Docking Algorithms Pavithra

8/13/2019 Docking Algorithms Pavithra

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MOLECULAR RECOGNITION AND

DOCKING ALGORITHM

Natasja Brooijmans & Irwin Kuntz

Pavithra.K.B


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INTRODUCTION

Binding between two molecules such that

their orientation maximizes the interaction

Earlier use

Protein-ligand complex

To find and optimize lead compounds

Docking program- key parts

Search

Scoring


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1. Protein-Protein Docking: Both molecules are rigid Interaction produces no change in conformation Similar to lock-and key model

2. Protein-Ligand Docking: Ligand is flexible but the receptor protein is rigid

Interaction produces conformational changes inligand

Categories of docking


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1. Protein-Protein Docking

2. Protein-Ligand Docking

optimized


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It involves:

Finding useful ways of representing the molecules and molecularproperties.

Exploration of the configuration spaces available for interactionbetween ligand and receptor. Evaluate and rank configurations using a scoring system, in this

case the binding energy

However, since it is difficult to evaluate the binding energy because the

binding sites may not be easily accessible, the binding energy is modeledas follows:

G bind= Gvdw+ Ghbond + Gelect+ G conform+ G tor + Gsol

Docking uses a search and scoremethod


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Flexibility Algorithms

Ligand FlexibilityAlgorithm

IncrementalConstruction

Monte carloAlgorithms

EvolutionaryAlgorithms

MolecularDynamicsMethod

Receptor FlexibilityAlgorithm

ConformerLibraries

Monte carlomethods

MolecularDynamicsMethod


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Algorithms

Systematic searches

Incremental construction

Stochastic searches

Montecarlo

Evolutionary Algorithm

Genetic Algorithm and LamarckianGA

Deterministic searches Energy minimization methods

Molecular dynamics simulations


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Incremental Construction

Anchor and grow method

Divide a ligandrigid and flexible.

Rotatable bonds Takes lowest n posenext level- Greedy

algorithm.

DOCK 4.0, FlexX Hammerhead- fragments- database screening.


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Monte Carlo Algorithm

Ligand is considered as whole

Random changes- translation, rotation & torsion.

Each move- structure is minimized

First cycle- high temperature

(Simulated annealing MC)- Autodock

Metropolis selection criterion= Local energy

minimization+ surface based solvationenergy+entropy calculation

Structure accepted or rejected. Prodock


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Simulated Annealing Algorithm modeled after the cooling of a solution to form glass,

though its better explained by crystal formation Given a long enough cooling time, molecules will relax into their

lowest energy state to form the largest crystals

Quick cooling - highly disordered system Slow cooling - highly ordered crystal, with each molecule in its

lowest energy state Algorithm simulates either linear or proportional slow cooling

At high temperatures, many higher energy solutions willbe accepted; at low temps., majority of probabilisticmoves rejected


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Evolutionary Algorithm

Stochastic method similar to MC methods

Finds global energy minimum

Fittest individuals carried- next generation

Random or biased mutation- genetic diversity

& prevent premature convergence

Cross over permitted in Genetic Algorithm

GOLD

AutodockGA and LGA (Lamarckian)


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How Genetic Algorithms Work -

A Simple Example

1 1 1 1 0 0

0 0 0 0 0 1

1 0 0 0 0 1

0 0 0 0 0 0

Initial population ofbinary creatures

having 6 genes Each gene has two

different alleles, eithera 0 or a 1

Three operators:crossover, mutationand selection


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Selection

1 1 1 1 0 0

0 0 0 0 0 1

1 0 0 0 0 1

0 0 0 0 0 0

Selection based on afitness function f(x)

This operator choosesthose individuals withthe lowest values

Those with highervalues chosen with avery low probability

20

13

48

52


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Crossover

0 0 0 1 0 0

1 1 1 0 0 1

1 1 1 1 0 1

0 0 0 0 0 0

1 1 1 1 0 0

0 0 0 0 0 1

1 1 1 1 0 0

0 0 0 0 0 1


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Mutation

0 0 1 1 0 0

1 1 1 0 1 1

1 1 1 1 0 1

0 0 1 0 1 0

0 0 0 1 0 0

1 1 1 0 0 1

1 1 1 1 0 1

0 0 0 0 0 0


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Replacement

Lower scoring individuals createmore offspring, higher scoringones create fewer or none at all

Offspring replace parentalgeneration

Cycle of selection, mutation,crossover and replacementrepeated

0 0 1 1 0 0

1 1 1 0 1 1

1 1 1 1 0 1

0 0 1 0 1 0

15 1

9 1

22 0

1 2


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MOLECULAR DYNAMICS METHODS

Cannot cross energy barriers

Easily trappedlocal minimauneven

potential energy

Two Approaches

Temperature ofthe simulation

Manipulatepotential energy


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SCORING FUNCTIONS

Accurate Binding free energy- time consuming

MM-PBSA & ES/IS methods

First-principles Methods DOCK & Autodock - Coulomb and

Van der waals force field

EUDOC- force field function- without grid


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Semi-empirical methods

Aqvist and coworkers- The linear interaction

energy (LIE)

Kuntz group developed SDOCK combines the van der Waals force field score

and the generalized Born-surface area (GB-SA)

Surface area

term-favors

VDW


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Empirical methods

Logical extension of Structure Activity

Relationship

First empirical scoring function LUDI

Reduction in

rotational

entropy


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The Application


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HIV-1 Protease and AHA006

HIV-1 Protease in complex with the cyclicsulfamide inhibitor, AHA006

Source: Protein Data Bank Authors: K. Backbro, T. Unge Exp. Method: X-ray Diffraction (2 res.) Primary Citation: Backbro et al, J Med Chem

40 pp. 898 (1997) Polymer Chains: A, B; Residues: 198; Atoms:

1632


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Protein (HIV-1 Protease)

Ligand(AHA006)

(Source: PDB)


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HIV-1 Protease dimer

(Rasmol)


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(SYBYL)

Initial X-Raycrystallographicpositions of protein

and ligand


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Docking Preparation Ligand

Assign charges Define rotatable bonds

Rename aromatic carbons Merge non-polar hydrogens Write .pdbq ligand file


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Docking Preparation Protein

Add essential hydrogens Load charges

Merge lone-pairs Add solvation parameters Write .pdbqt protein file


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AutoDock uses grid-

based docking

Ligand-proteininteraction energies

are pre-calculated and

then used as a look-uptable during

simulation

Grid maps areconstructed based onatoms of interest inligand (here CANOSH)

Docking Preparation Grid


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(AutoDockTools)


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(SYBYL)

Original ligand confSA conformation #67


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Original ligand confSA conformation #67

(SYBYL)

Close-up of previous


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Docking Algorithms Pavithra