evotec ag, 5 th joint sheffield conference on chemoinformatics , july 2010

Evotec AG, 5th Joint Sheffield Conference on Chemoinformatics, July 2010

Investigation of CDK2 Inhibitor Potency using Electrostatic Potential Complementarity and the Fragment Molecular Orbital Method

Creating high-value drug discovery innovation alliances

Overview

· Molecular Shape and Electrostatic Considerations in Ligand Binding· Case Study: Cyclin-Dependent Kinase 2 (CDK2)

· Understanding Complex Interactions During H2L/F2L/LO· The Fragment Molecular Orbital (FMO) Method· Application of FMO Calculations

Classical Lock and Key Problem

Ligand “Keys” Receptor “Lock”

· What is required to effectively describe protein::ligand interactions?· Ligand and receptor features to consider:

· Shape· Charge and electrostatic potential· Dynamics

“Everything should be made as simple as possible, but not simpler.” - Einstein

Scoring Ligand Shape and Electrostatic PotentialTanimoto Coefficient

A B

IA IBOAB

How similar are these?

· Tanimoto coefficient is widely used to compare chemical similarities

· Gaussian Tanimoto compares ligand shapes in 3D· Electrostatic Tanimoto (TES) is calculated in the similar manner

as for Gaussian Tanimoto but an electrostatic field overlap is used instead of volume overlap1

· Implemented in MOE2 and is high throughput (10,000s cmpds)

Tanimoto = 1 = A and B are identical

1) Jennings and Tennant, J. Chem. Inf. Model. 47, 1829-1838, 20072) MOE (The Molecular Operating Environment) http://www.chemcomp.com

Ligand-Based Shape and Electrostatic Potential Calculations

· Gaussian Tanimoto is a fast shape comparison application, based on the idea that molecules have similar shape if their volumes overlap well and any volume mismatch is a measure of dissimilarity

· Used as a virtual screening tool which can rapidly identify potentially active compounds with a similar shape to a known hit or lead compound

· TES score is sensitive to subtle changes in ligand electrostatics· Semi-empirical atomic charges using AM1-BCC is recommended 1,2

AM1-BCC is parameterized for good correlation with HF 6-31G* charges 3

Gauss = 1.00TES = 1.00

Gauss = 0.97TES = 0.40

Gauss = 0.99TES = 0.64

Gauss = 0.97TES = 0.54

1) Tsai et al., Bioorg. Med. Chem. Lett., 18, 3509-3512, 20082) Jennings and Tennant, J. Chem. Inf. Model. 47, 1829-1838, 20073) Balyl, et al., J. Comput. Chem., 132-146, 132, 2000

1) P. G. Wyatt et al., J. Med. Chem. 51, 4986-4999, 20082) M. Congreve et al., J. Med. Chem. 51, 3661-3680, 2008

Case Study: CDK2

· Can ligands be effectively represented and compared using measures of shape and electrostatics?

· Case example taken from the literature.1,2 CDK2 fragment-based screened identified a number of hits. 28 ligands taken from this work were examined.

· Pharmacological inhibitors of cyclin-dependent kinases (CDKs) are currently being evaluated for therapeutic use against cancer and neurodegenerative disorders amongst many other diseases.

Astex AT7519 (CDK2 inhibitor) as an example

2VU3323130

2VTT2VTQ

27262524

2VTP2VTO

212019

2VTN1716

2VTL2VTI

132VTS2VTR2VTJ

92VTM2VTH2VTA

2VTA

2VTH

2VTM 92VT

J2VT

R2VT

S 132VTI2VT

L 16 172VTN 19 20 212VT

O2VT

P 24 25 26 272VTQ

2VTT 30 31 32 2V

U3

Gaussian Tanimoto

3nM

Fragment Hit Clinical Candidate

AT7519

Hit

GaussianTanimoto

Coefficient

Based on CDK2-Bound Alignment

0.0

1.5

4.0

Absolute Difference in pIC50

3nM

AT7519


Hit

AbsoluteDifference

In pIC50

2VU3323130

2VTT2VTQ

27262524

2VTP2VTO

212019

2VTN1716

2VTL2VTI

132VTS2VTR2VTJ

92VTM2VTH2VTA

2VTA

2VTH

2VTM 92VT

J2VT

R2VT

S 132VTI2VT

L 16 172VTN 19 20 212VT

O2VT

P 24 25 26 272VTQ

2VTT 30 31 32 2V

U3

Electrostatic Tanimoto - TES

3nM

AT7519


Hit

ElectrostaticTanimoto

Coefficient

Based on CDK2-Bound Alignment

2VU3 AT7519, 47nM

Case Study: CDK2Optimisation of Shape and Electrostatics

Which interactions are the most important?

What happens when you have a complicated interaction that requires better understanding?

PAGE 101) Chau, P-L., and Dean, P.M., J. Comput.-Aided Mol. Design., 8, 513-525, 1994

Understanding Complex Interactions during H2L/F2L/LO

Multiple equivalent binding modes

Interactions not represented in docking/MM forcefields

“Defragmentation” of large ligands to determine group efficiency

Which interactions are the most important?

What happens when you have a complicated interaction that requires better understanding?

More complex methods required – e.g., free energy and/or quantum mechanical calculations

PAGE 11

Fragment Molecular Orbital (FMO) MethodMethod and throughput

Calculations for systems with 200-300 atoms are routinely ran at Evotec

(~10/day ) using MP2 / 6-31G* , 6-31G(3df,3pd) for Cl and S

PIE (Pair Interaction Energy)

Fragmentation of peptide

· Full quantum computation of protein::ligand complexes has been practically impossible until recently due to extremely large resources required for computing

· The fragment molecular orbital method1 (FMO) was proposed by K. Kitaura and co-workers– Highly suitable for calculation of large (biological)

systems in parallel computing environment2,3

– Implemented in GAMESS QM suite– PIEDA4,5 (Pair interaction energy decomposition

analysis) provides detailed ligand/protein interaction information

4) Fedorov, D. G., and Kitaura, K., J. Comput. Chem., 28, 222-237, 20075) Nakano et al., Chem. Phys. Lett., 351, 475-480, 2002

1) Kitara et al., Chem. Phys. Lett., 313, 701-706, 19992) Komeiji et al., Comput. Biol. Chem., 28, 155-161, 20043) Fedorov et al., J. Comput. Chem., 25, 872-880, 2004

The Cl-p Interaction in a Protein::Ligand Complex

· Cl-p interaction is an attractive interaction, where the major source of attraction is the dispersion force

· Calculated interaction energy is 2-3 kcal/mol depending on the chloro species

· Optimal distance is ca. 3.6 Å

· HF interaction is repulsive

· Electron correlation method, such as MP2, needed to probe the interaction accurately

· For example – serine protease inhibitor series1

Distance (Å)

Ene

rgy

(kca

l/mol

)

4.0 5.03.0-3

0

3

HF/6-311G++(3df,2pd)MP-2/6-311G++(3df,2pd)MP-2/cc-PVTZ

1) Shi, Y., et al., J. Med. Chem. 51, 7541-7551, 20082) Imai et al., Protein Science, 16, 1229, 2008PAGE 13

Application of FMO CalculationsPIE and PIEDA (Facio)1,2 and PIO (Pair Interacting Orbitals)3,4

Phe82

Phe80Glu81

His84Leu134

Exchange

Electrostatic

CT & Mixed

Dispersion

PIEDA diagram

PDB: 1WCCIC50 = 350mM

-48.40kcal/mol

1) Suenaga, M., J. Comput. Chem. Jpn., 4 (1), 25-32, 20052) Suenaga, M., J. Comput. Chem. Jpn., 7 (1), 33-53, 2008

PIO analysis

3) Fujimoto, H.; Koga, N.; Fukui, K. J. Am. Chem. Soc. 1981, 103, 7452. 4) Fujimoto, H.; Yamasaki, T.; Mizutani, H.; Koga, N. J. Am. Chem. Soc. 1985,

107, 6157.

Application of FMO to FBDDAstex AT7519 (CDK2 inhibitor) as an example

PDB: 2VTAIC50 = 185mM

LE = 0.57

PDB: 1WCCIC50 = 350mM

LE < 0.51

PDB: 2VTNIC50 = 0.85mM

LE = 0.44

PDB: 2VTPIC50 = 0.003mM

LE = 0.45

PDB: 2VTOIC50 = 0.14mM

LE = 0.39

AT7519IC50 = 0.047mM

LE = 0.40

Development discontinued

LE = -RT ln(IC50)/heavy atom cout

P. G. Wyatt et al., J. Med. Chem. 2008, 51, 4986-4999M. Congreve et al., J. Med. Chem. 2008, 51, 3661-3680PAGE 15

Application of FMO to FBDDPIEDA and PIO (Pair Interacting Orbitals)

Phe82Phe80

His84Leu134

Exchange

Electrostatic

CT & Mixed

Dispersion

PIEDA diagram PIO analysis

= Direction of CT

· PIEDA identifies the nature of ligand/protein interactions

– H-bond, VDW, p-p etc

· PIO analysis used to visualize and provide 3D information on the interactions

– Interacting orbitals, direction of charge transfer (vacant-occupied MO interaction)

PDB: 1WCCIC50 = 350mM-48.40 kcal/mol

Application of FMO to FBDD1WCC core modifications: FMO virtual SAR

DEDE = Sum PIE – Sum PIE (1WCC fragment)

1 2 3 4 5

6 7 8 9 10

11 12 13

IC50 = 7mM

· Medium throughput (up to few 100s input) FMO analysis can be rapidly carried out to answer SAR questions

· The technique is highly effective for prioritizing the initial fragment expansion directions or optimization for larger ligands

Removal of the chlorine detrimental to the fragment binding

IC50 = 350mM

Application of FMO to FBDDTracking the PDB: 2VTA development path by FMO analysis

PDB: 2VTOIC50 = 0.14mM

-64.81kcal/mol

PDB: 2VTNIC50 = 0.85mM

-61.24 kcal/mol

Val18 Val18

PDB: 2VTAIC50 = 185mM-41.71 kcal/mol

repulsive

attractive

Phe82

Phe80 Lys33-Asp145Salt bridge

Glu81

His84 Leu134

Leu83

96.55

-100.76

-94.99

-81.81

-79.53

-71.99

-70.77

-60.92

32

31

30

27

26

25

24

20

NH

N

NHR1

ONH

O R2

**

F

*

F

F

*

*

F

F

*

F

F

*

F

F

*

OH

*

NH2

*

*

F

F

F

*F

OMe

*

Cl

F

NH

*

NH

*

NH

*

FMO Heatmap AnalysisSum of the PIE

EnergyKcal/mol

IC50 (uM)

0.063

0.052

0.910

0.038

0.019

0.012

0.025

1.600

R1 R2

Binding Enthalpy Comparison to MM Methods

Method R2

FMO 0.68

GB IV 0.10

London dG 0.47

Affinity dG 0.18

Alpha HB 0.42

ASE 0.67

FMO GB IV London dG

Affinity dG Alpha HB ASE

Known Binding Modes from X-ray Structures

Summary

· Gaussian Tanimoto can be used to assess similarly shaped compounds to actives

· TES can be used to assess which docking pose is the best during VS

· TES used to identify suboptimal interactions for further development

· FMO can be used to identify which binding pose from a VS has the optimal interactions with a receptor

· FMO can be used to indentify subtle changes required to improve binding enthalpy· Molecular interactions reflected in the binding enthalpy are critical variables in lead

optimisation

Current and Future Work

· Currently assessing protein::ligand complementarity methods

PBSA treatment of free energy of solvation can be used to rationalize overestimated enthalpic terms in FMO

· Free energy of binding QSAR models are highly predictive· Need for improved treatment of

· Solvation· Entropy· Salts and Metals

Current and Future Work

Evotec CADD Group

Richard LawOsamu IchiharaAlex Heifetz

Acknowledgements

Chemical Computing GroupMOE svl Scripts

Andrew HenrySimon GrimshawGuido KirstenKristina Grabowski

FMO Developers

Dmitri Fedorov

Your contact:Dr. Mike MazanetzSenior Scientist, Computational Chemistry+44 (0) 1235 44 [email protected]

Appendices

IC50 µM DG

0.01 -11.34

0.1 -9.92

1 -8.51

10 -7.09

100 -5.67

R: universal gas constant ≈ 1.986 cal/KmolT: temperature 310 K

Aim of free energy calculation in a VS campaign is to rank-order moleculessuch that if a selection of high-ranking compounds is obtained and analysed,it is likely that some will show activity.

However, compound activity is likely to span about 5 log orders inmagnitude, which equates to free energy range of around5.5 kcal/mol at 37°C.

1) Williams, D., et al., Angew. Chem. Int. Ed., 43, 6596-6916, 2004

Estimation of Binding Free EnergiesEntropy – Enthalpy Compensation

Estimation of Binding Free Energies

· Relationship between to Ki (IC50) and the free enegy of binding

DG = -RT lnKD

· Free energy of ligand binding consists of two thermodynamic terms

DG = DH – TDS

Basic equations and two thermodynamic terms

• Binding enthalpy Notoriously difficult to optimize due to strict three dimensional requirementsEnthalpic improvement is often not reflected in better affinity, because of the associated entropy-loss (desolvation)

• Binding entropyDependent primarily on the hydrophobic effect and conformational entropyEasier to optimize and less affected by compensating enthalpy changes

Key SBDD Concepts

· Entropy-enthalpy compensation phenomenon· Desolvation penalty (4-8 kcal/mol per polar group)· Origin of hydrophobic interaction (entropy-driven effect, re-organization of surface

water network) · Two terms contribute to the entropy of binding

Desolvation entropy (always favourable, about 25 cal/mol Å2 for a carbon atom)

Conformational entropy

• Overcoming enthalpy/entropy compensationWell placed H-bond can make a favourable enthalpic contribution of the order of -4 to -5 kcal/mol (1000 – 5000 fold increase in affinity)Hydrogen bonds should be aimed at already structured regions of the proteinTry achieving multiple H-bonds for flexible residues – positive cooperativityBe aware of the forced solvent exposure of hydrophobic groups

PAGE 29

Free Energy of Binding Thermodynamic Cycle

ΔGVac = ΔEMM T·ΔS

ΔGBind, Solv = ΔGBind, Vac + ΔGSolv,Complex ( ΔGSolv,Ligand + ΔGSolv,Receptor )

ΔGSolv = ΔGElec, ε=80 ΔGElec, ε=1 + ΔGHydro

PAGE 30

+

+

ΔGBind, Solv

ΔGBind, Vac

ΔGSolv, ComplexΔGSolv, Ligand ΔGSolv, Receptor

r2 = 0.81q2 = 0.76

Predicted pIC50

Act

ual p

IC50ΔGVac = ΔEMM T·ΔS

ΔGBind, Solv = ΔGBind, Vac + ΔGSolv,Complex ( ΔGSolv,Ligand + ΔGSolv,Receptor )

ΔGSolv = ΔGElec, ε=80 ΔGElec, ε=1 + ΔGHydro

Estimation of Binding Free Energies

FMO sum PIE

PBSA using a single energy-minmized

structure

1) Rastelli G., et al., J. Comput. Chem., 31(4), 797-810, 2009

Number of rotatable bonds

All 28 CDK2 ligands

evotec ag, 5 th joint sheffield conference on chemoinformatics , july 2010

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