evotec ag, 5 th joint sheffield conference on chemoinformatics, july 2010 investigation of cdk2...
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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
PAGE 2
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
PAGE 3
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
PAGE 4
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
PAGE 5
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, 2008
2) Jennings and Tennant, J. Chem. Inf. Model. 47, 1829-1838, 2007
3) Balyl, et al., J. Comput. Chem., 132-146, 132, 2000
PAGE 6
1) P. G. Wyatt et al., J. Med. Chem. 51, 4986-4999, 2008
2) 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
PAGE 7
2VU3323130
2VTT2VTQ
27262524
2VTP2VTO
212019
2VTN1716
2VTL2VTI
132VTS2VTR2VTJ
92VTM2VTH2VTA
2VTA
2VTH
2VTM
92VT
J2VT
R2VT
S13
2VTI2VT
L16 17
2VTN
19 20 212VT
O2VT
P24 25 26 27
2VTQ
2VTT
30 31 322VU3
Gaussian Tanimoto
3nM
Fragment Hit Clinical Candidate
AT7519
Hit
GaussianTanimoto
Coefficient
Based on CDK2-Bound Alignment
PAGE 8
0.0
1.
5
4.0
Absolute Difference in pIC50
3nM
AT7519
Fragment Hit Clinical Candidate
Hit
AbsoluteDifference
In pIC50
PAGE 9
2VU3323130
2VTT2VTQ
27262524
2VTP2VTO
212019
2VTN1716
2VTL2VTI
132VTS2VTR2VTJ
92VTM2VTH2VTA
2VTA
2VTH
2VTM
92VT
J2VT
R2VT
S13
2VTI2VT
L16 17
2VTN
19 20 212VT
O2VT
P24 25 26 27
2VTQ
2VTT
30 31 322VU3
Electrostatic Tanimoto - TES
3nM
AT7519
Fragment Hit Clinical Candidate
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
PAGE 12
Fragment Molecular Orbital (FMO) Method
Method 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, 1999
2) Komeiji et al., Comput. Biol. Chem., 28, 155-161, 2004
3) Fedorov et al., J. Comput. Chem., 25, 872-880, 2004
The Cl-p Interaction in a Protein::Ligand Complex
Cl- 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)
En
erg
y (k
cal/m
ol)
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, 2008
2) Imai et al., Protein Science, 16, 1229, 2008PAGE 13
PAGE 14
Application of FMO Calculations
PIE and PIEDA (Facio)1,2 and PIO (Pair Interacting Orbitals)3,4
Phe82
Phe80Glu81
His84Leu134
Exchange
Electrostatic
CT & Mixed
Dispersion
PIEDA diagram
PDB: 1WCC
IC50 = 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 FBDD
Astex AT7519 (CDK2 inhibitor) as an example
PDB: 2VTA
IC50 = 185mM
LE = 0.57
PDB: 1WCC
IC50 = 350mM
LE < 0.51
PDB: 2VTN
IC50 = 0.85mM
LE = 0.44
PDB: 2VTP
IC50 = 0.003mM
LE = 0.45
PDB: 2VTO
IC50 = 0.14mM
LE = 0.39
AT7519
IC50 = 0.047mM
LE = 0.40
Development discontinued
LE = -RT ln(IC50)/heavy atom cout
P. G. Wyatt et al., J. Med. Chem. 2008, 51, 4986-4999
M. Congreve et al., J. Med. Chem. 2008, 51, 3661-3680PAGE 15
PAGE 16
Application of FMO to FBDD
PIEDA 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: 1WCC
IC50 = 350mM
-48.40 kcal/mol
PAGE 17
Application of FMO to FBDD
1WCC core modifications: FMO virtual SAR
DE
DE = 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
PAGE 18
Application of FMO to FBDD
Tracking the PDB: 2VTA development path by FMO analysis
PDB: 2VTO
IC50 = 0.14mM
-64.81kcal/mol
PDB: 2VTN
IC50 = 0.85mM
-61.24 kcal/mol
Val18 Val18
PDB: 2VTA
IC50 = 185mM
-41.71 kcal/mol
repulsive
attractive
Phe82
Phe80 Lys33-Asp145
Salt bridge
Glu81
His84 Leu134
Leu83
PAGE 19
-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
O
NH
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 Analysis
Sum 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
PAGE 20
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
PAGE 21
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
PAGE 22
Current and Future Work
· Currently assessing protein::ligand complementarity methods
PAGE 23
· 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
PAGE 24
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 Mazanetz
Senior Scientist, Computational Chemistry
+44 (0) 1235 44 [email protected]
PAGE 26
Appendices
PAGE 27
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 Energies
Entropy – Enthalpy Compensation
PAGE 28
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 requirements
Enthalpic improvement is often not reflected in better affinity, because of the associated
entropy-loss (desolvation)
• Binding entropyDependent primarily on the hydrophobic effect and conformational entropy
Easier 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 protein
Try achieving multiple H-bonds for flexible residues – positive cooperativity
Be 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
PAGE 31
r2 = 0.81q2 = 0.76
Predicted pIC50
Act
ual p
IC5
0
ΔGVac = 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