MOLECULAR MODELLING & DRUG DESIGN

What is Molecular modeling ? Molecular modelling encompasses all theoretical methods and

computational techniques used to model or mimic the behaviour of molecules.

• A science that elucidates and validates experimental evidence through imagination, visualization, and rationalization

• Applied in many areas of research (Academic/Industrial)

Capabilities of Molecular Modeling at Ranbaxy

Ligand- basedStructure- based

Lead Optimization

Crystal Structure analysis

Homology Modeling

Computational Analysis of Protein- Ligand Interactions

SAR, 2D- & 3D- QSAR

Lead Identification

I n- SillicoBBB,Solubility,Caco- 2 &Toxicity Predictions

Lead Hopping

Modification of ligands within the active- site for better binding

Pharmacophore Development

Hits fromDatabase Searches

Capabilities of Molecular Modeling

Prioritization of Hits

Application of Molecular Modeling

Molecular modelling methods are now routinely used to investigate the structure, dynamics, surface properties and thermodynamics of inorganic, biological and polymeric systems.

The types of biological activity that have been investigated using molecular modelling include protein folding, enzyme catalysis, protein stability, conformational changes associated with biomolecular function, and molecular recognition of proteins, DNA, and membrane complexes.

Popular software for molecular modelling

AMBER classical

AutoDock

CHARMM classical

Drug Design / drug discovery

What’s a drug? A substance that treats/cure a disease.A small molecule that interacts with a target, (often protein involved in the disease process; activator/inhibitor)

Drug discovery:The process of finding such a small molecule – combination of approaches

Drug discovery or drug design? In principle: “Design” is more rational and targeted, and “discovery” is more serendipitous. But design and discovery share a lot and are ~ synonymous in a pharmaceutical context.

Drug Design

Structure based Ligand based

Ligand (analog)based drug design

Receptor structure is not knownMechanism is known/ unknownLigands and their biological activities are known

Target (structure) based drug design

Receptor structure is knownMechanism is knownLigands and their biological activities are known/ unknown

High Resolution Structural Biology

Determine atomic structureAnalyze why molecules interact

Anti-tumor activityDuocarmycin SA

The Reward: UnderstandingControl

Shape

Atomic interactions

CAUTION….

macromolecular structure

protocols

methods

Structure determination methods

•Don't be a naive user!?!

• When computers are applied to biology, it is vital to understand the difference between mathematical & biological significance

• computers don’t do biology, they do sums quickly

Receptor Structure

Known Unknown

Structure BasedDrug Design

Analog BasedDrug Design

Docking

Homology ModelingReceptor Mapping

REQUIREMENTLead Compound and

derivatives with biologicaldata

REQUIREMENTA Model Receptor

Molecular DynamicsSimulations

Rigid Docking

FlexiDock

Monte CarloSimulations

Simulated Annealing

Quantum Mechanical(BRABO) ANN

GA

PCA

CoMFACoMSIA

QuantumMechanicalDescriptors

QuantumMechanics forAlignment

SYBYL, INSIGHT II, CERIUS2, MOE, AMBER (CDAC), DOCK, AUTODOCK

SINGLE MOLECULE

QSAR

Structure Based Drug Design

3D ligand Databases

DockingLinking orBinding

Receptor-LigandComplex

Random screening synthesis

Lead molecule

3D QSAR

Target Enzyme(or) Receptor

3D structure by Crystallography,NMR, electron microscopy (or)

Homology Modeling

Redesign to improve

affinity, specificity etc.

Testing

Compound databases, Microbial broths, Plants extracts,

Combinatorial Libraries

Drug and Target : Lock and Key ?

Most of the drugs “FIT” well to their targets

Study of protein crystals give the details of the “lock”. Knowing the “lock” structure, we can DESIGN some “keys”.

“Lock” structure (from experiment)

This is achieved by COMPUTER Algorithms

This is called “STRUCTURE BASED DRUG DESIGN”

“Key”constructed by computer

Algorithms

Some “Locks” are known but not all !!

Variations on the Lock and Key Model

1- Which structure of the lock should be targeted?

2- Is the binding pocket a good target?

3- Is structure-based design relevant for my receptor?

-Is the 3D structure reliable?

-Is the binding pocket static enough?

4- Which key fits best?

5- What are the prerequisite physicochemical properties for the key for better binding?

Ligand Active site

Non-Ligands

The ligand has been identified

Docking of Ligand to the Active site of Protein

3D Structure of the Complex

Experimental Information: The active site can be identified based on the position of the ligand in the crystal structures of the protein-ligand complexes

If Active Site is not KNOWN?????

Building Molecules at the Binding Site

Identify the binding regions Evaluate their disposition in space

Search for molecules in the library of ligands for similarity

Structure Based Ligand Design

O

NH

O

H

O

NH

?

O

O

O

H

O

NH

NSO

O

H

O

NH

O

H

O

NHS?

?

O

H

O

NH

??

?

OO

H

O

NH

DockingBuilding

Linking

O

O

O

H

HO

O

O

HH

OO

OH

OO

OH

O

O

OH

OH

O

DB Search

Define PharmacophoreLigandDesign

Structure based drug design

Molecular Docking

The process of “docking” a ligand to a binding site mimics the natural course of interaction of the ligand and its receptor via a lowest energy pathway.

Put a compound in the approximate area where binding occurs and evaluate the following:

Do the molecules bind to each other? If yes, how strong is the binding? How does the molecule (or) the protein-ligand complex

look like. (understand the intermolecular interactions) Quantify the extent of binding.

Molecular Docking (contd…)

Computationally predict the structures of protein-ligand complexes from their conformations and orientations.

The orientation that maximizes the interaction reveals the most accurate structure of the complex.

The first approximation is to allow the substrate to do a random walk in the space around the protein to find the lowest energy.

Algorithms used while docking

Fast shape matching (e.g., DOCK and Eudock), Incremental construction (e.g., FlexX,

Hammerhead, and SLIDE), Tabu search (e.g., PRO_LEADS and SFDock), Genetic algorithms (e.g., GOLD, AutoDock, and

Gambler), Monte Carlo simulations (e.g., MCDock and

QXP),

Some Available Programs to Perform Docking

Affinity AutoDock BioMedCAChe CAChe for Medicinal Chemists DOCK DockVision

FlexX Glide GOLD Hammerhead PRO_LEADS SLIDE VRDD

Thus to design a structure based drug we should know the molecules properties and its behavior by studing the molecular mechanics and molecular dynamics.

By knowing the molecular interactions and its properties we can be able to design a ligand or drug or key to the target.

Molecular mechanics

Molecular mechanics is one aspect of molecular modelling, as it refers to the use of classical mechanics/Newtonian mechanics to describe the physical basis behind the models.

Molecular mechanics methods are based on the following principles:

Nuclei and electrons are lumped into atom-like particles. Atom-like particles are spherical (radii obtained from

measurements or theory) and have a net charge (obtained from theory).

Interactions are based on springs and classical potentials. Interactions must be preassigned to specific sets of

atoms. Interactions determine the spatial distribution of atom-

like particles and their energies.

Objective of Molecular mechanics

The object of molecular mechanics is to predict the energy associated with a given conformation of a molecule.

However, molecular mechanics energies have no meaning as absolute quantities.

Only differences in energy between two or more conformations have meaning.

Emprical Force-FieldMolecular Mechanism

The mechanical molecular model considers atoms as spheres and bonds as springs. The mathematics of spring deformation can be used to describe the ability of bonds to stretch, bend, and twist:

Non-bonded atoms (greater than two bonds apart) interact through van der Waals attraction, steric repulsion, and electrostatic attraction/repulsion. These properties are easiest to describe mathematically when atoms are considered as spheres of characteristic radii.

A simple molecular mechanics A simple molecular mechanics energy equation is given by:

Energy = Stretching Energy + Bending Energy + Torsion Energy + Non-Bonded Interaction Energy

These equations together with the data (parameters)

required to describe the behavior of different kinds of atoms and bonds, is called a force-field.

In the context of molecular modeling, a force field refers to the form and parameters of mathematical functions used to describe the potential energy of a system of particles (typically molecules and atoms).

The mathematical form of the energy terms varies from force-field to force-field. The more common forms are : Stretching Energy Bending Energy Torsion Energy Non-Bonded Energy

STRETCHING ENERGY

•The stretching energy equation is based on Hooke's law. The "kb" parameter controls the stiffness of the bond spring, while "ro" defines its equilibrium length. Unique "kb" and "ro" parameters are assigned to each pair of bonded atoms based on their types (e.g. C-C, C-H, O-C, etc.). This equation estimates the energy associated with vibration about the equilibrium bond length. This is the equation of a parabola, as can be seen in the following plot

Components

bond length

Bonds behave like spring with equilibrium bond length depending on bond type. Increase or decrease from equilibrium length requires higher energy.

BENDING ENERGY

•The bending energy equation is also based on Hooke's law. The “k” parameter controls the stiffness of the angle spring, while ”o" defines its equilibrium angle. This equation estimates the energy associated with vibration about the equilibrium bond angle

bond angle Bond angles have equilibrium

value eg 108 for H-C-H Behave as if sprung.

Increase or decrease in angle requires higher energy.

TORSIONAL ENERGY

The torsion energy is modeled by a simple periodic function

Rotation can occur about single bond in A-B-C-D but energy depends on torsion angle (angle between CD & AB viewed along BC). Staggered conformations (angle +60, -60 or 180 are preferred). Torsional energy varies during rotation about C-C, C-N and C-O single bonds.The maximum values occur at t=0˚ and represent “eclipsing” interactions between atoms separated by three sigma bonds.

NON-COVALENT (NON-BONDED) TWO ATOM INTERACIONS

The non-bonded energy represents the pair-wise sum of the energies of all possible interacting non-bonded atoms i and j

The non-bonded energy accounts for van der Waals attraction, repulsion and electrostatic interactions.

MOLECULAR DYNAMICS

Molecular Dynamics are used to investigate the structure, dynamics and thermodynamics of biological molecules and their complexes

Protein stabilityConformational changesProtein foldingMolecular recognition: proteins, DNA, membranes, complexesIon transport in biological systems

The molecular dynamics method was first introduced by Alder and Wainwright in the late 1950's (Alder and Wainwright, 1957,1959) to study the interactions of hard spheres

The first molecular dynamics simulation of a realistic system was done by Rahman and Stillinger in their simulation of liquid water in 1974 (Stillinger and Rahman, 1974). The first protein simulations appeared in 1977 with the simulation of the bovine pancreatic trypsin inhibitor (BPTI) (McCammon, et al, 1977).

The molecular dynamics simulation method is based on Newton’s second law or the equation of motion, F=ma, where F is the force exerted on the particle, m is its mass and a is its acceleration

From a knowledge of the force on each atom, it is possible to determine the acceleration of each atom in the system

Integration of the equations of motion then yields a trajectory that describes the positions, velocities and accelerations of the particles as they vary with time. From this trajectory, the average values of properties can be determined

The method is deterministic; once the positions and velocities of each atom are known, the state of the system can be predicted at any time in the future or the past

Newton’s equation of motion is given by

where Fi is the force exerted on particle i, mi is the mass of particle i and ai is the acceleration of particle i. The force can also be expressed as the gradient of the potential energy,

Integration AlgorithmsThe potential energy is a function of the atomic positions (3N) of all the atoms in the system. Due to the complicated nature of this function, there is no analytical solution to the equations of motion; they must be solved numerically.

Numerous numerical algorithms have been developed for integrating the equations of motion.Verlet algorithmLeap-frog algorithmVelocity VerletBeeman’s algorithm

Important: In choosing which algorithm to use, one should consider the following criteria:The algorithm should conserve energy and momentum.It should be computationally efficientIt should permit a long time step for integration.

Integration Algorithms

All the integration algorithms assume the positions, velocities and accelerations can be approximated by a Taylor series expansion:

Where r is the position, v is the velocity (the first derivative with respect to time), a is the acceleration (the second derivative with respect to time), etc.

To derive the Verlet algorithm we can write

Summing these two equations, one obtains

The Verlet algorithm uses positions and accelerations at time t and the positions from time t-dt to calculate new positions at time t+dt. The Verlet algorithm uses no explicit velocities.

The Velocity Verlet algorithm

This algorithm yields positions, velocities and accelerations at time t. There is no compromise on precision.

The Leap-frog algorithm

In this algorithm, the velocities are first calculated at time t+1/2dt; these are used to calculate the positions, r, at time t+dt. In this way, the velocities leap over the positions, then the positions leap over the velocities. The advantage of this algorithm is that the velocities are explicitly calculated, however, the disadvantage is that they are not calculated at the same time as the positions. The velocities at time t can be approximated by the relationship:

Beeman’s algorithm

This algorithm is closely related to the Verlet algorithm

The advantage of this algorithm is that it provides a more accurate expression for the velocities and better energy conservation. The disadvantage is that the more complex expressions make the calculation more expensive.

Conclusion

Thus by knowning the interactions between the atoms or molecules we can study the behavior and its active site and hence it can be used to search a ligand or building a new ligand by denovo processes by using various computer simulations, algorithms, etc.

The drug is most commonly an organic small molecule that activates or inhibits the function of a biomolecule such as a protein, which in turn results in a therapeutic benefit to the patient.

In the most basic sense, drug design involves design of small molecules that are complementary in shape and charge to the biomolecular target to which they interact and therefore will bind to it.

Drug design frequently but not necessarily relies on computer modeling techniques.This type of modeling is often referred to as computer-aided drug design.

Modeling techniques for prediction of binding affinity are reasonably successful. However there are many other properties such as bioavailability, metabolic half-life, lack of side effects, etc. that first must be optimized before a ligand can become a safe and efficacious drug. These other characteristics are often difficult to optimize using rational drug design techniques.

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