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A Rational Approach to Receptor-Flexible

Docking: Method and Validation

October 2007

C. M. (Venkat) Venkatachalam, Ph. D.

Fellow, Accelrys

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Participant Code: 8587995760

2

Overview

• Receptor Changes in Ligand Binding• Flexible Docking• Discovery Studio 2.0 – Architecture of DS and

PipeLine Pilot• Key Pipeline Pilot Components used in Flexible

Docking– ChiFlex, CatConf, LibDock, ChiRotor, CDOCKER

• Flexible Docking Workflow• Results of Cross Docking

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Hydrogen bonding interactions in Thymidine Kinase within 4 angstroms of the ligand

Hydrogen bonding network

Ligand … Gln125 (2 hbs)Ligand … Glu225

Glu83 … Arg222Ile97 … Tyr101Gln125 … Ala168Arg163…Tyr172Arg222 … Glu225

1kim complex from xray

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Variation in Side chains in Estrogen: 1err vs 3ert

-10.632.4LEU539

-55.0-14.0ASP538

82.0179.6TYR537

-94.4120.2LEU536

44.5-69.3LEU525

-31.3128.5HIS524

47.3-107.7MET421

-23.3-15.0ARG394

-18.26.1TRP393

-11.2-14.2ILE389

-14.0-15.6GLU385

-12.483.1LEU354

-12.07-10.2ARG352

0-17.2THR347

13.6-3.1LEU346

19.4-8.6LEU345

∆chi2∆chi1residue

1err

3ert

∆chi = chi(3ert) -chi(1err)

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Flexible Docking: Needs and Challenges• Scientific Need: Increased accuracy of

docked poses • Challenges:

– Ignoring receptor flexibility during docking leads to inaccurate poses

• The problem is magnified in vHTS– There is often a complex network of

interactions between a protein and a bound ligand over many residues

– In existing docking methods, receptor conformational search needs to be repeated for each small molecule during vHTS

– For real vHTS applications, flexible docking needs to be fully automated Complex network of interactions in

Thymidine Kinase (PDB ID 1kim)

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Discovery Studio and Pipeline Pilot

• The Flexible Docking protocol requires a Pipeline Pilot Client• Can be run in Pipeline Pilot or Discovery Studio 2.0

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Key Components used to build a Flexible Docking Workflow

• ChiRotor – Side chain reconstruction• ChiFlex – Generates low energy side conformations• CatConf – Ligand Conformation generation• LibDock – Docks a ligand conformation rigidly to receptor site• CDOCKER – Ligand refinement in the presence of the receptorChiRotor/ChiFlexV. Z. Spassov, L. Yan, P. K. Flook, “The Dominant Role of Side-chain Backbone Interactions in Structural Realization of Amino-acid Code. ChiRotor: a Side-chain Prediction Algorithm Based on Side-chain Backbone Interactions”, Protein Science 16, 1-13 (2007).

CDOCKERG. Wu, D. H. Robertson, C. L. Brooks III and M. Veith, Detailed Analysis of Grid-Based Molecular Docking: A Case Study of CDOCKER- A CHARMm-Based MD Docking Algorithm, J. Comp. Chem. 24, 1549-1562, 2003.

J. A. Erickson, M. Jalaie, D. H. Robertson, R. A. Lewis and M. Vieth, “Lessons in Molecular Recognition: The Effects of Ligand and Protein Flexibility on Molecular Docking Accuracy”, J. Med. Chem., 47 (1), 45 -55, 2004

LibDockD. Diller and K. Mertz, PROTEINS: Structure, Function, and Genetics 43, 113–124 (2001)D. Diller and Li, R. J. Med. Chem. 46, 4638- 4647 (2003)

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Key Components used to build a Flexible Docking Workflow

• ChiRotor – Side chain reconstruction• ChiFlex – Generates low energy side conformations• CatConf – Ligand Conformation generation• LibDock – Docks a ligand conformation rigidly to receptor site• CDOCKER – Ligand refinement in the presence of the recptorChiRotor/ChiFlexV. Z. Spassov, L. Yan, P. K. Flook, “The Dominant Role of Side-chain Backbone Interactions in Structural Realization of Amino-acid Code. ChiRotor: a Side-chain Prediction Algorithm Based on Side-chain Backbone Interactions”, Protein Science 16, 1-13 (2007).

CDOCKERG. Wu, D. H. Robertson, C. L. Brooks III and M. Veith, Detailed Analysis of Grid-Based Molecular Docking: A Case Study of CDOCKER- A CHARMm-Based MD Docking Algorithm, J. Comp. Chem. 24, 1549-1562, 2003.

J. A. Erickson, M. Jalaie, D. H. Robertson, R. A. Lewis and M. Vieth, “Lessons in Molecular Recognition: The Effects of Ligand and Protein Flexibility on Molecular Docking Accuracy”, J. Med. Chem., 47 (1), 45 -55, 2004

LibDockD. Diller and K. Mertz, PROTEINS: Structure, Function, and Genetics 43, 113–124 (2001)D. Diller and Li, R. J. Med. Chem. 46, 4638- 4647 (2003)

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ChiRotorFlowChart

Protein3D Structure

Select a Set of n ResiduesFor Refinement

Remove all side chain atoms of selected residues

Choose Residue i

Sample side chain conformations of residue i varying χ1

Energy Minimize side chain atoms of residue i in CHARMm

Save 2 Best Conformations for residue i

Start loop for i from 1 to n

End loop for i

Output: 2n partial structures

Construct complete structure using lowest energy conformer of each residue.

Energy minimize all selected side chains

Replace side chain conformation i with the 2nd

conformer and energy minimize

Accept the structure if energy is lower.


End loop for i

Output: 1 Lowest Energy structure

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1.1890.3727GLU225

1.7541.7161.35240.8187ARG222

0.8823ARG176

0.5440.2950.20930.1153TYR172

1.627His164

1.4441.1520.25120.9478ARG163

0.3420.2070.12210.2999TYR132

0.3541.0860.9721.2551.0879MET128

1.5431.6111.6221.46340.1899GLN125

1.6220.25440.1899TYR101

0.0930.1880.2280.18230.1406ILE100

0.2471.2520.13550.2061ILE97

0.2520.1740.6121TRP88

2.2012.5942.00870.6576GLU83

1.5584.4751.1384.56621.7081HIS58

1e2k1e2m1ki41qhi1kim

Side Chain Conformations in Thymidine Kinase

ChiRotor calculation withligand present

•RMSD to Crystal Structure side chain coordinates

•Side chains within 4 angstroms from any ligandatom selected for refinement

•Blank means side chain was not selected for refinement

< 2.0

> 2.0

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ChiRotor: Placement of Side Chains in Thymidine Kinase Structures

3431.022ki5 -2

2741.302ki5 -1

4351.481qhi

2700.741kim

3790.791ki7

3450.761ki6

3221.161ki4

2191.351ki3

2151.91ki2

2111.341e2p

2161.851e2m

1761.091e2k

Time (secs)

RMSD (Å)Complex

ChiRotor calculation with ligand present

RMSD to Crystal Structure side chain coordinates

Side chains within 4 angstroms from any ligand atom selected for placement

Computing time for Dell M 70 Pentium 2 GHz single processor

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Side Chain Conformations in HUMAN CDK 2 COMPLEXED WITH THE INHIBITOR STAUROSPORINE -ChiRotor without the ligand

1.0151ASP145

0.4575LEU134

1.9583ASN132

2.6595GLN131

0.8786ASP86

0.4196GLN85

0.0814HIS84

1.444LEU83

0.4024PHE82

0.1778GLU81

0.2069PHE80

0.2018VAL64

0.519LYS33

0.2585VAL18

0.0651ILE10

1aq1

Protein shown with Ligand

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ChiFlexFlowChart

Protein3D Structure

Select a Set of n ResiduesFor Flexibility testing

Remove all side chain atoms of selected residues

Choose Residue i

Sample side chain conformations of residue i and energy minimize using CHARmm

Accept conformation if pass energy threshold and degeneracy checking


End loop for i

Output: a set of partial structures

Construct complete structure by making all possible combination of the partial structures and energy minimize using CHARMm

Output: multiple conformations with varingside chain conformations of the selected residues

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Identification of Flexible Residues

Thymidine Kinase (1kim)His58 Glu83 Ile97 Ile100 Gln125 Arg163 Tyr172 Arg176 Arg222Glu225Lowest RMSD to Crystal Side Chains ~1.0 angstroms

CDK2 (1aq1)Ile10 Lys33 Phe80 Glu81 Leu83 His84 Gln 85 Asp86 Gln131 Asn132 Leu134 Asp145Lowest RMSD to Crystal Side Chains ~1.8 angstroms

Residues identified by ChiFlex as highly flexible (>2 Å)

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Energy of Diverse Protein Side chain conformations

0

20

40

60

80

100

120

140

0 500 1000 1500 2000

No of Conformations

Rel

ativ

e En

ergy

1nsc1a4q1aq11dm21err3ert1rth1c1c1kjo

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Generate Protein Side Chain conformations using ChiFlex

Compute Hotspots

Generate LigandConformation using CatConf /CAESAR

Dock to HotspotsRetain n posesLibDock

Modify Side Chain conformations using ChiRotor

Anneal/Energy minimizeLigand poseCDOCKER

Flexible Docking Protocol

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New Flexible Docking Protocol

CDOCKER

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Step 1: Generate Receptor Conformations

Receptor

• Generate reasonable low energy side chain conformations– Side-chain/backbone

interactions explicitly taken into account

• Flexible residues specified by user and protocol

• Need to run only once per receptor binding siteO

O

O OO

OO

O

O

OOO

Generate n Receptor Structures Made up of different Side Chain

Conformations (ChiFlex)

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Step 2: Compute Protein Hotspots

Red = polar hotspotsBlue = apolar hotspots

Receptor

1. Diller and Merz,. PROTEINS: Structure, Function and Genetics 43:113-123 (2001)

Simple two-feature model has been shown to be

accurate and robust for guiding docking 1

Simple two-feature model has been shown to be

accurate and robust for guiding docking 1

Compute Hotspots onConformation n

O

O

O OO

OO

O

O

OOO



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Step 3: Generate Small Molecule Conformations

Generate Small Molecule Conformation (CatConf )

Small Molecules Several Methods Available: Optimize

either speed or accuracy

Several Methods Available: Optimize

either speed or accuracy

• Generates diverse low energy conformers

• Fast (~ 50 compounds per minute)

Receptor


O

O

O OO

OO

O

O

OOO

O

NH

NH2

O

NH2

O

NH2NH2



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Step 4: Fast and Efficient Docking to Hotspots

Dock to Hotspots (LibDock)

Retain m Poses



Receptor Small Molecules

Knowledge-based docking: only sample

relevant regions of binding site

Knowledge-based docking: only sample

relevant regions of binding site

• Triplets of hotspots matched to triplets of small molecule atoms

• Matches clustered and optimized

O

NH

NH2

O

NH2

O

NH2NH2



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Step 5: Side-Chain Optimization Around Docked Pose


Retain m Poses

Refine Side Chain Conformations

(ChiRotor)



Receptor Small Molecules

• CHARMm-based refinement of side chain positions in the presence of docked molecule pose

• 1-3 minutes per pose

O

O

O O

O

NH2

NH



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LibDock: Fast and Accurate Docking Solution

CAESAR2CatConf

BEST

91%

91%

61%

LibDock% Docked Successfully1

86%

86%

67%

SuccessRate

<2

<1

RMSD bin (Å)

.

1. Best of 10 highest-ranked poses2. Li et al, submitted to J. Chem. Inf. Model

• Docking results on the newly available AstexDiverse1 dataset– 85 receptor-ligand PDB entries comprising diverse receptor families– Docking under a minute per small molecule

% of AstexDiverse dataset docked successfully with LibDock using two conformation generation methods

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Ligand Pose, i

Generate Conformations(high temp MD), n

Generate Orientation (m)(in the presence of Rec)

And check vdW E Threshold

Simulated Annealing

Minimization

i*j

i*n

i*n*m

Receptor

i*n*m

Calculate Grid

Rank Best Poses, ji*n*m

CDOCKER Flowchart

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CDOCKER Results: RMSD to 41 Crystal Structures

RMSD

0.00

2.00

4.00

6.00

8.00

10.00

12.00

0.00 5.00 10.00 15.00 20.00 25.00 30.00 35.00 40.00

RMSD

1apu (PENICILLOPEPSIN )

1uvs (Thrombin)

1htf (hiv protease)

1pgp (PhosphogluconateDehydrogenase )

Proteins

RM

SD

Same Dataset as Erickson et al. J Med Chem (2004) 47:45-55

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Docking Solutions Optimized for Speed or Accuracy• Comparative performance of LibDock and CDOCKER on AstexDiverse1

dataset

5.51.50.87994CDOCKER

0.53.81.25091LibDock

Time (s)4

RMSD Average (Top)

RMSD Average (Best)

% Docked Accurately(Top)3

% Docked Accurately (Best)2

Method

LibDock is optimized for speed: : get accurate docked poses in seconds

LibDock is optimized for speed: : get accurate docked poses in seconds

CDOCKER is optimized for accuracy: : get significant improvement in rank-

ordering of correct pose and RMSD to X-ray structure

CDOCKER is optimized for accuracy: : get significant improvement in rank-

ordering of correct pose and RMSD to X-ray structure

1. Hartshorn, et al. J. Med. Chem., 50 (4), 726 -741 (2007)2. Best of 10 highest-ranked poses3. Top-ranked pose4. 3 GHz Intel Xeon, Linux

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Flexible Docking of 1kim ligand into 1kim receptor

Xray Ligand is shown in green.Ligand RMSD to xray = 0.8 angstrom

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Flexible Docking of 1ki4 ligand into 1kim receptor

Xray Ligand is shown in green.Ligand RMSD to xray = 1.0 angstrom

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Validation of Rational Flexible Docking

RMSD Values compared to X-ray conformation for cross-docking experiments

• Cross-docking: Dock ligands into an alternate conformation of the same receptor

5.23.061kr61kjo

4.91.161kjo1kr6Thermolysin

0.351rev1fk9

0.451fk91s1x

1.281fk91rth

1.121s1x1rth

0.721s1x1fk9

1.541rev1rth

0.581rev1s1x

0.581rth1fk9

5.30.541rth1s1x

4.91.511rth1revHIV-RT

4.21.71nsc1a4q

1.81.61a4q1nscNeurominidase

5.11.91cx23pgh

6.12.03pgh1cx2COX2

1.601dm21vyw

3.60.651aq11dm2

5.70.851dm21aq1CDK2

5.21.021err3ert

5.71.223ert1errEstrogen

2.71.21kim1ki4

1.11.21ki41kimThymidineKinase

Rigid ReceptorRMSD

Flexible ReceptorLowest RMSD

ReceptorLigandProtein

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Retain m Poses

Refine Side Chain Conformations

(ChiRotor)

Flexible Docking: Unprecedented Customizability

• Easily change workflow to incorporate different methods– Add CHARMm-based

loop sampling1 in the beginning

– Change the docking engine

1. V. Z. Spassov, L. Yan, P. K. Flook, to appear in Protein Science

Loop Sampling(Looper1)

• LigandFit• CDOCKER• GOLD

Replace with

Use Pre-generated Conformations

(e.g.: MD Trajectory Frames)

Refine docked Poses(CDOCKER)


Generate Protein Side Chain Conformations (n) (ChiFlex)

Generate Small Molecule Conformations (CatConf )

Energy minimize m Poses

(CHARMm)

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Improvements in DS 2.0

• Flexible Docking protocol based on LibDock technology

• Ligand Conformational sampling by CatConf or CAESAR

• Improved CDOCKER• Ability to handle structures with cofactor• Parallel Deployment of the protocol• Improved user interface (input

parameters/Output data)

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Summary of Accelrys Flexible Docking Method

• A rational approach• Consistent force field (CHARMm) used throughout• Minimal user intervention required• Docking into a realistic environment

– Docking of ligand influenced by existing side chains in active site– Accurate initial protein conformations

• Realistic and based on side-chain-backbone interactions as well as side-chain-side chain interactions

• Pre-generated side chain conformations can be used as input• Library of receptor conformations can be saved and used for all

small molecules being docked• Customizable• Parellel Execution in multi-processors and clusters

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Strengths of the Approach

• ChiRotor – ability to reliably predict side chain conformations

• Very flexible interface• Power of modifying the workings by modifying

workflow• Extendable interface – adding LOOPER• Docking engine may be replaced• Consistent, validated force field – CHARMm• A rational approach to Ligand…Protein

interaction problem

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Thanks to …• Accelrys

– R&D• Al Maynard (Structure Based Design) • Eric Yan (CHARMm)• Jürgen Koska (Flexible Docking Workflows)• Lisa Yan (Proteins)• Nan-Jie Deng (Simulation, CHARMm)• Velin Spassov (ChiRotor, ChiFlex)• Paul Flook (Direction)• Nic Austin (Direction)• Frank Brown (Discussions)

– Marketing• Sylvia Tara, Dipesh Risal

– Application Scientists• Over 25 PhD scientists

• External Collaboration– Charles E. Brooks (CHARMm, CDOCKER)– Dave Diller (LibDock)

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Future DS 2.0 Webinars

Elegant Protein-Protein Docking in Discovery Studio >>> November 20, 2007

Antibody Modeling: New Tools for Improved Success >>> November 8, 2007

Practical QSAR and Library Design: Advanced Tools for Research Teams >>> November 6, 2007

Going where no Pharmacophore has Gone Before: Fragment-based design and activity profiling >>>

November 1, 2007

A Rational Approach to Receptor-Flexible Docking: Method and Validation Results >>> October 16, 2007

New Simulation Methods for Drug Discovery: Fast Accurate pK Prediction and More >>>October 11, 2007

Overview of Discovery Studio 2.0 >>> October 9, 2007

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Accelrys Science Forums

• Come see Discovery Studio in action at the US and European Science Forums:

• Paris, France 18 October• Boston, MA 23 October• Princeton, NJ 25 October• San Diego, CA 30 October• Heidelberg, Ger 31 October• Cambridge, UK 13 November• San Francisco, CA 15 November

Agenda, Registration details, etc… can be found at:

www.accelrys.com/scienceforums

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