MOLECULAR DOCKING V. Subramanian Chemical Laboratory Central Leather Research Institute Adyar,...

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MOLECULAR DOCKINGMOLECULAR DOCKING

V. SubramanianChemical LaboratoryCentral Leather Research Institute Adyar, Chennaisubbu@clri.info

Chemical + biological system desired response?

Drug discoveryDrug discovery

TRADITIONAL DRUG DESIGN

Lead generation: Natural ligand / Screening

Biological Testing

Synthesis of New Compounds

Drug Design CycleDrug Design Cycle

If promising

Pre-Clinical Studies

Finding lead compoundFinding lead compound• A lead compound is a small molecule that serves as the

starting point for an optimization involving many small molecules that are closely related in structure to the lead compound

• Many organizations maintain databases of chemical compounds

• Some of these are publically accessible others are proprietary

• Databases contain an extremely large number of compounds (ACS data bases contains 10 million compounds)

• 3D databases have information about chemical and geometrical features

» Hydrogen bond donors» Hydrogen bond acceptors» Positive Charge Centers» Aromatic ring centers» Hydrophobic centers

Finding lead compoundFinding lead compound

• There are two approaches to this problem– A computer program AutoDock (or

similar version Affinity (accelrys)) can be used to search a database by generating “fit” between molecule and the receptor

– Alternatively one can search 3D pharmacophore

Structure based drug designStructure based drug design

• Drug design and development • Structure based drug design exploits

the 3D structure of the target or a pharmacophore– Find a molecule which would be expected

to interact with the receptor. (Searching a data base)

– Design entirely a new molecule from “SCRATCH” (de novo drug/ligand design)

• In this context bioinformatics and chemoinformatics play a crucial role

Structure-based Drug Design (SBDD)

Molecular Biology & Protein Chemistry

3D Structure Determination of Target and Target-Ligand Complex

Modelling

Structure Analysisand Compound Design

Biological Testing

Synthesis of New Compounds

If promising

Pre-Clinical Studies

Drug Design CycleDrug Design Cycle

Natural ligand / Screening

Structure based drug designStructure based drug design

• SBDD:• drug targets (usually proteins)• binding of ligands to the target

(docking)

↓ “rational” drug design

(benefits = saved time and $$)

Select and Purify the target protein

Model inhibitor with

computational tools

Synthesis, Evaluate preclinical, clinical, invitro, invivo, cells, animals, & humans

Drug

Schematics for structure based drug designSchematics for structure based drug design

Obtain known inhibitor

X-Ray structural determination of native

protein

X-Ray structural determination of inhibitor complex

Determine IC50

Structure Based Drug Design have the potential to shave off years and millions of dollars

Working at the intersectionWorking at the intersection

• Structural Biology• Biochemistry• Medicinal Chemistry• Toxicology• Pharmacology• Biophysical Chemistry• Natural Products Chemistry• Chemical Ecology• Information Technology

Molecular docking-definitionMolecular docking-definition

• It is a process by which two molecules are put together in 3 Dimension

• Best ways to put two molecules together

• Using molecular modeling and computational chemistry tools

Molecular dockingMolecular docking

• Docking used for finding binding modes of protein with ligands/inhibitors

• In molecular docking, we attempt to predict the structure of the intermolecular complex formed between two or more molecules

• Docking algorithms are able to generate a large number of possible structures

• We use force field based strategy to carry out docking

Oxygen transport molecule (101M) Oxygen transport molecule (101M) with surface and myoglobin ligandwith surface and myoglobin ligand

Influenza virus b/beijing/1/87 neuraminidase Influenza virus b/beijing/1/87 neuraminidase complexed with zanamivircomplexed with zanamivir

Influenza virus b/beijing/1/87 neuraminidase Influenza virus b/beijing/1/87 neuraminidase complexed with zanamivir complexed with zanamivir

Plasma alpha antithrombin-iii and Plasma alpha antithrombin-iii and pentasaccharide protein with heparin ligand pentasaccharide protein with heparin ligand

Steps of molecular dockingSteps of molecular docking

• Three steps(1)Definition of the structure of the

target molecule

(2) Location of the binding site

(3) Determination of the binding mode

Best ways to put two molecules Best ways to put two molecules togethertogether

– Need to quantify or rank solutions

– Scoring function or force field

– Experimental structure may be amongst one of several predicted solutions

-Need a Search method

QuestionsQuestions

• Search– What is it?– When/why and which search?

• Scoring– What is it?

• Dimensionality– Why is this important?

Spectrum of searchSpectrum of search

• Local– Molecular Mechanics

• Short - Medium– Monte Carlo Simulated Annealing– Brownian Dynamics– Molecular Dynamics

• Global– Docking

Details of searchDetails of search

Level-of-Detail• Atom types• Terms of force field

– Bond stretching– Bond-angle bending– Torsional potentials– Polarizability terms– Implicit solvation

Kinds of searchKinds of search

Systematic• Exhaustive• Deterministic• Dependent on granularity of

sampling• Feasible only for low-dimensional

problems• DOF, 6D search

Kinds of searchKinds of search

Stochastic• Random• Outcome varies• Repeat to improve chances of

success• Feasible for higher-dimensional

problems

• AutoDock, < ~40D search

Stochastic search methodsStochastic search methods

•Simulated Annealing (SA)•Evolutionary Algorithms (EA)

– Genetic Algorithm (GA)

•Others– Tabu Search (TS)

•Hybrid Global-Local Search– Lamarckian GA (LGA)

Simulated annealingSimulated annealing

• One copy of the ligand (Population = 1)• Starts from a random or specific

postion/orientation/conformation (=state)

• Constant temperature annealing cycle (Accepted & Rejected Moves)

• Temperature reduced before next cycle• Stops at maximum cycles

Search parametersSearch parameters

Simulated Annealing• Initial temperature (K)• Temperature reduction factor (K-

1cycle)• Termination criteria:

– accepted moves– rejected moves– cycles

Genetic function algorithmGenetic function algorithm

• Start with a random population (50-200)• Perform Crossover (Sex, two parents -

> 2 children) and Mutation (Cosmic rays, one individual gives 1 mutant child)

• Compute fitness of each individual •Proportional Selection & Elitism• New Generation begins if total energy

evals or maximum generations reached

Search parametersSearch parameters

• Population size• Crossover rate•Mutation rate• Local search

– energy evals• Termination criteria

– energy evals– generations

Dimensionality of molecular Dimensionality of molecular dockingdocking

• Degrees of Freedom (DOF)• Position or Translation

– (x,y,z) = 3• Orientation or Quaternion

– (qx, qy, qz, qw) = 4• Rotatable Bonds or Torsions

– (tor1, tor2, … torn) = n

• Total DOF, or Dimensionality, D = 3 + 4 + n

Docking scoreDocking scoreDGbinding = DGvdW + DGelec + DGhbond +

DGdesolv + DGtors

DGvdW

12-6 Lennard-Jones potential• DGelec

Coulombic with Solmajer-dielectric• DGhbond

12-10 Potential with Goodford Directionality• DGdesolv

Stouten Pairwise Atomic Solvation Parameters• DGtors

Number of rotatable bonds

Molecular mechanics: theoryMolecular mechanics: theory• Considering the simple

harmonic approximation, the potential energy of molecules is given by

V= VBond+ VAngle + VTorsion + Vvdw + Velec+ Vop

• VBond = 1/2Kr (rij-r0)2

• Where Kr is the stretching force constant

• VAngle =1/2K (ijk-0)2

• Where K is the bending force constant

• VTorsion =V/2 (1+ Cos n(+0))• Where V is the barrier to

rotation, is torsional angle

Molecular mechanics: TheoryMolecular mechanics: Theory

• Lennard-Jones type of 6-12 potential is used to describe non-bonded and weak interaction

• Vvdw= (Aij/rij12-Bij/rij

6)

• Simple Columbic potential is used to describe electrostatic interaction

• Velec=(qiqj/rij)

• Out of plane bending/deformation is described by the following expression

• Vop= 0.5 Kop 2

The forcefieldThe forcefield• The purpose of a forcefield is to describe the

potential energy surface of entire classes of molecules with reasonable accuracy

• In a sense, the forcefield extrapolates from the empirical data of the small set of models used to parameterize it, a larger set of related models

• Some forcefields aim for high accuracy for a limited set of elements, thus enabling good predictions of many molecular properties

• Others aim for the broadest possible coverage of the periodic table, with necessarily lower accuracy

Components of a forcefieldComponents of a forcefield• The forcefield contains all the necessary

elements for calculations of energy and force: – A list of forcefield types – A list of partial charges

• Forcefield-typing rules – Functional forms for the components of the

energy expression • Parameters for the function terms

– For some forcefields, rules for generating parameters that have not been explicitly defined

– For some forcefields, a way of assigning functional forms and parameters

The energy expressionThe energy expression

Valence interactionsValence interactions• The energy of valence interactions is generally

accounted for by diagonal terms: – bond stretching (bond) – valence angle bending (angle) – dihedral angle torsion (torsion) – inversion, also called out-of-plane interactions

(oop) terms, which are part of nearly all forcefields for covalent systems

– A Urey-Bradley (UB) term may be used to account for interactions between atom pairs involved in 1-3 configurations (i.e., atoms bound to a common atom)

• Evalence=Ebond + Eangle + Etorsion + Eoop + EUB

Non-bond interactionsNon-bond interactions

• The energy of interactions between non-bonded atoms is accounted for by

• van der Waals (vdW) • electrostatic (Coulomb) • hydrogen bond (hbond) terms in

some older forcefields

• Enon-bond=EvdW + ECoulomb + Ehbond

Molecular dynamics (MD) Molecular dynamics (MD) simulationssimulations

• A deterministic method based on the solution of Newton’s equation of motion

Fi = mi ai

for the ith particle; the acceleration at each step is calculated from the negative gradient of the overall potential, using Fi = - grad Vi - = - Vi

Vi = Sk(energies of interactions between i and all other residues k located within a cutoff distance of Rc from i)

Classical molecular dynamics Classical molecular dynamics • Constituent molecules obey

classical laws of motion• In MD simulation, we have to

solve Newton's equation of motion

• Force calculation is the time consuming part of the simulation

• MD simulation can be performed in various ensembles

• NVT, NPT and NVE are the ensembles widely used in the MD simulations

• Both quantum and classical potentials can be used to perform MD simulation

• MM total energy can be used to get interaction energy of the ligands with biomolecules

• In order to compute the interaction energy, calculations have to be performed for the biomolecule, ligands and the biomolecule-ligand adduct using the same force field

• Eint= Ecomplex - {Ebiomolecule+Eligand}

Calculation of interaction energyCalculation of interaction energy

Integration of equation of motion Integration of equation of motion and time step and time step

• A key parameter in the integration algorithm is the integration time step

• The time step is related to molecular vibration• The main limitation imposed by the highest-

frequency motion• The vibrational period must be split into at

least 8-10 segments for models to satisfy the Verlet algorithm that the velocities and accelerations are constant over time step used

• In most organic models, the highest vibrational frequency is that of C-H stretching, whose period is of the order of 10-14 s (10fs). Therefore integration step should be 0.5-1 fs

Stages and duration in MD Stages and duration in MD simulationsimulation

• Dynamics simulations are usually carried out in two stages, equilibration and data collection

• The purpose of the equilibration is to prepare the system so that it comes to the most probable configuration consistent with the target temperature and pressure

• For large system, the equilibration takes long time because of the vast conformational space it has to search

• The best way to judge whether a model has equilibrated is to plot various thermodynamic quantities such as energy, temperature, pressure versus time

• When equilibrated, the system fluctuate around their average

Durations of some real Durations of some real molecular eventsmolecular eventsEvent Approximate duration

Bond stretching   1-20 fs  

Elastic domain modes   100 fs to several ps  

Water reorientation   4 ps  

Inter-domain bending  10 ps-100 ns  

Globular protein tumbling  1-10 ns  

Aromatic ring flipping   100 µs to several seconds  

Allosteric shifts 2 µs to several seconds  

Local denaturation  1 ms to several seconds  

Free energy simulationsFree energy simulations

• Ability to predict binding energy• Free energy perturbation and

thermodynamic integration• Computational demand and issues

related to sampling prevent this technique in probing structure based drug design

• Free Energy equation

• An impressive example of the application of SBDD is was the design of the HIV-I protease inhibitor

De novaDe nova design of inhibitor for HIV-I design of inhibitor for HIV-I proteaseprotease

De novaDe nova design design

• It is a member of the aspartyl protease family with the two active sites

• Structure has tetra coordinated water molecules tat accepted two hydrogen bond from the backbone amide hydrogens of isoleucine in the flaps

• Two hydrogen bonds to the carbonyl oxygens of the inhibitor

Application of structure based drug Application of structure based drug design: HIV protease inhibitorsdesign: HIV protease inhibitors

• The starting point is the series of X-ray structures of the enzyme and enzyme-inhibitor complex

• The enzyme is made up of two equal halves

• HIV protease is a symmetrical molecule with two equal halves and an active site near its center like butterfly

• For most such symmetrical molecules, both halves have a "business area," or active site, that carries out the enzyme's job

• But HIV protease has only one such active site in the center of the molecule where the two halves meet

Structure based drug design: HIV Structure based drug design: HIV protease inhibitorsprotease inhibitors

• The single active site was plugged with a small molecule so that it is possible shut down the whole enzyme and theoretically stop the virus' spread in the body

• Several Inhibitors have been designed based on– Peptidic inhibitor– Peptidomemitic compounds– Non-peptide inhibitors

• Further work has demonstrated the success of this approach

Some examplesSome examples

• Ritonavir (trade name Norvir) is one of a class of anti-HIV drugs called protease inhibitors

• Saquinavir • Indinavir is another example of very

potent peptidomimetic compound discovered using the elements of 3D structure and Structure Activity Relationship (SAR)

De novaDe nova design… design…

• The first step was a 3D database search of a subset of the Cambridge Structural Database

• The pharmacophore for this search comprised of two hydrophobic groups and a hydrogen bond donor or acceptor

• The hydrophobic groups were intented to bind to the catalytic asp residues

De novaDe nova design… design…• The search yielded the hit which contained

desired element of the pharmacophore but it also had oxygen that could replace the bound water molecules

• The benzene ring in the original compound was changed to a cyclohexanone, which was able to position substituents in a more fitting manner

• The DuPont Merck group had explored a series of peptide based diols that were potent inhibitors but with poor oral bioavailability

De novaDe nova design design

• They have retained the diol functionality and expanded the six me member ring to a seven membered diol

• The ketone was changed to cyclic urea to enhance the hydrogen bonding to the flaps and to help synthesis

• The compound chosen further studies including clinical trails was p-hydroxymethylbenzyl derivative

P1’P1

H-bond donor or acceptor

3.5-6.5Å 3.5-6.5Å

8.5-12Å

Symmetric diol docked into HIV active site

3D pharmacophore3D hit

Initial idea for inhibitor

Expand ring to give diol and incorporate urea

Stereochemistry required for optimal binding

Final Molecule selected for clinical Trials

Host-Guest Interactions with Host-Guest Interactions with Collagen: As moleculesCollagen: As molecules

Dominated by Geometrical factors and Solvent Accessible Volumes

Energy minimized structure of 24-Energy minimized structure of 24-mer collagen triple helixmer collagen triple helix

Aspargine of T.Helix and gallic acid

Aspartic acid of T.Helix and catechin

Complex Formation of poly phenols Complex Formation of poly phenols at various collagen sitesat various collagen sites

Lysine of T.Helix and epigallocatechingallate

Binding Sites in triple helix

Binding Energy (Kcal/mol)

Gallic acid (Gal)

Catechin (Cat)Epigallocatechi

ngallate (EGCG)

Pentagalloyl glucose (PGG)

9th residue Ser of C-chain (α2)

16.5 22.5 35.2 56.6

6th residue Hyp of A-chain (α1)

14.5 20.8 34.5 48.4

12th residue Lys of B-chain (α1)

19.2 23.8 37.9 41.1

21st residue Asp of A-chain (α1)

18.4 20.0 38.2 59.8

17th residue Asn of C-chain (α2)

14.1 23.7 34.3 52.8

Binding energies different complexes Binding energies different complexes between polyphenols and triple helixbetween polyphenols and triple helix

Interfacial interacting volume Vs Binding Interfacial interacting volume Vs Binding energy of the collagen-poly phenol complexenergy of the collagen-poly phenol complex

Interacting Interfacial Volume (Å3)

Effective solvent inaccessible contact volume Effective solvent inaccessible contact volume Vs Binding energy of the collagen-poly phenol Vs Binding energy of the collagen-poly phenol

complexcomplexInset: effective solvent inaccessible contact surface area Vs Binding energy of the complex

Plot of inverse of interacting interfacial volume Plot of inverse of interacting interfacial volume (1/Int.Vol.) Vs inverse of binding energy(1/B.E) of the (1/Int.Vol.) Vs inverse of binding energy(1/B.E) of the

complexescomplexes

AcknowledgementAcknowledgement

• Mr. R. Parthasarathi• Mr. B. Madhan• Mr. J. Padmanabhan• Mr. M. Elango• Mr. S. Sundar Raman• Mr. R. Vijayraj• CSIR & DST, GOI

Big Thank YouBig Thank You

Others have done the work. Some have used

the work. I have spoken only on behalf of their

behalf.