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Molecular DockingMolecular Docking

Ping-Chiang Lyu

Institute of Bioinformatics and Structural Biology,Institute of Bioinformatics and Structural Biology,Department of Life Science,Department of Life Science,

National National TsingTsing HuaHua University University

96/08/02

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Outline

IntroductionDocking methodSoftwareApplication

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Computational ligand design

Target Structure

Target Structure

Ligand-based approachesLigand-based approaches Structure-based approachesStructure-based approaches

(Pharmacophore + QSAR) (Docking; De novo design)

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Computational ligand design

Two different strategies: Ligand-based (analog-based) design

Relies on a set of known ligands and is particularly valuable if no structural information about the receptoris available.

Structure-based (target-based) designUsually starts with the structure of a receptor site, such as the active site in a protein. This structure can be generated from direct experimentation or can be deduced from experimental structures through homology modeling

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Ligand-based (analog-based) design

Pharmacophore+

QSAR

*QSAR; quantitative structure-activity relationships

LeadLead 3DReceptor

3DReceptor

experimental affinitiesmolecular properties

chemical structures

experimental affinitiesmolecular properties

chemical structures

A hypothesis of structural featuresA hypothesis of

structural features

Fit

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Structure-based (target-based) design

(Krumrine et al., 2003)

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Site-directed ligand generation

Two main approaches:Docking

Search available databases for matches to an active siteGiven an appropriate database, compounds are retrieved and are often immediately available for testing

De novo designGenerate new ligands by connecting atoms or molecular fragments uniquely chosen for a particular receptorDe novo design can suggest chemically novel ligandclasses that are not limited to previously synthesized compounds

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Docking is an energy-based operation for exploring the binding modes of two interaction molecules.

Docking

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Give the 3D structure of a protein target, compuondscan be designed to fit in a cavity, which is called "docking".The treatment ends when a minimum of energy is obtained for the complex.

Definition of Docking

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Docking Goal

:

1. (ligand)(protein)

2. DNA

3. (mutant)

4.

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Before Docking

( target site)

(bind site)( shape) hydrophobic sites (H), hydrogen bond donors (D) and acceptors (A)

(Flexible)

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Before Docking

Where

Whatdocking(conformation)?

How??

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Docking Require

(ligand)

Ligand: XK-263

Protein: HIV-1 Protease (1hvr)

Software: AutoDock version 2.4

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Docking Methods

Some common searching algorithms includeMolecular dynamicsMonte Carlo methods [AutoDock, ProDock, MCDOCK...]Genetic algorithms [GOLD, AutoDock, DARWIN...]Fragment-based methods [FlexX and DOCK]Point complementary methods [FTDOCK, FLOG...]Distance geometry methods [DockIt]Tabu searches [PRO LEADS]Systematic searches

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Force Field Models

Force fields are usually employed to generate accurate predictions to complex problems by interpolating and extrapolating from relatively simple experimental set of molecules.

Classical force field models AMBER, CHARMM and CVFF.

Second generation force field models CFF and COMPASS.

Generalized force field models ESFF and UFF.

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Software

docking

(rigid docking)

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(soft docking)

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(rigid docking)

(Distance geometry)(Monte-Carlo)(simulate annealing)

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(soft docking)

1.

2. (ligand)

3. (receptor)

4.

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Docking Flowchart

InputInput

OutputOutput

DockingDocking

LimitationLigand structureProtein structure

AutodockDockLudiGramm

Complex structure informationAnalysis ProSall, SWISS PDB ViewerEvaluation

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Docking Flowchart

InputInput

OutputOutput

DockingDocking

LimitationLigand structureProtein structure

AutodockDockLudiGramm

Complex structure informationAnalysis ProSall, SWISS PDB ViewerEvaluation

For Input Data:

Protein must be high resolution!

B factors

NMR(Poorly constrained regions)

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Docking Flowchart

InputInput

OutputOutput

DockingDocking

LimitationLigand structureProtein structure

AutodockDockLudiGramm

Complex structure informationAnalysis ProSall, SWISS PDB ViewerEvaluation

For Output Data:

(active sites)

(Geometry)

(potential energy)

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Evaluation

(ligand)(bioassay)(affinity)

scoring functionRoot mean square deviation (RMSD)QSAR (Quantitative Structure-Activity Relationship)

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Scoring function

Scoring function

(ligand)(conformation)

(ligand)

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Docking Software

AutoDock

Algorithm:

Monte Carlo simulated annealing and Lamarckian genetic algorithm

Force fields:

AMBER

Scoring function:

(Wang et al., 2003)

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AutoDock

(Wang et al., 2003)

Figure. Conformational ensemble of the ligand molecule generated by AutoDock (PDB entry 1BXO).

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Docking Software

Dock

Algorithm:

Fragment-based and genetic algorithm

Force fields:

AMBER

Scoring function:

(From DOCK Web-site)

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27(From DOCK Web-site)

The target (green) is an HIVgp41 protein, which mediates membrane fusion between the HIV virus and the host cell. During DOCKing, spheres (orange) are used to guide the placement of potential compounds (colored by atom type). These compounds are then scored using a grid (gray box) and ranked by their potential to bind to the target.

Dock

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Docking Software

GOLD (Genetic Optimisation for Ligand Docking)

Algorithm:

Genetic algorithm

A choice of scoring functions :

GoldScore, ChemScore and User defined score.

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Result of GOLD docking of the ligand in 1JAP, a matrix metalloprotease complex. The GOLD docked solution (structure shown in red) is compared with that observed in the PDB (shown coloured by element) RMSD = 0.8 Angstroms.

GOLD

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Application- Docking Example

Docking program: GOLDScoring function:

Bioorganic & Medicinal Chemistry 14 (2006) 27712778

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Docking study:

Biological data and molecular structures

Structures Sybyl, Charge& minimize

Docking

Prediction of binding free energies

Structural alignment

CoMFA model

GOLD

ChemScoring function for predicting binding free energyencoded in GOLD

GOLDinhibitory activitybinding free energy,binding

GOLDinhibitory activitybinding free energy,binding

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Figure 1. Superimposition of docked compound calculated by GOLD(blue) and X-ray crystallographic (red) conformations of TCO inactive sites of CatK.

(TCO, PDB ID: 1Q6K)

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Figure 2. (a) Binding conformations of docked

compounds at the active sites of CatK.(b) Superimposition of 59 aldehyde

analogues for 3D-QSAR studies.

34Compound 38

Figure 3. (a) Plots of pIC50 versus ChemScore

energy for compounds from the training and the test sets.

(b) Proposed interaction model of inhibitor 38 in the active sites of CatK

Figure 3b represents the interaction model of the docked inhibitor 38with CatK, as generated withthe program Ligplot.

Figure 3b represents the interaction model of the docked inhibitor 38with CatK, as generated withthe program Ligplot.

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Figure 4. Correlation between predicted activities (PA) by CoMFAmodels and the experimental pIC50 values of training and test sets, bluefilled triangles represent predictions for the training set, while red filledcircles represent predictions for the test set.

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Figure 5. CoMFA contour maps in combination with inhibitor 38: (a) the steric field distribution; (b) the electrostatic field distribution.

The inhibitor is shown in cyan stick. Sterically favored areas in green; sterically unfavored areas in yellow. Positive potential favored areas in blue; positive potential unfavored areas in red.

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Hot Link[AutoDock]: http://www.scripps.edu/mb/olson/doc/autodock/

[Dock]: http://www.cmpharm.ucsf.edu/kuntz/

[GOLD]: http://www.ccdc.cam.ac.uk/products/life_sciences/gold/

[LigPlot]: http://www.biochem.ucl.ac.uk/bsm/ligplot/ligplot.html

[DockIt]: http://www.metaphorics.com/products/dockit.html

[3D-Dock Suite]: http://www.bmm.icnet.uk/docking/

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Summary- Docking Software

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Bioinformatics Center, NTHU

http://bioinfo.life.nthu.edu.tw/