QM - Accelrys

Towards Increased 

Accuracy in 

Computational Drug 

Discovery with QM/MM 

Dipesh Risal, Ph. D. 

Life Sciences Product Manager 

June 26, 2008 

This presentation and/or any related documents contains statements regarding our plans or expectations for future features, 

enhancements or functionalities of current or future products (collectively "Enhancements"). Our plans or expectations are subject 

to change at any time at our discretion. Accordingly, Accelrys is making no representation, undertaking no commitment or legal 

obligation to create, develop or license any product or Enhancements. The presentation, documents or any related statements are 

not intended to, nor shall, create any legal obligation upon Accelrys, and shall not be relied upon in purchasing any product. Any 

such obligation shall only result from a written agreement executed by both parties. In addition, information disclosed in this 

presentation and related documents, whether oral or written, is confidential or proprietary information of Accelrys. It shall be used 

only for the purpose of furthering our business relationship, and shall not be disclosed to third parties.

Overview 

• QM/MM background 

• QM/MM implementation 

• Validation: Scientific applications of QM/MM 

© 2007 Accelrys, Inc. 

2

QM/MM overview 

• Combine QM and MM methods 

to achieve good accuracy at 

low cost 

– Treat ‘chemically 

significant’ region with QM 

– Treat the bulk with MM 

– Combine the results 


MM region 

QM region 

Ligand 

3

QM/MM in Discovery Studio 

• A QM/MM method has been 

implemented that 

incorporates 

– DMol3 (DFT) for the QM 

region 

– CHARMm for the MM region 

– QUANTUMm, a 

communication program 

between the two regions 

• How do each of these 

programs work? 


MM region 

QM region 

Ligand 

4

QM/MM Overview 

Anatomy of QM/MM machinery 


xyz 

QM 

Engine 

E 

∇E 

q 

QM/MM 

Driver 

xyz 

q 

MM 

Engine 

E 

∇E 


Driver 

Call QM Call MM 


Driver 

Geometry 

optimization or 

MD step 

Repeat 

• QM and MM servers only provide energies and gradients 

• Propagation algorithms (geometry optimization, MD, TS search ...) 

operate on data received from compute engines 

5

DMol3 DMol Overview 

3 Overview 

• DMol 3 uses DFT to predict structures, energies, 

electronic properties 

• Works for molecular and periodic systems 

• Extremely fast 

– Numerical basis sets provide a rapid means of evaluating 

Coulomb and exchange-correlation potentials 

– Provides options to trade off between computational cost 

and accuracy 

• Delley, J. Chem. Phys.113, 7756 (2000) 

– Energy calculations on drug-size molecules require few 

minutes on typical laptop 


6

DMol3 DMol Functionals 

3 Functionals 


H-bonded complexes Dispersion-dominated 

complexes 

Type of 

complex DMol 3 /PBE DMol 3 /HCTH Z-T B3LYP 1 Z-T PBE 1 

H-bond 1.0 3.4 2.0 1.3 

Dispersion 3.2 2.8 6.5 4.9 

Mixed 1.2 0.9 2.9 1.9 

1. J. Chem. Theory Comput. (2007), 3, 289-300. 

Mixed 

complexes 

Avg. Error (kcal/mol) 

of binding energies 

in loose complexes 

7

MM engine: CHARMm 

• CHARMm: the industry standard for simulation of macromolecules and protein-ligand systems 

• Constant Forcefield development 

– Alex MacKerell, Charlie Brooks, Bernard Brooks, Accelrys, Others 

• Most comprehensive simulation package available 

– MM, MD 

– CDOCKER 

– Free Energy Perturbation (FEP) 

– MM-PB/GB SA Scoring 

– Normal Mode analysis 

– RDOCK (refinement of Protein-Protein docking) 

– ChiRotor, Looper 

– Replica Exchange Molecular Dynamics (REMD) 

– Three implicit membrane models 

• GBSW, GBSA-IM, IMM1 

– Umbrella sampling 

– Monte Carol simulations 

– Physics-based pK Prediction and Protein Ionization 

– Constant-pH MD 

– And many more! 

• Strong UI support in Discovery Studio 

– Antibody Modeling 

– Implicit Membrane Modeling 

– Receptor-Flexible Docking 


8

QUANTUMm Overview 

• Total energy ... 

Etotal MM 

QM QM MM 

• Scientific requirements for biological 

QM/MM: 

– QM region “feels” MM atom 

environment 

– Minimal number of FF parameters 

for QM region 

• Issues to address 

– Embedding: how does the QM region 

interact with the MM region? 

– Boundary region: what happens to 

bonds that cross between regions? 


( O, 

I) 

= 

E ( O) 

+ E ( I) 

+ E / ( O ↔ I) 

E total = E( 

RMM, 

RQM) 

9

QM ↔ MM Coupling: Electrostatics 

QM density is polarized by MM point charges: 

electronic embedding 


MM → QM 

QM → MM 

elec 

E QM / 

MM 

O charges polarize I density 

I gradients induce forces on O 

Part of QM energy expression 

10

QUANTUMm Issue: Broken QM ↔ MM bonds 


Problem: QM calculation on I region yields unrealistic species 

→ add link atom (L) to QM calculation 

• Link atom is absent in MM calculation 

• Position restrained onto C A -C B vector 

• QM/MM server program handles link atoms transparently 

[Field, JCC 1990] 

11

Complications: Electrostatics 

Electronic embedding and link atoms 

Problem: QM overpolarization near link atoms: MM host too close 

Solution: the QM fragment should see no charge from MM host atom 


[Bakowies, JPC 1996; Sinclair, J Chem Soc Faraday 1998] 

12

QUANTUMm User Interface 

• DS QUANTUMm allows easy job setup 

• Select QM region 

• Set DFT options 


– Charge on QM region 

– Spin multiplicity of QM region 

– Relative precision (basis set, integration grid, SCF 

convergence) 

• Number of processors for parallel calculation 

• Provides the tools you need to balance the size of the 

problem, relative accuracy, and computational cost 

13

QM/MM Implementation I 

• Methods available for first release 


– QM/MM Minimization 

– QM/MM Energy Calculation (Single Point Energy) 

• If only the ligand is in the QM region, both protocols output 

ESP, Hirshfeld and Mulliken charges for ligand 

– Recharge Ligand Pipeline Pilot Component 

• Point charges from a protein model used in the electronic 

structure calculation, causing polarization of the ligand 

14

QM/MM Calculation: Setup in Discovery Studio 


15

QM/MM Applications for Life Science 

• QM/MM-derived ligand partial charges for: 

– improved docking accuracy (and simulation) 

• Optimization of hydrogen bonds 

– Post-processing of docked poses 

• Modeling of special electrostatic interactions not fully captured 

by force fields 

– Cation-Pi interactions 

– Pi-Pi interactions 

– Charge transfer 

– Metal-ligand-protein interactions 

• Improved estimate of interaction energy between protein and 

ligand 

• QM/MM in conjunction with MD 1 , QM-PBSA 2 

• Preparing ligands and cofactors for MM calculations 3 

– Heme, others 

• Studying reaction mechanisms 3 

– individual steps (hydrolysis, etc.) 

– transition state 

– entire catalytic cycle 

• Activation free energy 3 

• QM/MD (dynamics) 

• Semi-empirical method in QM/MM 


Possible Today. Some validation 

Already available 

Possible Today. Validation 

ongoing 

Possible in future releases based 

on customer prioritization 

1. J Comput Aided Mol Des. 2007 Jan-Mar;21(1-3):131-7 

2. J Phys Chem B, 109 (2):10474-83. 

3. Chem Rev. 2006 Sep;106(9):3497-519 

4. Drug Discov Today: Technologies, 2004 Dec; 1(3), 253-260 

5. Drug Discov Today. 2007 Sep;12(17-18):725-31 . 

16

QM/MM Background: Partial Charge Analysis 

Partial charges on ligand after MM and QM/MM Minimization, 1STP-1: Streptavidin/Biotin 

0.8 

0.6 

0.4 

0.2 

-0.2 

-0.4 

-0.6 

-0.8 


0 

MM Min QM/MM Min 

C11 

O11 

O12 

C10 

C9 

C8 

C7 

C2 

S1 

C6 

C5 

N1 

C3 

O3 

N2 

C4 

H1 

H2 

H3 

H4 

Generally, H-bond donors become increase in δ+ 

H-bond acceptors increase in δ- 

CHA RMm M-Rone 

CFF 

QM/MM Min 

H5 

H6 

H7 

H8 

H9 

H10 

H11 

H12 

H13 

H14 

H15 

H16 

17

QM/MM Applications: Background 

• CDOCKER is a CHARMm-based small molecule docking refinement 

algorithm 1 


– Uses soft-core potentials 

– Grid-based (optional) 

Generate ligand conformations 

through high temperature MD 

Random (rigid-body) rotation 

(grid-based) simulated annealing 

Full minimization 

Output # of refined ligand poses 

sorted by energy 

(vdW+ e/s + ligand strain) 

1. Wu et al. J Comput Chem (2003) 24:1549-62 

18

QM/MM Applications: Improving Docking Accuracy* 

• CDOCKER on AstexDiverse Dataset** (85 

diverse, high-resolution protein-ligand 

complexes) 

Prepared X-ray 

Protein- Ligand 

Complex 

Calculate CDOCKER QM charges 

for ligand 


Randomize 

Ligand Conformation 

Top 

Pose 

Dock with 

CDOCKER 

CDOCKER 

Dock with 

CDOCKER 

CDOCKER- 

QM-CDOCKER 

* Cho et al, J Comput Chem 26: 915–931, 2005 

** Hartshorn et al. JMC 2007 

Top 

Pose 

Top 

Pose 

Calculate RMSD 

to X-ray 

Calculate RMSD 

to X-ray 

Success 

Avg. 

RMSD 

Success 

Avg. 

RMSD 

First 

Pose 

72.62% 73% 72.62% 73% 

1.6331 1.6 1.6331 1.6 

First 

Pose 

77.38% 79% 

1.3856 1.4 

Poses are scored with CDOCKER Energy: 

sum of electrostatics+vdW interaction energy + ligand strain E 

X-Ray (A) 

Best 

Pose 

88.10% 88% 88.10% 88% 

1.0289 1.0 1.0289 1.0 

X-Ray (B) 

Best 

Pose 

90.48% 88% 

0.9114 1.3 

19

QM/MM Applications: Improving Docking Accuracy 

• 

• Pipeline Pilot workflow for CDOCKER-QM-CDOCKER 


Available options: 

ESP, Hirshfeld, Mulliken 

Available Options: 

Coarse/Medium/Fine. 

Affects the basis set, k-point, 

and SCF convergence criteria 

Available Options: local 

(LDA) potentials (PWC, 

VWN) and gradientcorrected 

(GGA) potentials 

(PW91, BP, PBE, BLYP, BOP, 

VWN-BP, RPBE, HCTH). 

20

QM/MM Applications: Improving Docking Accuracy 

• CDOCKER-QM-CDOCKER on AstexDiverse dataset: 

success by RMSD bin 

100% 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 


< 0.5 Å < 1.0 Å < 1.5 Å < 2.0 Å 

Only single, top-ranked 

pose for each PDB complex considered 

CDOCKER First Pose 

QM-CDOCKER First Pose 

100% 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

CDOCKER Best Pose 

QM-CDOCKER Best 

< 0.5 Å < 1.0 Å < 1.5 Å < 2.0 Å 

Best-RMSD pose (to X-ray) 

out of 10 docked poses considered 

21

QM/MM Application: Cation-Pi Interaction Modeling 

• Investigate the binding of Compound 1(active 

against Histamine H3 receptor) on AChE 1 

• Goal was to design dual-acting compound 

• Hypothesis of two cation-pi interactions 

between ligand and receptor 

• Docking (CDOCKER) of Compound 1 into AChE 

receptor (PDB ID 1EVE) yielded a pose in 

position to make cation-Pi interactions 

• Cation-Pi not modeled well by force fields 

• QM/MM geometry optimization suggests 

cation-Pi interactions 

– 51 hrs on 2 processors 

– Multiplicity: Smart 

– Quality: Ultra Coarse 

– Infinite nonbonded cutoffs 

– No constraints/restraints 


Einitial = -15676.278608 kcal/mol 

Efinal = -16904.454283 kcal/mol 

1. Bembenek, S. D.. et al., Bioorg. Med Chem. (2008), 

22

QM/MM Application: Optimizing Heme systems 

• Starting Structure: PDB ID 1P2Y 1 , Cytochrome P450CAM 

in complex with (S)-(-)-Nicotine 

nicotine 

Cys 357 


Arg 112 

His 355 

1. Biochemistry 42: 11943-11950 

Arg 299 

QM/MM min. 

2 proc. 2.6 GHz 

Xeon ca. 4 days 

nicotine 

Cys 357 

Arg 112 

His 355 

• improved coordination between Arg and 

heme carboxyl groups 

• coordination of Fe (II) 

Arg 299 

23

QM/MM Application: Optimizing Heme systems 

• Starting Structure: PDB ID 1P2Y 1 , Cytochrome P450CAM 

in complex with (S)-(-)-Nicotine 

6-coordination of Zinc in QM/MM optimized structure 

No constraints/restraints were used in the QM/MM optimization experiment 


1. Biochemistry 42: 11943-11950 

Initial QUANTUMm Energy = -29288.570302 kcal/mol 

Initial QM Energy = -13252.109685 kcal/mol 

Initial MM Energy = -16036.460617 kcal/mol 

QUANTUMm Energy = -33719.154699 kcal/mol 

QM Energy = -14279.192571 kcal/mol 

MM Energy = -19439.962129 kcal/mol 

24

QM/MM Application: Modeling Metals in Proteins 


Zinc Metalloproteins: important drug targets 

ligand bound to zinc ion 

development of zinc force field difficult 

coordination pattern 

electrostatics 

vdW interactions 

QM/MM description challenging 

large QM zone 

QM/MM bonds 

From Jain et al , PROTEINS 2007 

25

QM/MM Application: Optimization of MMP Binding Sites 

• Previous study 1 describes design and docking studies with matrix 

metalloproteinase-9 (MMP-9) and a set of hydroxamate inhibitors 

• The study was replicated in Discovery Studio 2.1 

– Sketch “Compound 1” 

– Dock to MMP9 receptor (PDB ID 1GKC) with CDOCKER 


Top docked pose using CDOCKER 

1. J. Med. Chem, 2005, 48, 5437-5447 

2. J. Med. Chem. 2002, 45, 919-929 

Known hydroxamate interactions in MMP-9 

binding site 2 

26






– Dock to MMP9 receptor (PDB ID 1GKC) 

– Take First Pose, optimize protein-ligand complex with QM/MM 


1. J. Med. Chem, 2005, 48, 5437-5447 

2. J. Med. Chem. 2002, 45, 919-929 

27


• Some details of QM/MM experiment 

– 3 His, Zinc, Glu402, Ligand included in QM region 

– Cut between QM and MM region made at the CA-CB bond of residue 

side chains 

– 5Å shell around QM region subjected to MM (CHARMm) 

– Rest of the system kept frozen (as per published study 1 ) 

– 2000 steps of minimization, PBE Functional, Ultra-Coarse setting 

(Basis Set: minimal, Integration Grid: xcoarse, DMol3 Cutoff 3.0 Å, 

SCF Density Convergence 5.0e-4) 

– 7 hours on 4 CPU 1.8GHz Opteron machine 


1. J. Med. Chem, 2005, 48, 5437-5447 

28








His411 


Zn 

Before QM/MM (Docked Pose) 

His405 

1. J. Med. Chem, 2005, 48, 5437-5447 

2. J. Med. Chem. 2002, 45, 919-929 

Glu402 

His401 Zn 

His411 

After QM/MM 

His405 

Glu402 

His401 

29








His411 


Zn 

His405 

1. J. Med. Chem, 2005, 48, 5437-5447 

2. J. Med. Chem. 2002, 45, 919-929 

Glu402 

His401 

QM/MM optimized distances and partial charges in a 

hydroxamate-MMP9 complex from a published study 1 

30


• Comparison of post-optimized interactions of two MMP-9 actives 

– Ongoing work: QM/MM-based scoring and rank-ordering of actives in the series 1,2 


His411 

“Compound 1” 

K i = 5.05 nM 

QM/MM Inter E = 

-246.95 Kcal/mol 

Zn 

His405 

1. J. Med. Chem, 2005, 48, 5437-5447 

2. J. Med. Chem. 2002, 45, 919-929 

Glu402 

His401 

His411 

“Compound 20” 

K i = 0.08 nM 

QM/MM Inter E = 

-266.92 Kcal/mol 

Zn 

Glu402 

His401 

QM/MM optimized distances and partial charges in a 

hydroxamate-MMP9 complex from a published study1 QM/MM optimized distances and partial charges in a 

hydroxamate-MMP9 complex from a published study 

His405 

1 

His405 

31

Summary/ Future Plans 

• QM/MM methods have been shown to provide improvement over 

pure force field (CHARMm) calculations 

• QM/MM methods have been applied in real-life computational tasks 

– Improved partial charges for docking 

– Modeling of special interactions such as cation-pi 

– Refinement of heme-containing systems 

– Optimization of metalloprotein active sites 

• accurate interaction energies 

• Ongoing validation 

– QM/MM-based scoring function 

– Comparison of DMol3 ESP charges with AM1-BCC, others 

– Torsion profiles (ΔE vs. torsional angle) for select small molecules 

• Future developments on QM/MM will be exclusively based on 

customer feedback 

– QM/MM based scoring function 

– Semi-empirical methods for QM 

– Modeling reaction mechanisms 


32

Thank you!!! 

• Thank You for attending today’s webinar. If you have any further questions please 

e-mail me at: drisal@accelrys.com 

• You can also contact us using the form on our website: 

http://accelrys.com/company/contact/ 

• We will be exhibiting at the following upcoming events: 


– CHI Protein Kinase Targets (June 23 – 25, Boston, Booth #4) 

– CHI Structure Based Design (June 25 – 27, Boston, Booth #7) 

– Drug Discovery Technology and Development (August 4 – 7, Boston, Booth #512) 

– ACS Fall 2008 (August 17 – 21, Philadelphia, Booth #211) 

• Reminder: the next webinar in this series will be: 

– Pharmacophore Guided Fragment-Based Drug Design 

Dr. Tien Luu – July 10, 2008 at 7am PST and 10am PST 

33

QM ↔ MM coupling: Short-range 


•QM ↔ MM van-der-Waals 

interactions 

handled classically (i.e., by 

MM server) 

•Requires Lennard-Jones 

parameters for QM region 

34

HOMO/LUMO Visualization (Work in Progress…) 


Diene Dienophile 

Diels-Alder Reaction 

The electron-rich HOMO of the diene and the 

Electron-vacant LUMO of the dienophile must 

be in a stacked orientation (top-bottom) for 

maximal overlap of the orbitals for the reaction 

to proceed 

HOMO LUMO 

35

QM - Accelrys

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