75736282-Molecular-Modelling-Drug-Design.pptx

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1. MOLECULAR MODELLING & DRUG DESIGN

2. 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)

3. Pharmacophore Development Hits from Database Searches Capabilities of Molecular Modeling Prioritization of Hits

4. 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.

5. Popular software for molecular modelling AMBER classical AutoDock CHARMM classical

6. 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.

7. Drug Design Structure based Ligand based ?

8. Ligand (analog) based drug design Receptor structure is not known Mechanism is known/ unknown Ligands and their biological activities are known Target (structure) based drug design Receptor structure is known Mechanism is known Ligands and their biological activities are known/ unknown

9. High Resolution Structural Biology Determine atomic structure Analyze why molecules interact

10. Anti-tumor activity Duocarmycin SA The Reward: Understanding  Control Shape Atomic interactions

11. 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

12. Structure Based Drug Design 3D ligand Databases Docking Linking or Binding Receptor-Ligand Complex 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

13. Drug and Target : Lock and Key ? Most of the drugs “FIT” well to their targets

14. 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 !!

15. 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?

16. The ligand has been identified

17. Docking of Ligand to the Active site of Protein

18. 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?????

19. 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

20. Structure Based Ligand Design

21. O O O H H O O O H H O O O H O O O H DB Search Define Pharmacophore Ligand Design Structure based drug design

22. 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.

23. 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.

24. 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),

25. Some Available Programs to Perform Docking Affinity AutoDock BioMedCAChe CAChe for Medicinal Chemists DOCK DockVision FlexX Glide GOLD Hammerhead PRO_LEADS SLIDE VRDD

26. 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.

27. 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.

28. 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 .

29. 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.

30. Emprical Force-Field Molecular 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.

31. 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).

32. 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

33. STRETCHING ENERGY The stretching energy equation is based on Hooke's law. The "k b " parameter controls the stiffness of the bond spring, while " r o " defines its equilibrium length. Unique "k b " and " r o " 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.

34. 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.

35. 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.

36. 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.

37. Molecular Dynamics

38. Molecular Dynamics are used to investigate the structure, dynamics and thermodynamics of biological molecules and their complexes Protein stability Conformational changes Protein folding Molecular recognition: proteins, DNA, membranes, complexes Ion 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).

39. 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

40. Newton’s  equation of motion is given by where  F i   is the force exerted on particle  i ,  m i  is the mass of particle  i  and  a i  is the acceleration of particle  i.  The force can also be expressed as the gradient of the potential energy,

41. Integration Algorithms The 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 algorithm Leap-frog algorithm Velocity Verlet Beeman’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 efficient It should permit a long time step for integration.

42. 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.

43. 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.

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

45. 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:

46. 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.

47. 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.

48. 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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