genomics proteo mics based drug development and process

7/29/2019 Genomics Proteo Mics Based Drug Development and Process

1/35

20/03/2008 Dept.of Pharmaceutics 1

Genomics & Proteomics Based

Drug DISCOVERY

Dr. Basavaraj K. Nanjwade M.Pharm., Ph. D

Associate ProfessorDepartment of Pharmaceutics

KLE University

BELGAUM 590010


2/35


Genomics

Genetic scientist isolate individual

genes and determine their chemical

composition, and ultimately to sequence

entire genomes.

The sequencing of the human genome

with the human genome project


3/35


Genome Sequencing Gene number, exact locations, and functions

Gene regulation

DNA sequence organization

Chromosomal structure and organization

Noncoding DNA types, amount, distribution, information content,and functions

Coordination of gene expression, protein synthesis, and post-translational events

Interaction of proteins in complex molecular machines

Predicted vs experimentally determined gene function


4/35


Genome Sequencing

Evolutionary conservation among organisms

Protein conservation (structure and function)

Proteomes (total protein content and function) in organisms

Correlation of SNPs (Single nucleotide polymorphisms ) with health anddisease

Disease-susceptibility prediction based on gene sequence variation

Genes involved in complex traits and multigene diseases

Complex systems biology including microbial consortia useful forenvironmental restoration

Developmental genetics, genomics


5/35


Genome Sequencing

C = Cytosine, G = Guanine, A = Adenine and T = Thymine


6/35


SBI* can be used to examine: drug targets (usually proteins)

binding ofligands

rational drug design

(benefits = saved time and RsRsRs)

Drug Discovery

* SBI-Structural Bioinformatics


7/35


Whats different?

Drug discovery process beginswith a disease(rather than a treatment)

Use disease model to pinpoint relevantgenetic/biological components (i.e.

possible drug targets)

Modern Drug Discovery


8/35



disease genetic/biological target

discovery of a lead molecule- design assay to measure function oftarget

- use assay to look for modulators oftargets function

high throughput screen (HTS)

- to identify hits


9/35



small molecule hits

manipulate structure to increase potency

*optimization of lead molecule intocandidate drug*

fulfillment of required pharmacological properties:

potency, absorption, bioavailability, metabolism, safety

clinical trials


10/35


Interesting facts...

Over 90% of drugsentering clinicaltrials fail to make

it to market

The average costto bring a newdrug to market isestimated at $770million


11/35


Relating druggable targetsto disease...

GPCR

STY kinases

Zinc peptidases

Serine

proteases

PDE

Other 110families

Cys proteases

Gated ion-

channelIon channels

Nuclear

receptor

P450 enzymes

Analysis of Pharmindustry reveals:

Over 400 proteins used

as drug targets Sequence analysis of

these proteins showsthat most targets fallwithin a few major

gene families (GPCRs,kinases, proteases andpeptidases)


12/35


Assessing Target Druggability

Once a target is defined for yourdisease of interest, SBI can helpanswer the question:

Is this a druggable target?

Does it have sequence/domains similar to

known targets?Does the target have a site where a drug

can bind, and with appropriate affinity?


13/35


Genome Annotation and Analysis


14/35


Impact of Structural Bioinformatics

on Drug Discovery

Genome Gene Protein HTS Hit Lead Candidate DrugGenomics

BioinformaticsStructural Bioinformatics

ChemoinformaticsStructure-based Drug Design

ADMET Modelling. Speeds up key steps in

DD process by combiningaspects of bioinformatics,

structural biology, and

structure-based drug

design


15/35


human genomepolysaccharides lipids nucleic acids proteins

Problems with toxicity, specificity, and

difficulty in creating potent inhibitors

eliminate the first 3 categories...


16/35


human genome

polysaccharides lipids nucleic acids proteins

proteins withbinding site

druggable genome = subset of genes which

express proteins capable of binding small drug-like

molecules


17/35


Proteomics Proteomics studies networks of proteins by measuring,

among other things, protein expression.

Protein activity is regulated by post-translationalmodification and degradation; these cannot yet bepredicted from DNA sequence.

Proteomics measures protein expression directly, not viagene expression, thus achieving better accuracy.Current work uses 2-dimensional polyacrylamide gel

electrophoresis (2D-PAGE) and mass spectrometry.

New separation and characterization technologies, suchas protein microarrays and high-throughputchromatography, are being developed


18/35


Proteomics


19/35


Process Flow Chart of Proteomics

(Image) analysis(Data massage, Evaluation)

Spot identification

(Mass spectrometry)

Biomarkers

(Principal compound analysis)

Two dimensional gel electrophoresis


20/35


Proteomics in Drug Discovery

As we have seen genomics has dramatically altered theway drug discovery is now being viewed.

However, there may not be a good correlation betweengene expression and protein expression as most diseaseprocesses and treatments are manifest at the proteinlevel.

It is believed that gene-based expression analysis alonewill be totally inadequate for drug discovery.


21/35


Proteomics is Drug Discovery

Proteomics has unique and significant

advantages as an important complement

to a genomics approach.

1. Target/marker identification

2. Target validation/toxicology


22/35


Target/marker identification

This application of proteomics provides a

protein profile of a cell, tissue and/or bodily

fluids that can be used to compare a

healthy with a diseased state for proteindifferences in the search for drugs or drug

targets.


23/35


Target validation/toxicology

Proteomics can be applied as an assay procedure forthe potential utility of drug candidates.

This can be achieved by a comparative analysis of

reference protein profiles from normal or diseased stateswith profiles after drug treatment (Wang 1999).

Proteomics technology can also be integrated with

combinatorial chemistry to evaluate comparativestructure-activity relationships of drug analogs.


24/35


Protein-Ligand Docking

Starting orientation of the program with 2 water molecules as the Protein

and Ligand (a useful setup for testing the application). The energy of the

system is in J/mol.


25/35



Independent control of both molecules is allowed. The leftmost

molecule is rotated using a trackball style rotation, while the second

molecule remains fixed.


26/35



From the previous figure, the second molecule has been

independently translated up and away from the first molecule.

Molecules can be arbitrarily positioned and oriented in 3D


27/35



This is the same setup as the previous figure, except the viewpoint has been

rotated, translated and zoomed to a different location. The energy of the system

remains the same as the molecules are physically unmoved relative to each other


28/35



The two oxygen atoms are just overlapping and consequently the energy of the

system takes on a large negative value indicating a VERY high energy (the energy

well is reversed for the purpose of the program, so large positive values indicate a

favourable conformation, and large negative values indicate unfavourable

conformations


29/35



Here the atoms are at an optimum distance for the van der Waals

Forces to hit the minimum of the well potential. However, the atoms

are not aligned for any dipole-dipole interaction or hydrogen bonding


30/35



The energy of the system attains a maximum with the following

orientation. This is the orientation that occurs between water

molecules when ice forms. This puts the hydrogen bond in its

optimum orientation, and this changes makes another order of

magnitude difference in the energy of the system


31/35


Structure being the key to function, determining aproteins structure is a key step toward elucidating itsrole.

The subfield of protein-ligand docking is useful in rationaldrug design.

Laboratory prediction is time consuming and expensive,so researchers have been working on computerized

prediction for several decades.

Exact computational prediction is difficult butsophisticated algorithms to find approximate solutionscontinue to be developed.



32/35


Critical Assessment of Methods of Protein

Structure Prediction

Computational groups predict structures ofproteins whose structures have been found in thelaboratory before the latter results are released.

Tools are Classified

1. Comparative modeling looks for amino acid similarity toproteins of known structure.

2. Fold recognition predicts folds in regions that do notshare amino acid similarity with known structures


33/35


Advantages

More Powerful Medicines

Better, Safer Drugs the First Time

More Accurate Methods of Determining Appropriate Drug

Dosages

Advanced Screening for Disease

Better Vaccines

Improvements in the Drug Discovery and Approval Process

Decrease in the Overall Cost of Health Care


34/35


Disadvantages

Complexity of finding gene variations thataffect drug response

Limited drug alternatives

Disincentives for drug companies to make

multiple pharmacogenomic products

Educating healthcare providers


35/35

20/03/2008 Dept of Pharmaceutics 35

THANK YOUE-mail: [email protected]

genomics proteo mics based drug development and process

Documents