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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)
12 ~2 ~453
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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/