.15 AZT Synthesis G1.6.16 Another Synthesis for AZT G1.6.17 Which Route is Preferable? G1.6.18 Physico-Chemical Properties of Zidovudine G1.6.19 Terfenadine G1.6.20 Retrosynthetic Scheme G1.6.21 Terfenadine Synthesis G1.6.22 Physico-Chemical Properties of Terfenadine G1.6.23 Nifedipine G1.6.24 Simple Retrosynthesis of Nifedipine G1.6.25 One-Pot Synthesis of Nifedipine G1.6.26 Two Steps Retrosynthesis Scheme of Nifedipine G1.6.27 Two Steps Synthesis of Nifedipine G1.6.28 Physico-Chemical Properties of Nifedipine G1.6.29 Sildenafil (Viagra) G1.6.30 Retrosynthetic Scheme G1.6.31 Sildenafil Synthesis G1.6.32 Physico-Chemical Properties of Sildenafil

G1.7. Programs for Computer-Aided Synthesis G1.7.1 Programs for Computer-Aided Synthesis G1.7.2 Retrosynthetic Programs G1.7.3 LHASA G1.7.4 SYNCHEM G1.7.5 SECS, OCCS, CASP G1.7.6 Formal and Mathematically-Based Programs G1.7.7 IGOR G1.7.8 EROS G1.7.9 SYNGEN G1.7.10 RAIN G1.7.11 Forward Reaction Predictions G1.7.12 CAMEO G1.7.13 CHIRON G1.7.14 WODCA G1.7.15 Other Programs G1.7.16 AIPHOS G1.7.17 CAESA G1.7.18 AOCR

G1.7.19 SYSTEMATICHEM

G1.8. Databases for Organic Synthesis G1.8.1 Databases for Organic Synthesis G1.8.2 Printed Information G1.8.3 Specialized Abstracting Services G1.8.4 Chemical Abstracts Services (CAS) G1.8.5 SciFinder G1.8.6 Beilstein G1.8.7 Gmelin G1.8.8 Reaction Databases G1.8.9 On-Line Resources G1.8.10 Patent Databases G1.8.11 US Patents: USPTO G1.8.12 European Patents: EPOLINE G1.8.13 Other Patent Databases

G1.9. CHAPTER QUIZZES (Available only in Teaching Package) G1.9.1 Quiz 1 G1.9.2 Quiz 2 G1.9.3 Quiz 3 G1.9.4 Quiz 4 G1.9.5 Quiz 5 G1.9.6 Quiz 6 G1.9.7 Quiz 7 G1.9.8 Quiz 8 G1.9.9 Quiz 9 G1.9.10 Quiz 10 G1.9.11 Quiz 11 G1.9.12 Quiz 12 G1.9.13 Quiz 13 G1.9.14 Quiz 14 G1.9.15 Quiz 15 G1.9.16 Quiz 16 G1.9.17 Quiz 17 G1.9.18 Quiz 18 G1.9.19 Quiz 19 G1.9.20 Quiz 20 G1.9.21 Quiz 21 G1.9.22 Quiz 22 G1.9.23 Quiz 23 G1.9.24 Quiz 24 G1.9.25 Quiz 25 G1.9.26 Quiz 26 G1.9.27 Quiz 27 G1.9.28 Quiz 28 G1.9.29 Quiz 29 G1.9.30 Quiz 30 G1.9.31 Quiz 31 G1.9.32 Quiz 32 G1.9.33 Quiz 33 G1.9.34 Quiz 34

G1.9.35 Quiz 35 G1.9.36 Quiz 36 G1.9.37 Quiz 37 G1.9.38 Quiz 38 G1.9.39 Quiz 39 G1.9.40 Quiz 40 G1.9.41 Quiz 41 G1.9.42 Quiz 42 G1.9.43 Quiz 43 G1.9.44 Quiz 44 G1.9.45 Quiz 45 G1.9.46 Quiz 46 G1.9.47 Quiz 47 G1.9.48 Quiz 48 G1.9.49 Quiz 49 G1.9.50 Quiz 50 G1.9.51 Quiz 51 G1.9.52 Quiz 52 G1.9.53 Quiz 53 G1.9.54 Quiz 54 G1.9.55 Quiz 55 G1.9.56 Quiz 56 G1.9.57 Quiz 57 G1.9.58 Quiz 58 G1.9.59 Quiz 59 G1.9.60 Quiz 60 G1.9.61 Quiz 61 G1.9.62 Quiz 62 G1.9.63 Quiz 63 G1.9.64 Quiz 64 G1.9.65 Quiz 65 G1.9.66 Quiz 66 G1.9.67 Quiz 67 G1.9.68 Quiz 68 G1.9.69 Quiz 69 G1.9.70 Quiz 70 G1.9.71 Quiz 71 G1.9.72 Quiz 72 G1.9.73 Quiz 73 G1.9.74 Quiz 74 G1.9.75 Quiz 75 G1.9.76 Quiz 76 G1.9.77 Quiz 77 G1.9.78 Quiz 78 G1.9.79 Quiz 79 G1.9.80 Quiz 80 G1.9.81 Quiz 81 G1.9.82 Quiz 82 G1.9.83 Quiz 83 G1.9.84 Quiz 84 G1.9.85 Quiz 85

G1.9.86 Quiz 86 G1.9.87 Quiz 87 G1.9.88 Quiz 88 G1.9.89 Quiz 89 G1.9.90 Quiz 90 G1.9.91 Quiz 91 G1.9.92 Quiz 92 G1.9.93 Quiz 93 G1.9.94 Quiz 94 G1.9.95 Quiz 95 G1.9.96 Quiz 96 G1.9.97 Quiz 97 G1.9.98 Quiz 98 G1.9.99 Quiz 99 G1.9.100 Quiz 100 G1.9.101 Quiz 101 G1.9.102 Quiz 102 G1.9.103 Quiz 103

G2. LIBRARY DESIGN

G2.1. Introduction G2.1.1 Libraries of Molecules Prepared One by One G2.1.2 The Combinatorial Chemistry Boom G2.1.3 Initial Disapointments G2.1.4 The Quest of Quality G2.1.5 Chemical Diversity Space G2.1.6 Library Representation G2.1.7 Definition of a Virtual Library G2.1.8 Scaffolds-Substituents-Reactions

G2.2. The Basis of a Good Scaffold G2.2.1 Scaffold: the First Piece of a Complex Jigsaw Puzzle G2.2.2 Cyclic and Acyclic Scaffold G2.2.3 The Scaffold, a Fuzzy Concept G2.2.4 The Scaffold Names G2.2.5 Scaffold Requirements G2.2.6 Scaffold and ADME Properties G2.2.7 Geometrical Requirements G2.2.8 Avoid Clashes with the Receptor G2.2.9 Good Binding Interactions With the Scaffold G2.2.10 Good Vector Orientation G2.2.11 Patent Position and Novelty G2.2.12 Problems of Scaffolds Patentability G2.2.13 Patentable Scaffold G2.2.14 Validation of Novelty G2.2.15 Syntheses Amenable to Combinatorial Chemistry G2.2.16 Bond-Formation for Array Synthesis Methods G2.2.17 Ideal Scaffold: a Multi-Project Template G2.2.18 A Universal Spacer as a Master Key G2.2.19 Diversity of the Space Covered by the Substituents

G2.2.20 Benzodiazepine Scaffold as a Spacer G2.2.21 A Master Key Adapted for a Family G2.2.22 Kinase Example G2.2.23 Gleevec: from PKC to Abl Inhibition G2.2.24 Modulation with Simplified Staurosporine Scaffolds G2.2.25 Quinazoline Scaffold

G2.3. Scaffold Selection and Design G2.3.1 Methods for Designing a new Scaffold G2.3.2 Small Modification of Known Scaffold G2.3.3 2D Similarity Searching G2.3.4 3D Superimpositions G2.3.5 Docking and Virtual Screening G2.3.6 3D Shape Searching G2.3.7 2D Pharmacophore Searching G2.3.8 3D Pharmacophore Searching G2.3.9 Vector Matching G2.3.10 Hybrids of Known Scaffolds G2.3.11 Creative Design

G2.4. Focused and Diverse Strategies G2.4.1 Library Design Goals G2.4.2 Library Design Assumptions - Similar Property Principle G2.4.3 Analogy with Battleships Game G2.4.4 Diversity Strategy G2.4.5 Molecular Diversity G2.4.6 Focused Strategies G2.4.7 Diverse vs. Focused G2.4.8 Library Design in the Global Drug Discovery Perspective G2.4.9 Informative Libraries G2.4.10 Commercial Informative Libraries

G2.5. CDK2 Example: Design of a Focused Library G2.5.1 Purine Scaffold as a Source of Bioactive Molecules G2.5.2 CDK2 Biological Target and Known Inhibitors G2.5.3 Diverse 2,6,9-trisubstituted Purine Libraries G2.5.4 Substituent Design G2.5.5 Additivity of the Biological Effects G2.5.6 Browser of Substituents at the C-2 Position G2.5.7 Browser of Substituents at the C-6 Position G2.5.8 Successive Rounds G2.5.9 Library Results

G2.6. Measuring Distances Between Molecules G2.6.1 Methods to Calculate Molecular Similarity G2.6.2 The Distance-Based and the Binary-Based Methods G2.6.3 The Property-Based Approach G2.6.4 Molecules in the Space of their Relevant Properties G2.6.5 From Molecular Properties to Molecular Descriptors G2.6.6 High-Dimensionality Space of the Molecular Descriptors G2.6.7 Similarity Coefficient and Distance Coefficient G2.6.8 Euclidian Distance G2.6.9 Tanimoto Coefficient

G2.6.10 The Structural Approach G2.6.11 Relevant Structural Keys G2.6.12 Extended 3D Fingerprints G2.6.13 Example of Structural Key G2.6.14 Similarity Coefficients and Distance Coefficients G2.6.15 Binary Tanimoto Example G2.6.16 Computational Speed G2.6.17 Similarity Index of an Entire Library G2.6.18 Huge Dataset of Undigested Information G2.6.19 Principal Components Analysis

G2.7. Subset Selection Issues G2.7.1 Subset Selection Problem G2.7.2 Illustration of the Subset Selection Problem G2.7.3 The Systematic Route G2.7.4 Systematic Assessment Impracticable G2.7.5 Solving the Subset Selection Problem G2.7.6 Distance-Based Methods G2.7.7 Clustering Methods G2.7.8 Cell-Based Partitioning G2.7.9 Optimization of Diversity Function G2.7.10 Example of Selection of Diverse Compounds G2.7.11 The Input G2.7.12 Normalization of the Data G2.7.13 The Results

G2.8. Reagent Selection G2.8.1 Cherry Picking Limitations G2.8.2 Optimization of Diversity and Synthetic Issues G2.8.3 Example of Optimization Algorithm G2.8.4 Selecting Reagents is a Complex Issue

G2.9. Increasing the Quality of a Library (ADMET) G2.9.1 Failures in Clinical Trials G2.9.2 Failure in Drug Discovery G2.9.3 Early Integration of ADME Properties in Drug Discovery G2.9.4 The Drug-Like Approach and the Predictive Approach G2.9.5 The Drug-Like Approach: Identify Poor Candidates G2.9.6 Structural Mimicry and ADME Properties Mimicry G2.9.7 The Rule-Based Approach G2.9.8 Lipinski Rules (Rule of 5) G2.9.9 MW Distribution G2.9.10 LogP Distribution G2.9.11 H-Bond Donor Distribution G2.9.12 H-Bond Acceptor Distribution G2.9.13 Total Analysis G2.9.14 Other Rules G2.9.15 Remove Too Flexible Molecules G2.9.16 Remove Molecules with too Many Rings G2.9.17 Remove Compounds with Known Toxic Moieties G2.9.18 Remove Compounds with Reactive Groups G2.9.19 Remove False-Positive Hits G2.9.20 Remove Poorly Soluble Compounds

G2.9.21 Filter on Heteroatoms and Non-Organic Molecules G2.9.22 Remove Molecules with Multiple Chiral Centers G2.9.23 Tailor-Made Filtering G2.9.24 Assisting Medicinal Chemist Expertise and Intuition G2.9.25 Privileged Drug-Like Scaffolds G2.9.26 Building Blocks Based on Known Drugs G2.9.27 The Computational Approach G2.9.28 Prediction of Absorption G2.9.29 Prediction of Metabolism G2.9.30 Prediction of Distribution and Elimination G2.9.31 Prediction of Toxicity G2.9.32 Lack of Standardized ADMET Databases G2.9.33 Available Software

G2.10. Example of Library Analysis G2.10.1 Common Treatments in Library Analysis G2.10.2 Import of Libraries in a Common Database G2.10.3 Cleaning Up the Database G2.10.4 Set Stereoisomers G2.10.5 Assessing the Uniqueness of a Library G2.10.6 Drug-Likeness: Lipinski Rule of 5 G2.10.7 Drug-Likeness: Other Filters G2.10.8 Diversity Analysis with Molecular Descriptors G2.10.9 Diversity Analysis with Fingerprints and PCA G2.10.10 Final Results

G2.11. CHAPTER QUIZZES (Available only in Teaching Package) G2.11.1 Quiz 1 G2.11.2 Quiz 2 G2.11.3 Quiz 3 G2.11.4 Quiz 4 G2.11.5 Quiz 5 G2.11.6 Quiz 6 G2.11.7 Quiz 7 G2.11.8 Quiz 8 G2.11.9 Quiz 9 G2.11.10 Quiz 10 G2.11.11 Quiz 11 G2.11.12 Quiz 12 G2.11.13 Quiz 13 G2.11.14 Quiz 14 G2.11.15 Quiz 15 G2.11.16 Quiz 16 G2.11.17 Quiz 17 G2.11.18 Quiz 18 G2.11.19 Quiz 19 G2.11.20 Quiz 20 G2.11.21 Quiz 21 G2.11.22 Quiz 22 G2.11.23 Quiz 23 G2.11.24 Quiz 24 G2.11.25 Quiz 25

G2.11.26 Quiz 26 G2.11.27 Quiz 27 G2.11.28 Quiz 28 G2.11.29 Quiz 29 G2.11.30 Quiz 30 G2.11.31 Quiz 31 G2.11.32 Quiz 32 G2.11.33 Quiz 33 G2.11.34 Quiz 34 G2.11.35 Quiz 35 G2.11.36 Quiz 36 G2.11.37 Quiz 37 G2.11.38 Quiz 38 G2.11.39 Quiz 39 G2.11.40 Quiz 40 G2.11.41 Quiz 41 G2.11.42 Quiz 42 G2.11.43 Quiz 43 G2.11.44 Quiz 44 G2.11.45 Quiz 45 G2.11.46 Quiz 46 G2.11.47 Quiz 47 G2.11.48 Quiz 48 G2.11.49 Quiz 49 G2.11.50 Quiz 50 G2.11.51 Quiz 51 G2.11.52 Quiz 52 G2.11.53 Quiz 53 G2.11.54 Quiz 54 G2.11.55 Quiz 55 G2.11.56 Quiz 56 G2.11.57 Quiz 57 G2.11.58 Quiz 58 G2.11.59 Quiz 59 G2.11.60 Quiz 60 G2.11.61 Quiz 61 G2.11.62 Quiz 62 G2.11.63 Quiz 63 G2.11.64 Quiz 64 G2.11.65 Quiz 65 G2.11.66 Quiz 66 G2.11.67 Quiz 67 G2.11.68 Quiz 68 G2.11.69 Quiz 69 G2.11.70 Quiz 70 G2.11.71 Quiz 71 G2.11.72 Quiz 72 G2.11.73 Quiz 73 G2.11.74 Quiz 74 G2.11.75 Quiz 75 G2.11.76 Quiz 76

H. PEPTIDOMIMETICS

H1. PEPTIDOMIMETICS

H1.1. Introduction H1.1.1 Key Peptides in Drug Discovery H1.1.2 Definition of Peptidomimetics H1.1.3 Problems with Peptide Molecules H1.1.4 The Aim of Peptidomimetics H1.1.5 Typical Peptidomimicry Projects

H1.2. Structural Modifications H1.2.1 Range of Structural Modifications H1.2.2 Side Chain Mimicry H1.2.3 Short-Range Cyclizations (Bridging) H1.2.4 Long Range Cyclizations H1.2.5 Mimicking the Peptidic Bond H1.2.6 Browser of Bioisosteric Replacements H1.2.7 Cα Modifications H1.2.8 Tetra Substituted Amino Acids H1.2.9 Azapeptides H1.2.10 Extension of the Peptide Chain H1.2.11 β-Peptides

H1.3. Two Alternative Routes H1.3.1 From Peptides to Non-peptidic Molecules H1.3.2 First Route: Successive Modifications of Peptide H1.3.3 Depeptidization H1.3.4 Problems with Peptide-Based Analogs H1.3.5 Example of Reduction of Peptide Character H1.3.6 A-72517 is a Mimic of Angiotensinogen H1.3.7 Dead End in the Development of A-72517 H1.3.8 Second Route:De Novo Design of Non Peptide Mimics H1.3.9 Operational Framework H1.3.10 Which Route Should be Used?

H1.4. The Challenge of Peptidomimicry H1.4.1 Challenges in Peptide Modifications H1.4.2 Challenges in Non-Peptidic Mimicry H1.4.3 Perspectives in Peptidomimetics

H1.5. CHAPTER QUIZZES (Available only in Teaching Package) H1.5.1 Quiz 1 H1.5.2 Quiz 2 H1.5.3 Quiz 3 H1.5.4 Quiz 4 H1.5.5 Quiz 5 H1.5.6 Quiz 6 H1.5.7 Quiz 7 H1.5.8 Quiz 8 H1.5.9 Quiz 9 H1.5.10 Quiz 10

H1.5.11 Quiz 11 H1.5.12 Quiz 12 H1.5.13 Quiz 13 H1.5.14 Quiz 14 H1.5.15 Quiz 15 H1.5.16 Quiz 16 H1.5.17 Quiz 17 H1.5.18 Quiz 18 H1.5.19 Quiz 19 H1.5.20 Quiz 20 H1.5.21 Quiz 21 H1.5.22 Quiz 22 H1.5.23 Quiz 23 H1.5.24 Quiz 24 H1.5.25 Quiz 25 H1.5.26 Quiz 26 H1.5.27 Quiz 27 H1.5.28 Quiz 28 H1.5.29 Quiz 29

H2. PEPTIDOMIMETICS EXAMPLES

H2.1. TRH Mimicry H2.1.1 Ro-24-9975 is a Non-Peptidic Mimic of TRH H2.1.2 TRH Browser

H2.2. Inhibitors of HLE H2.2.1 Inhibition of Human Leukocyte Elastase H2.2.2 Problem of Peptide-Based ICI-200,880 H2.2.3 TFMK as a Reference H2.2.4 Analysis of the Binding of TFMK H2.2.5 Summary of the Analyses H2.2.6 Design of a New Pyridone Framework H2.2.7 Optimization of the Pyridone Series H2.2.8 Browser of HLE Inhibitors

H2.3. Renin Inhibitors H2.3.1 The Renin-Angiotensin System Cascade H2.3.2 The First Generation of Renin Inhibitors H2.3.3 The Second Generation of Renin Inhibitors H2.3.4 Low Oral Absorption of CGP-38560 H2.3.5 Bioactive Conformation of CGP-38560 H2.3.6 Strategy for the Design of Non-Peptidic Inhibitors H2.3.7 Successful Design of a Non-Peptidic Inhibitor H2.3.8 Optimization of the Tetrahydro-Quinoline Inhibitor H2.3.9 A Third Generation of Renin Inhibitors

H2.4. Substance P Antagonists H2.4.1 Substance P : a Ligand of CNS Receptors H2.4.2 The Successful Discovery of SP Antagonists H2.4.3 A Phe-Phe Mimic of Substance P H2.4.4 Mimicry of CGP-47899 and Substance P

H2.5. Angiotensin-II Antagonists H2.5.1 Antagonists of Angiotensin-II Receptors H2.5.2 Losartan as a Mimic of Angiotensin-II H2.5.3 Browser of Angiotensin-II Antagonists

H2.6. Inhibitors of HIV-1 Protease H2.6.1 HIV-1 Protease Inhibition H2.6.2 The Peptide Problem H2.6.3 Database Searching for Non-Peptidic Scaffolds H2.6.4 Analysis of the Content of the Hit H2.6.5 Design of Cyclic Urea Scaffold H2.6.6 XK-263 is a Non-Peptidic Mimic of A-77003

H2.7. δ-Opioid Receptor Agonists H2.7.1 Therapeutic utility of δ-Opioid Receptor Agonists H2.7.2 Typical Peptide δ-Opioid Receptor Agonists H2.7.3 Typical Non-Peptide δ-Opioid Receptor Agonists H2.7.4 Pharmacophore for δ-Opioid Receptor Agonists H2.7.5 SAR, NMR and Modeling of the DPDPE series H2.7.6 Bioactive Conformation of DPDPE H2.7.7 Scaffold Design of Non-Peptide Antagonists: H2.7.8 Refinement of the Scaffold and Substituents H2.7.9 The First Series Synthesized

H2.8. Farnesyltransferase Inhibitors H2.8.1 Farnesyltransferase, a Target in Oncology H2.8.2 X-ray Structure of FTase with a Tetrapeptide H2.8.3 Binding Interactions of CAAX Substrate for FTase H2.8.4 4-Aminobenzoic Spacer to Replace Val-Ile Dipeptide H2.8.5 The Simple Aromatic Central Ring is not Sufficient H2.8.6 Analogs with Significantly Enhanced Potency H2.8.7 Terphenyl to Replace the Central Val-Ile Dipeptide H2.8.8 Potent and Selective Farnesyltransferase Inhibitor H2.8.9 Browser of Farnesyltransferase Inhibitors

H2.9. Motilin Receptor Antagonists H2.9.1 Motilin Receptor Antagonists H2.9.2 Motilin Receptor and Motilin Peptide H2.9.3 Structural Analyses on Motilin H2.9.4 Bioactive Conformation of Motilin H2.9.5 Biologically Relevant Residues of Motilin H2.9.6 The Motilin Pharmacophore H2.9.7 RWJ-64583: a Trisubstituted Cyclopentene Lead H2.9.8 The Three-point Pharmacophore and RWJ-64583 H2.9.9 Optimization of the Initial Lead Molecule

H2.10. MC4R Melanocortin Receptor Agonists H2.10.1 Melanocortin Receptors H2.10.2 Minimal Peptide Sequence for Activating the Receptor H2.10.3 Strategy for the Design of New Agonists H2.10.4 Molecular Geometry of the Cyclic Peptide H2.10.5 Design of Molecules with a Cyclohexane Core H2.10.6 Cis and Trans Cyclohexane Isomers H2.10.7 Molecular Geometries of the Cis and Trans Isomers

H2.10.8 Overlap of Molecule 2 with the Peptidic Agonist H2.10.9 Discovery of a Nanomolar Non-Peptidic Agonist

H2.11. Antagonists of the Mdm2-p53 Interaction H2.11.1 Antagonists of the Mdm2-p53 Interaction H2.11.2 Mdm2 Bound to p53 Transactivation Domain H2.11.3 Systematic SAR Studies H2.11.4 3D Structure of the Pharmacophore H2.11.5 The Novartis 5 nM Peptide-Like Antagonist H2.11.6 Problems with the Peptide-Based Antagonists H2.11.7 The Bicyclo [2.2.1]-Heptane Scaffold H2.11.8 Designed Scaffold Aligned with the Pharmacophore

H2.12. Somatostatin Mimicry H2.12.1 Somatostatin Structure H2.12.2 Somatostatin Receptors H2.12.3 The Somatostatin Pharmacophore H2.12.4 Successful Reduction of the Somatostatin H2.12.5 Mimics of L-363,377 with Database Searching H2.12.6 Results of the Database Searching H2.12.7 A Good Mimic of the Reference Cyclic Peptide H2.12.8 Development of a Combinatorial Chemistry Approach H2.12.9 Combinatorial Chemistry Results H2.12.10 An Integrated Approach to Drug Discovery

I. ADME PROPERTIES AND PREDICTIONS

I1. ADME PROPERTIES

I1.1. Introduction I1.1.1 Therapeutics I1.1.2 Pharmacokinetics I1.1.3 Pharmacodynamics I1.1.4 Dose-Response Relationships I1.1.5 The Drug Route I1.1.6 Absorption I1.1.7 Distribution I1.1.8 Metabolism I1.1.9 Excretion I1.1.10 Bioavailability I1.1.11 Dose-Response Relationship I1.1.12 Translocation of Drugs I1.1.13 Cell Membrane Architecture I1.1.14 Passive Diffusion I1.1.15 Endocytosis and Exocytosis I1.1.16 Carrier-Mediated Transport

I1.2. Absorption I1.2.1 Drug Absorption I1.2.2 Incomplete Absorption of Drug Dose I1.2.3 Routes of Administration I1.2.4 Properties of Drugs that Influence Absorption

I1.2.5 Lipophilicity and Membrane Penetration I1.2.6 pKa of a Drug and pH I1.2.7 Water Solubility and Dissolution

I1.3. Distribution I1.3.1 Drug Distribution I1.3.2 Drug Translocation and Distribution I1.3.3 Site of Action I1.3.4 Distribution is to Many Body Sites I1.3.5 Apparent Volume of Distribution I1.3.6 Vd and Drug Distribution Patterns I1.3.7 Meaning of Vd I1.3.8 Factors that Influence Drug Distribution I1.3.9 Perfusion and Membrane Permeability I1.3.10 Binding to Plasma Proteins I1.3.11 Accumulation in Organs and Tissues I1.3.12 Ion Trapping I1.3.13 Biological Barriers (BBB, Placental, Blood-Testis) I1.3.14 Distribution as Equilibrium State

I1.4. Metabolism I1.4.1 Metabolism of Foreign Substances (Xenobiotics) I1.4.2 Metabolic Reactions I1.4.3 Pathways of Metabolism I1.4.4 Chemistry of Phase I Metabolism I1.4.5 Chemistry of Phase II Metabolism I1.4.6 Metabolic Activation and Toxification I1.4.7 Sites of Drug Metabolism I1.4.8 Drug Metabolizing Enzymes I1.4.9 Cytochrome P-450 (CYP) I1.4.10 Oxidative Metabolism by Cytochrome P-450 Enzymes I1.4.11 Mechanism of Cytochrome P-450 Oxidation I1.4.12 Metabolic Variability I1.4.13 Genetic Polymorphisms I1.4.14 Age I1.4.15 A Drug Metabolism Inhibited by Another Drug I1.4.16 Metabolism Increased by Enzymatic Induction I1.4.17 Metabolism and Drug Design I1.4.18 Hard Drugs I1.4.19 Removing I1.4.20 Hiding I1.4.21 Stabilizing I1.4.22 Soft Drugs I1.4.23 Topical Use I1.4.24 Ultrashort Use I1.4.25 Oral Use I1.4.26 Pro-Drugs I1.4.27 Oral Absorption I1.4.28 Prolonged Activity I1.4.29 Improved Formulation I1.4.30 BBB Penetration I1.4.31 Tumor Targeting

I1.5. Excretion I1.5.1 Excretion I1.5.2 Renal Excretion I1.5.3 Glomerular Filtration I1.5.4 Tubular Secretion I1.5.5 Tubular Reabsorption I1.5.6 Biliary Excretion I1.5.7 Other Excretion Routes I1.5.8 Clearance I1.5.9 Half-life

I1.6. ADME in Drug Design I1.6.1 Failures in Drug Development I1.6.2 Challenge of R&D Planning I1.6.3 High-Throughput ADME Evaluations I1.6.4 In Silico Prediction of ADME Properties I1.6.5 Lipinski Rules and Drug-Like Properties I1.6.6 More Insights into ADME Predictions

J. CHEMINFORMATICS

J1. CHEMINFORMATICS, PRINCIPLES AND APPLICATIONS

J1.1. Introduction J1.1.1 What is Cheminformatics ? J1.1.2 Cheminformatics or Chemoinformatics ? J1.1.3 Cheminformatics and Drug Discovery J1.1.4 Cheminformatics: Integration of Three Disciplines J1.1.5 Historical Background of Pharmaceutical Research J1.1.6 Molecular Modeling J1.1.7 Chemical Information J1.1.8 Coupling Modeling and Chemical Information J1.1.9 The Data Analysis Contribution J1.1.10 Example of Successful Integration J1.1.11 Definitions of Cheminformatics J1.1.12 Cheminformatics vs. Structural Bioinformatics J1.1.13 Encoding Molecules J1.1.14 Development of Algorithms J1.1.15 Facilitate Multidisciplinary Communication

J1.2. Molecular Modeling J1.2.1 Pharmacophore Mapping J1.2.2 The Concept of 3D Pharmacophores J1.2.3 Pharmacophoric Structural Elements J1.2.4 What is Pharmacophore Mapping ? J1.2.5 Manual Pharmacophore Mapping J1.2.6 Derivation of Pharmacophore Hypotheses J1.2.7 Steps in Deriving a Pharmacophore J1.2.8 The Initial Training Set J1.2.9 Generation of Conformers J1.2.10 Which Combination of Structural Elements?

J1.2.11 Manual Method J1.2.12 Example of Tricyclic Antidepressants J1.2.13 Design of Non-Tricyclic Structures J1.2.14 Automated Methods J1.2.15 Automated Methods: the Conformational Issue J1.2.16 Common Use of a Pharmacophore J1.2.17 Pharmacophore Fingerprints J1.2.18 Pharmacophore Databases J1.2.19 Combination with Other Methods J1.2.20 Combining Pharmacophore and Shape J1.2.21 Structure-Based Pharmacophore Mapping J1.2.22 Structure-Based Pharmacophore vs. Docking J1.2.23 The Ludi Program J1.2.24 LigandScout J1.2.25 Example of Pharmacophore Mapping J1.2.26 Initial Data Sets J1.2.27 Pharmacophore Models J1.2.28 Exploitation of the Pharmacophores Generated J1.2.29 Programs for Pharmacophore Mapping

J1.3. Chemical Information J1.3.1 Molecule Searching J1.3.2 Components of an Information System J1.3.3 Database Query Languages J1.3.4 Quest for Information and Ideas J1.3.5 Quest for Information J1.3.6 Identifying Compounds J1.3.7 Searching by Name J1.3.8 Problems when Searching by Name J1.3.9 Searching by CAS Registry Number J1.3.10 Searching by 2D Molecular Structure J1.3.11 Searching by SMILE String J1.3.12 Searching by Formula J1.3.13 Information Delivered by the Search J1.3.14 Types of Information J1.3.15 Quest for Ideas J1.3.16 Constrained Search J1.3.17 Language to Define Constraints Associated to a Query J1.3.18 Define Constraints for Substituents J1.3.19 Substituent Control by Explicit Hydrogens J1.3.20 Substituent Control by Substitution Numbers J1.3.21 Define Constraints for Atom Types J1.3.22 Define Constraints for Bonds J1.3.23 Define Constraints for Rings J1.3.24 Define Constraints for Stereochemistry J1.3.25 Define Constraints for Tautomers J1.3.26 Define 3D Constraints J1.3.27 Similarity Search J1.3.28 Structural Keys J1.3.29 Example of Similarity Measure J1.3.30 Similar Name J1.3.31 Focused and Diverse Approaches

J1.3.32 Maximizing Knowledge with Information Systems J1.3.33 Filtering Results J1.3.34 Boolean Operations with Different Sets of Hits

J1.4. Data Analysis J1.4.1 Introduction to QSAR Modeling J1.4.2 QSAR Definition J1.4.3 The QSPR/QSAR Problem J1.4.4 SAR Definition J1.4.5 Qualitative Class Assignment of New Chemicals J1.4.6 Three Prerequisites for QSAR Modeling J1.4.7 Classical Hansch Equation J1.4.8 Molecular Descriptors Calculations J1.4.9 Theoretical Molecular Descriptors J1.4.10 Chemometric Approaches to QSAR Modeling J1.4.11 Development of Quantitative Models J1.4.12 Identify the Best Subset of Descriptors J1.4.13 Variable Selection: Independent Variables X J1.4.14 Variable Selection: Dependent Variables Y J1.4.15 Characteristics of QSAR Models J1.4.16 Example of QSAR Model J1.4.17 Chemical Domain of Applicability J1.4.18 Application Domain from Williams plot J1.4.19 Validity Check and Predictivity J1.4.20 Validation Parameters of QSAR Models J1.4.21 Statistic of QSAR Classification Models J1.4.22 Classification Methods J1.4.23 Scheme for Predictive QSAR Modeling J1.4.24 Reversible Decoding of Molecular Descriptors J1.4.25 Interpretation of Molecular Descriptors J1.4.26 Predictive and Descriptive QSAR Models J1.4.27 OECD Principles for QSAR Models J1.4.28 Main Applications of QSAR Predictions

J3. 3D DATABASE SEARCHING

J3.1. What is 3D Searching? J3.1.1 Importance of the 3D J3.1.2 What is 3D Searching? J3.1.3 Components of a 3D Searching Program J3.1.4 3D Database J3.1.5 Search Hypothesis J3.1.6 Converting a Search Hypothesis into a Query J3.1.7 Processing the Query

J3.2. Typical Uses of 3D Searching J3.2.1 Typical Uses of 3D Searching J3.2.2 Test a Pharmacophore Hypothesis J3.2.3 Find Hits that Fit the Volume of Active Molecules J3.2.4 Revealing Bioactive Conformation of a Flexible Molecule J3.2.5 "Lead-Hop" to a New Core J3.2.6 Design a Library for HTS

J3.2.7 Structural Analyses on Experimental 3D Databases J3.2.8 Generate Ideas

J3.3. Types of 3D Searches J3.3.1 Types of 3D Searches J3.3.2 Geometric Searching J3.3.3 Typical Geometric Objects J3.3.4 Typical Properties Considered J3.3.5 Point at an Atom J3.3.6 Centroid J3.3.7 Extension Point J3.3.8 Line J3.3.9 Plane J3.3.10 Geometric Constraints J3.3.11 Distance Constraints J3.3.12 Angle Constraints J3.3.13 Torsion Angle Constraints J3.3.14 Excluded Volumes J3.3.15 Sources of Constraints for 3D Searching J3.3.16 Constraints from a 3D Pharmacophore J3.3.17 Constraints from a Protein Active Site J3.3.18 Constraints from a Bioactive Conformation J3.3.19 Constraints to Probe the Bioactive Conformation J3.3.20 Shape Searching J3.3.21 Bioactive Conformation as a Source of Shape J3.3.22 Ensemble of Active Molecules as a Source of Shape J3.3.23 Active Site as a Source of Shape J3.3.24 Full versus Partial Match J3.3.25 Complex Query Combination

J3.4. Constructing 3D Databases J3.4.1 Constructing 3D Databases J3.4.2 Sources of Compounds for Searching J3.4.3 Database of the Corporate Collection J3.4.4 Databases of Vendor Compounds J3.4.5 Database of Virtual Compounds J3.4.6 Generating 3D Structures J3.4.7 Experimental 3D Structures J3.4.8 Computationally Generated 3D Structures J3.4.9 Cleaning up 2D Input J3.4.10 CONCORD J3.4.11 CORINA J3.4.12 ConFirm and Omega J3.4.13 Information Stored for a Molecule in the Database J3.4.14 Coordinates J3.4.15 Bitmaps or Fingerprints of Typical Search Constraints

J3.5. Programs for 3D Searching J3.5.1 Programs for 3D Searching J3.5.2 ConQuest J3.5.3 CAVEAT J3.5.4 UNITY J3.5.5 ISIS

J3.5.6 Catalyst J3.5.7 FlexS J3.5.8 ROCS

J3.6. CHAPTER QUIZZES (Available only in Teaching Package) J3.6.1 Quiz 1 J3.6.2 Quiz 2 J3.6.3 Quiz 3 J3.6.4 Quiz 4 J3.6.5 Quiz 5 J3.6.6 Quiz 6 J3.6.7 Quiz 7 J3.6.8 Quiz 8 J3.6.9 Quiz 9 J3.6.10 Quiz 10 J3.6.11 Quiz 11 J3.6.12 Quiz 12 J3.6.13 Quiz 13 J3.6.14 Quiz 14 J3.6.15 Quiz 15 J3.6.16 Quiz 16 J3.6.17 Quiz 17 J3.6.18 Quiz 18 J3.6.19 Quiz 19 J3.6.20 Quiz 20 J3.6.21 Quiz 21 J3.6.22 Quiz 22

J4. EXAMPLES OF 3D DATABASE SEARCHING

J4.1. Dopamine Transporter Inhibitors J4.1.1 The Dopamine Transporter Target J4.1.2 Methodology: 3D Database Searching J4.1.3 First Pharmacophore J4.1.4 3D Searching Results with the First Pharmacophore J4.1.5 Piperidinol Hit J4.1.6 Optimization of the Piperidinol Hit J4.1.7 Quinuclidine Hit J4.1.8 Optimization of the Quinuclidine Hit J4.1.9 Phenyl-4 Piperidine Hit J4.1.10 Optimization of the Phenyl-4 Piperidine Hit J4.1.11 Challenging the First Pharmacophore J4.1.12 Structural Analyses of the Quinuclidine Hit J4.1.13 Modeling Analyses: C=O Not Necessary! J4.1.14 Browser Associated to the First Pharmacophore J4.1.15 What Can Be Learned So Far? J4.1.16 Second Pharmacophore J4.1.17 Characteristics of the Second Pharmacophore J4.1.18 3D Searching with the Second Pharmacophore J4.1.19 Optimization of the Pyrrolidine Hit J4.1.20 What Can Be Learned So Far?

J4.1.21 Browser Associated to the Second Pharmacophore J4.1.22 Third Pharmacophore J4.1.23 Bioactive Form of Mazindol J4.1.24 Characteristics of the Third Pharmacophore J4.1.25 3D Searching with Third Pharmacophore J4.1.26 Browser Associated to the Third Pharmacophore J4.1.27 Fourth Pharmacophore J4.1.28 Aligning Low Energy Conformers J4.1.29 Characteristics of the Fourth Pharmacophore J4.1.30 3D Searching with the Fourth Pharmacophore J4.1.31 Optimization of the Substituted Pyridine Hit J4.1.32 Browser Associated to the Fourth Pharmacophore J4.1.33 Summary

J4.2. Non-Sugar Antagonists of Selectin J4.2.1 Reference Compound J4.2.2 Initial SAR Analyses J4.2.3 Pharmacophore Model J4.2.4 Results of 3D Searching J4.2.5 Optimization of the Diphenyl Ether Hit J4.2.6 Summary J4.2.7 Browser of Selectin Antagonists

J4.3. Non-Peptidic Cyclophilin Ligands J4.3.1 Reference Compound: Cyclosporin A J4.3.2 The Bioactive Conformation of Cyclosporin A J4.3.3 Pharmacophore Model J4.3.4 Results of 3D Searching J4.3.5 Superposition of the Hit with Cyclosporin-A J4.3.6 Optimization of Initial Hit J4.3.7 Browser of Non-Peptidic Cyclophilin Ligands

J4.4. Ligands of the Dopamine D3 Receptor J4.4.1 Reference Compounds J4.4.2 Pharmacophore Model J4.4.3 Model of the Dopamine D3 Receptor J4.4.4 Combined Pharmacophore and Structure-Based Searching J4.4.5 Results of 3D Searching J4.4.6 Summary J4.4.7 Browser of Dopamine D3 Receptor Ligands

J4.5. Inhibitors of HIV-1 Protease J4.5.1 HIV-1 Protease Inhibition J4.5.2 The Peptide Problem J4.5.3 Database Searching for Non-Peptidic Scaffolds J4.5.4 The Terphenyl Derivative Hit J4.5.5 Analysis of the Content of the Hit J4.5.6 Design of Cyclic Urea Scaffold J4.5.7 XK-263 is a Non-Peptidic Mimic of A-77003 J4.5.8 Summary

J5. MOLECULAR SIMILARITY

J5.1. Introduction J5.1.1 Similarity and Complementarity-Based Drug Design J5.1.2 Comparing Molecules: a Central Issue in Drug Discovery J5.1.3 The Molecular Similarity Principle J5.1.4 Subjectivity of the Similarity Concept J5.1.5 What can be Similar in Molecules? J5.1.6 2D-Structure Similarity J5.1.7 Shape Similarity J5.1.8 Surface Physicochemical Similarity J5.1.9 H-Bond Similarity J5.1.10 Absence of Particular Features J5.1.11 Pharmacophore Similarity J5.1.12 Comparing Molecular Characteristics J5.1.13 Terminology: Similarity Attributes J5.1.14 Relevant Characteristics: What is Important? J5.1.15 Relativity of Relevant Properties J5.1.16 Interpretable Characteristics J5.1.17 Global and Local Characteristics J5.1.18 Maximizing Similarity: Object Alignments J5.1.19 The Psychology of Similarity J5.1.20 Molecular Similarity in Medicinal Chemistry Era J5.1.21 Cheminformatics

J5.2. Medicinal Chemistry Approaches Based on the Similarity Principle J5.2.1 Chemical Modifications J5.2.2 Bioisosteric Replacements J5.2.3 Molecular Mimicry J5.2.4 Mee-too-ism J5.2.5 Peptidomimetics J5.2.6 Lead-Like and Drug-Like Approaches

J5.3. Similarity Searching in Database J5.3.1 Exact and Substructure Searching J5.3.2 Similarity Searching J5.3.3 Semi-Manual Similarity Searching J5.3.4 Similarity Concept and Creativity J5.3.5 Output of Similarity Searching J5.3.6 Broad Range of Applications J5.3.7 Substructure & Similarity Searching Complementarities J5.3.8 General Requirements of a Method J5.3.9 Make Molecules Accessible to the Computer J5.3.10 Need of Methods to Measure Similarity J5.3.11 Apply an Algorithm

J5.4. Molecular Descriptors: Make Molecules Accessible to the Computer J5.4.1 The Concept of "Molecular Descriptors" J5.4.2 Selection of Relevant Descriptors J5.4.3 High-Dimensionality Space of the Molecular Descriptors J5.4.4 Example of Selection of Relevant Descriptors J5.4.5 Binary and Numerical Descriptors J5.4.6 Experimental and Calculated Molecular Descriptors J5.4.7 Predefined vs. Algorithmically Defined Descriptors J5.4.8 Possible Classification of Molecular Descriptors

J5.5. Examples of Molecular Descriptors J5.5.1 1D Descriptors: Single Numbers or Sequences J5.5.2 Topological Indices J5.5.3 Electrotopological Descriptors J5.5.4 Linear Representations of Molecules J5.5.5 2D Descriptors: Fragments and Substructures J5.5.6 Spectra-Derived Descriptors J5.5.7 Graph-Based Multiple Point Pharmacophores J5.5.8 Reduced Graph and Feature Trees J5.5.9 Ghose and Crippen Descriptors J5.5.10 3D Descriptors J5.5.11 Field-Based Descriptors J5.5.12 Multiple-Point Pharmacophores J5.5.13 Surface-Based Descriptors J5.5.14 4D Chirality Descriptors J5.5.15 Virtual Affinity Fingerprints J5.5.16 BCUT Descriptors

J5.6. Comparing Molecules: Similarity Coefficients J5.6.1 Methods to Quantify Similarity J5.6.2 Similarity Coefficients of Relevant Properties J5.6.3 Binary and Distance-Based Formulas J5.6.4 Distance Coefficients J5.6.5 Similarity Coefficients J5.6.6 Symmetry Problems in Similarity Analysis J5.6.7 Symmetrical vs. Asymmetrical Similarity in Psychology J5.6.8 Does the Absence of Features Indicate Similarity? J5.6.9 Examples of Similarity and Distance Coefficients J5.6.10 The Tanimoto Coefficient J5.6.11 Dice and Cosine Similarity Coefficients J5.6.12 Tversky Similarity Coefficient J5.6.13 Some Common Distance Coefficients

J5.7. Examples of Direct Use of Similarity Coefficients J5.7.1 Searching Molecules with Similar Properties J5.7.2 Searching Information from Similar Molecules J5.7.3 Knowing a Pharmacophore, Search for Novel Molecules J5.7.4 Example of a Fuzzy Pharmacophore J5.7.5 Validation of Novelty J5.7.6 Reducing a Virtual Library to a Practical Size J5.7.7 Peptidomimetics J5.7.8 Compounds that Fit the Shape of an Active Site J5.7.9 Find a Synthetic Route J5.7.10 Filtering Undesired Hits J5.7.11 Clustering of Molecules

J5.8. Development of Computational Models J5.8.1 Development of a Structure-Property Model J5.8.2 Deriving Knowledge from Distances and Properties J5.8.3 Molecules in the Space of the Descriptors J5.8.4 QSAR and 3D-QSAR J5.8.5 QSPR - Quantitative Structure-Property Relationships J5.8.6 Intelligent Machine Learning Models

J5.8.7 Binary Kernel Discrimination J5.8.8 Artificial Neural Networks J5.8.9 Support Vector Machines (SVMs) J5.8.10 Binary QSAR and Naive Bayes Classifier J5.8.11 Rule-Based Approaches J5.8.12 Decision Trees

J5.9. Practical Applications of Structure-Property Models J5.9.1 Example of a 3D-QSAR Model J5.9.2 Molecular Similarity: Models of ADME/Tox Predictions J5.9.3 'A' - Absorption: Does a Drug Work Orally? J5.9.4 'D' - Distribution: Where Does the Drug Go in the Body? J5.9.5 'M' - Metabolism: The Drug's Fate J5.9.6 'E' - Elimination: The Drug Says Good-Bye J5.9.7 'Tox' - Toxicity: Side-Effects J5.9.8 Prediction of Solubility J5.9.9 Prediction of Melting Points

J5.10. Important Properties of Molecular Descriptors and Similarity Coefficients J5.10.1 Neighborhood Behavior J5.10.2 Back-Projectability J5.10.3 Validation and Information Content of Descriptors J5.10.4 Properties of Binary Fingerprints J5.10.5 Folding of Fingerprints J5.10.6 The Concept of Binning J5.10.7 The Concept of "Fuzzy" Descriptors J5.10.8 Size-Bias of the Tanimoto Similarity Coefficient J5.10.9 Size-Bias: Favoring Large Molecules J5.10.10 2D vs. 3D Descriptors

J5.11. Choice of the Best Method for Calculating Similarity Coefficients J5.11.1 Unique Content of Each Similarity Coefficient? J5.11.2 Clustering Similarity Coefficients J5.11.3 Consensus Scoring: Asking a Panel of Experts J5.11.4 Why Does Consensus Scoring Improve the Results? J5.11.5 What Algorithms Exist for Consensus Scoring?

J5.12. Limitations of the Concept of "Molecular Similarity" J5.12.1 Limitation of Ligand-Based Approaches J5.12.2 Example of Ligand-Based Approach Limitation J5.12.3 Limitation Due to Extrapolations J5.12.4 Limitation Due to Pitfalls in interpolations J5.12.5 Principle of Continuity J5.12.6 Discontinuity in Molecular Recognition J5.12.7 Bumps J5.12.8 Ligand Conformational Change J5.12.9 Receptor Conformational Changes J5.12.10 Flip in Binding Mode J5.12.11 Discontinuity in Ligand Property J5.12.12 pKa J5.12.13 LogP J5.12.14 Discontinuity in the Function of the Receptor

J5.13. Conclusions

J5.13.1 How Does "Molecular Similarity" Fare Today? J5.13.2 How Many Chances of Being Active? J5.13.3 Economic Rationale of Similarity-Based Methods J5.13.4 Perspectives

J5.14. CHAPTER QUIZZES (Available only in Teaching Package) J5.14.1 Quiz 1 J5.14.2 Quiz 2 J5.14.3 Quiz 3 J5.14.4 Quiz 4 J5.14.5 Quiz 5 J5.14.6 Quiz 6 J5.14.7 Quiz 7 J5.14.8 Quiz 8 J5.14.9 Quiz 9 J5.14.10 Quiz 10 J5.14.11 Quiz 11 J5.14.12 Quiz 12 J5.14.13 Quiz 13 J5.14.14 Quiz 14 J5.14.15 Quiz 15 J5.14.16 Quiz 16 J5.14.17 Quiz 17 J5.14.18 Quiz 18 J5.14.19 Quiz 19 J5.14.20 Quiz 20 J5.14.21 Quiz 21 J5.14.22 Quiz 22 J5.14.23 Quiz 23 J5.14.24 Quiz 24 J5.14.25 Quiz 25 J5.14.26 Quiz 26 J5.14.27 Quiz 27 J5.14.28 Quiz 28 J5.14.29 Quiz 29 J5.14.30 Quiz 30 J5.14.31 Quiz 31 J5.14.32 Quiz 32 J5.14.33 Quiz 33 J5.14.34 Quiz 34 J5.14.35 Quiz 35 J5.14.36 Quiz 36 J5.14.37 Quiz 37 J5.14.38 Quiz 38 J5.14.39 Quiz 39 J5.14.40 Quiz 40 J5.14.41 Quiz 41 J5.14.42 Quiz 42 J5.14.43 Quiz 43 J5.14.44 Quiz 44 J5.14.45 Quiz 45 J5.14.46 Quiz 46

J5.14.47 Quiz 47 J5.14.48 Quiz 48 J5.14.49 Quiz 49 J5.14.50 Quiz 50 J5.14.51 Quiz 51 J5.14.52 Quiz 52 J5.14.53 Quiz 53 J5.14.54 Quiz 54 J5.14.55 Quiz 55 J5.14.56 Quiz 56 J5.14.57 Quiz 57 J5.14.58 Quiz 58 J5.14.59 Quiz 59 J5.14.60 Quiz 60 J5.14.61 Quiz 61 J5.14.62 Quiz 62 J5.14.63 Quiz 63 J5.14.64 Quiz 64 J5.14.65 Quiz 65 J5.14.66 Quiz 66 J5.14.67 Quiz 67 J5.14.68 Quiz 68 J5.14.69 Quiz 69 J5.14.70 Quiz 70 J5.14.71 Quiz 71 J5.14.72 Quiz 72 J5.14.73 Quiz 73 J5.14.74 Quiz 74 J5.14.75 Quiz 75 J5.14.76 Quiz 76 J5.14.77 Quiz 77 J5.14.78 Quiz 78 J5.14.79 Quiz 79 J5.14.80 Quiz 80 J5.14.81 Quiz 81 J5.14.82 Quiz 82 J5.14.83 Quiz 83 J5.14.84 Quiz 84 J5.14.85 Quiz 85 J5.14.86 Quiz 86 J5.14.87 Quiz 87 J5.14.88 Quiz 88

K. GENERAL TOPICS

K1. GENERAL INTRODUCTION ON DRUGS

K1.1. What is a Drug K1.1.1 What is a Drug? K1.1.2 Improvement of Life Expectancy

K1.1.3 Origin of Active Principles K1.1.4 Drug Formulation K1.1.5 Multiple Names of Drugs K1.1.6 Example of Multiple Names of a Drug K1.1.7 Requirements for the Ideal Drug K1.1.8 Safety K1.1.9 Properties K1.1.10 Compliance K1.1.11 Pharmacology K1.1.12 Metabolism and ADME K1.1.13 Side Effects and Toxicity

K1.2. The Pharmaceutical Industry K1.2.1 Drug Discovery and Development, a Long Process K1.2.2 Drug Discovery and Drug Development K1.2.3 One Million Studied for One to Reach the Market K1.2.4 Pharmaceutical R&D, a High-Risk Undertaking K1.2.5 The Time of Developing a New Drug K1.2.6 The Cost of Developing a New Drug K1.2.7 Reasons for Termination of Development

K1.3. Industry Focus Area K1.3.1 Industry Focus Areas and Examples of Useful Drugs K1.3.2 Cardiovascular System (CVS) K1.3.3 Antiarrhytmics K1.3.4 Antihypertensive K1.3.5 Vasodilatation K1.3.6 Anticoagulants K1.3.7 Antihyperlipidemic K1.3.8 Anti-infective Agents K1.3.9 Antibiotics K1.3.10 Antiviral K1.3.11 Antifungals K1.3.12 Antimalarias K1.3.13 Antituberculosis K1.3.14 Central Nervous System (CNS) Agents K1.3.15 Antipsychotics K1.3.16 Cholinergic K1.3.17 Parkinsonians K1.3.18 Anticonvulsants K1.3.19 Antidepressants K1.3.20 Tranquilizers K1.3.21 Adrenergic K1.3.22 Gastro-Intestinal Drugs K1.3.23 Antidiarrhea K1.3.24 Laxatives K1.3.25 Anti-emetics K1.3.26 Anti-Ulcers K1.3.27 Anti-Neoplastic (Anti Cancer) Agents K1.3.28 Alkylating K1.3.29 Antimetabolites K1.3.30 Anti-neoplastic

K1.3.31 Immunosuppressants K1.3.32 Taxoids K1.3.33 Respiratory Agents K1.3.34 Bronchodilators K1.3.35 Antihistamines K1.3.36 Antitussives K1.3.37 Anti-Rheumatism and Pain Agents K1.3.38 Anti-inflammatory K1.3.39 Anti-rheumatism K1.3.40 Analgesics K1.3.41 Anesthetics K1.3.42 Agents Against Metabolic Disorders K1.3.43 Antidiabetic K1.3.44 Antiosteoporotic K1.3.45 Thyroid Hormone K1.3.46 Steroids K1.3.47 Diagnostic Agents

K1.4. CHAPTER QUIZZES (Available only in Teaching Package) K1.4.1 Quiz 1 K1.4.2 Quiz 2 K1.4.3 Quiz 3 K1.4.4 Quiz 4 K1.4.5 Quiz 5 K1.4.6 Quiz 6 K1.4.7 Quiz 7 K1.4.8 Quiz 8 K1.4.9 Quiz 9 K1.4.10 Quiz 10 K1.4.11 Quiz 11 K1.4.12 Quiz 12 K1.4.13 Quiz 13 K1.4.14 Quiz 14 K1.4.15 Quiz 15 K1.4.16 Quiz 16 K1.4.17 Quiz 17 K1.4.18 Quiz 18 K1.4.19 Quiz 19 K1.4.20 Quiz 20 K1.4.21 Quiz 21 K1.4.22 Quiz 22 K1.4.23 Quiz 23 K1.4.24 Quiz 24 K1.4.25 Quiz 25 K1.4.26 Quiz 26 K1.4.27 Quiz 27 K1.4.28 Quiz 28 K1.4.29 Quiz 29 K1.4.30 Quiz 30 K1.4.31 Quiz 31 K1.4.32 Quiz 32 K1.4.33 Quiz 33

K1.4.34 Quiz 34 K1.4.35 Quiz 35 K1.4.36 Quiz 36 K1.4.37 Quiz 37 K1.4.38 Quiz 38 K1.4.39 Quiz 39 K1.4.40 Quiz 40 K1.4.41 Quiz 41 K1.4.42 Quiz 42 K1.4.43 Quiz 43 K1.4.44 Quiz 44 K1.4.45 Quiz 45 K1.4.46 Quiz 46 K1.4.47 Quiz 47 K1.4.48 Quiz 48 K1.4.49 Quiz 49 K1.4.50 Quiz 50 K1.4.51 Quiz 51 K1.4.52 Quiz 52 K1.4.53 Quiz 53 K1.4.54 Quiz 54 K1.4.55 Quiz 55 K1.4.56 Quiz 56 K1.4.57 Quiz 57 K1.4.58 Quiz 58 K1.4.59 Quiz 59 K1.4.60 Quiz 60 K1.4.61 Quiz 61 K1.4.62 Quiz 62 K1.4.63 Quiz 63 K1.4.64 Quiz 64 K1.4.65 Quiz 65 K1.4.66 Quiz 66 K1.4.67 Quiz 67 K1.4.68 Quiz 68 K1.4.69 Quiz 69 K1.4.70 Quiz 70 K1.4.71 Quiz 71 K1.4.72 Quiz 72 K1.4.73 Quiz 73 K1.4.74 Quiz 74 K1.4.75 Quiz 75 K1.4.76 Quiz 76 K1.4.77 Quiz 77 K1.4.78 Quiz 78 K1.4.79 Quiz 79 K1.4.80 Quiz 80 K1.4.81 Quiz 81 K1.4.82 Quiz 82 K1.4.83 Quiz 83 K1.4.84 Quiz 84

K1.4.85 Quiz 85

K2. DRUG DISCOVERY

K2.1. Introduction K2.1.1 Drug Discovery K2.1.2 Target Identification K2.1.3 Lead Discovery K2.1.4 Lead Optimization K2.1.5 Disciplines Involved in Drug Discovery

K2.2. Discovery Methods K2.2.1 How Are Leads Discovered?

K2.3. Serendipity K2.3.1 The Serendipitous Pathway K2.3.2 Penicillin K2.3.3 Aspirin K2.3.4 Glafenine K2.3.5 Furosemide K2.3.6 Chlorpromazine K2.3.7 Cyclosporin A K2.3.8 Viagra

K2.4. Screening K2.4.1 The Screening Pathway K2.4.2 Example of Molecules Discovered by Screening

K2.5. Chemical Modification K2.5.1 The Chemical Modification Pathway K2.5.2 Tagamet K2.5.3 Beta-Blockers K2.5.4 Limitation of the Chemical Modification Approach

K2.6. Rational Drug Design K2.6.1 The Rational Pathway K2.6.2 Captopril Story K2.6.3 Cimetidine Story K2.6.4 Advantages of Rational Drug Design

K2.7. Chemistry in Drug Discovery K2.7.1 Chemistry in Drug Discovery K2.7.2 Synthesis of Complicated Molecules K2.7.3 Penicillin K2.7.4 Taxol K2.7.5 Steroid K2.7.6 Three Methods in Synthetic Chemistry K2.7.7 Classical K2.7.8 Parallel K2.7.9 Combinatorial K2.7.10 Chemistry in Lead Discovery K2.7.11 Protein Kinase Example K2.7.12 Chemistry in Lead Optimization K2.7.13 Optimization of the Gleevec Series

K2.7.14 CCK-A Receptor Antagonist Example K2.7.15 Chemistry in Drug Development

K2.8. Patents K2.8.1 Intellectual Property and Patents K2.8.2 What Can be Patented? K2.8.3 Requirements for Patentability K2.8.4 Lifetime of a Patent K2.8.5 Effective Patent Lifetime K2.8.6 Patent Protection

K2.9. CHAPTER QUIZZES (Available only in Teaching Package) K2.9.1 Quiz 1 K2.9.2 Quiz 2 K2.9.3 Quiz 3 K2.9.4 Quiz 4 K2.9.5 Quiz 5 K2.9.6 Quiz 6 K2.9.7 Quiz 7 K2.9.8 Quiz 8 K2.9.9 Quiz 9 K2.9.10 Quiz 10 K2.9.11 Quiz 11 K2.9.12 Quiz 12 K2.9.13 Quiz 13 K2.9.14 Quiz 14 K2.9.15 Quiz 15 K2.9.16 Quiz 16 K2.9.17 Quiz 17 K2.9.18 Quiz 18 K2.9.19 Quiz 19 K2.9.20 Quiz 20 K2.9.21 Quiz 21 K2.9.22 Quiz 22 K2.9.23 Quiz 23 K2.9.24 Quiz 24 K2.9.25 Quiz 25 K2.9.26 Quiz 26 K2.9.27 Quiz 27

K3. DRUG DEVELOPMENT

K3.1. Introduction K3.1.1 Drug Development K3.1.2 Pipe-Line of Development K3.1.3 Pre-Clinical Development K3.1.4 Clinical Development K3.1.5 Post-marketing Surveillance K3.1.6 Disciplines Involved in Drug Development K3.1.7 Effective Teams: Interactivity and Cooperativity

K3.2. The Pre-Clinical Studies K3.2.1 Pre-Clinical Studies

K3.2.2 Chemical Development K3.2.3 Pharmacological Studies K3.2.4 Drug Metabolism and Pharmacokinetics K3.2.5 Toxicology Studies K3.2.6 Safety Studies K3.2.7 Carcinogenicity K3.2.8 Mutagenicity K3.2.9 Reproduction Studies K3.2.10 Formulation Development K3.2.11 Stability Tests K3.2.12 Disciplines Involved in Pre-Clinical Development

K3.3. Clinical Development K3.3.1 Introduction on Clinical Trials K3.3.2 Clinical Trials Phase 1 K3.3.3 Clinical Trials Phase 2 K3.3.4 Clinical Trials Phase 3 K3.3.5 Clinical Trials Phase 4 K3.3.6 Disciplines Involved in Drug Development

K3.4. Regulatory Affairs K3.4.1 The Role of the Food and Drug Administration (FDA) K3.4.2 The Investigational New Drug Application (IND) K3.4.3 The New Drug Application (NDA) K3.4.4 The Regulatory Approval Process

K3.5. CHAPTER QUIZZES (Available only in Teaching Package) K3.5.1 Quiz 1 K3.5.2 Quiz 2 K3.5.3 Quiz 3 K3.5.4 Quiz 4 K3.5.5 Quiz 5 K3.5.6 Quiz 6 K3.5.7 Quiz 7 K3.5.8 Quiz 8 K3.5.9 Quiz 9 K3.5.10 Quiz 10 K3.5.11 Quiz 11 K3.5.12 Quiz 12 K3.5.13 Quiz 13 K3.5.14 Quiz 14 K3.5.15 Quiz 15 K3.5.16 Quiz 16 K3.5.17 Quiz 17 K3.5.18 Quiz 18 K3.5.19 Quiz 19 K3.5.20 Quiz 20 K3.5.21 Quiz 21 K3.5.22 Quiz 22 K3.5.23 Quiz 23 K3.5.24 Quiz 24 K3.5.25 Quiz 25 K3.5.26 Quiz 26

K3.5.27 Quiz 27 K3.5.28 Quiz 28 K3.5.29 Quiz 29 K3.5.30 Quiz 30 K3.5.31 Quiz 31 K3.5.32 Quiz 32 K3.5.33 Quiz 33 K3.5.34 Quiz 34 K3.5.35 Quiz 35 K3.5.36 Quiz 36 K3.5.37 Quiz 37 K3.5.38 Quiz 38 K3.5.39 Quiz 39 K3.5.40 Quiz 40 K3.5.41 Quiz 41 K3.5.42 Quiz 42 K3.5.43 Quiz 43 K3.5.44 Quiz 44 K3.5.45 Quiz 45

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