COMPUTER AIDED DRUG DESIGN.pptx
- 1. COMPUTER AIDED DRUG DESIGN MOLECULAR DOCKING AND DRUG RECEPTOR INTERACTIONS: RIGID DOCKING, FLEXIBLE DOCKING & EXTRA PRECISION DOCKING Presented by Sumit Maji M.Pharm, Pharmaceutical Chemistry Bharat Technology
- 2. CONTENT Introduction Molecular Docking Docking: Basic concepts Importance of Docking Flowchart of Docking Types of Molecular Docking Docking tools Drug Receptor Interactions
- 3. INTRODUCTION Docking is structure based technique which attempts to find the best match between two molecules. Molecular docking is an attractive scaffold to understand drug biomolecular interactions for the rational drug design & drug discovery.
- 4. MOLECULAR DOCKING Molecular docking is an attempt to find the best matching between two molecules. Docking is a method which predicts the preferred orientation of one ligand when bound in an active site to form a stable complex. Knowledge of the preferred orientation may be used to predict he strength of association or binding affinity between two molecules.
- 5. DOCKING: BASIC CONCEPTS The protein can be thought as the lock & ligand can be thought as a key.
- 6. IMPORTANCE OF DOCKING Identification of the ligand’s correct binding geometry (pose) in the binding site(Binding Mode) Prediction of the binding affinity (Scoring Function) Rational design of drugs: It is the key to rational drug design. The result of docking can be used to find inhibitors for specific target proteins and design of new drugs as well.
- 8. TYPES OF MOLECULAR DOCKING Rigid Docking(Lock & Key) In rigid docking, internal geometry of both the receptor and ligand is rigid/kept fixed, then docking is performed. Flexible Docking (Induced fit) An enumeration on the rotations of one of the molecules(usually smaller one) is performed. In every rotation the energy is calculated. Then most optimum pose is selected.
- 9. RIGID DOCKING Historically the first approaches Protein and ligand are fixed Search for the relative orientation of two molecules with lowest energy. First apply steric constants to limit search space and examine energetics of possible binding conformaions.
- 10. FLEXIBLE DOCKING Protein ligand docking Flexible ligand and rigid receptor Search space much larger. Either reduce flexible ligand to rigid fragments connected by one or several hinges, or search the conformaional space using monte carlo methods or molecular dynamics.
- 11. DOCKING TOOLS Docking Software DOCK AutoDock GOLD GLIDE LigandFit Docking Algorithm Shape fitting Lamarckian algorithm Genetic Algorithm Monte Carlo Sampling
- 12. STEPS FOLLOWED FOR MOLECULAR DOCKING IN-silico generation of ligands (Using chemsketch we can draw the structure of ligand/molecule Converted the file to suitable format (OPEN BABEL is the software used to converting format of file from .mol to .pdb. Protein optimization( RCSB- Protein data bank, here we can prepare our protein of interest for docking).www.rcsb.org
- 13. Energy minimization ( SPDV swiss-Pdb viewer software) Molecular docking (creaion of .gpf-grid parameter file & .dpf-dock parameter file. 1) Autodock Vina 2) Autodock 4.0 3) Autodock 4.2 This softwares are used to make auto griding and dock parameters along with grid mapping.
- 14. Running the docking algorithm(CYGWIN-1 in this software we will create GLG file & DLG file here this software works commanding after getting successful command for auto grid(glg) & auto dock (dlg) After this step we got to know minimal binding energy CYGWIN-2 Hydrogen bond analysis (UCSF CHIMERA software is used for visulisation & analysis of result)
- 15. ADMET ( the molecules which have shown H-bond with the active site residue or any other residue of the binding pocket. Note down those molecules and then run these molecule on the online ADMET servers
- 16. REFERENCES Morris GM, Goodsell DS, Halliday RS, Huey R, Hart WE, Olson AJ(1998). ‘Automated docking using a Lamarckian genetic algorithm and an emperical binding free energy function’. Journal of Computational Chemistry 19(14): 1639-1662. Morris RJ, Najmanovich RJ, Kahraman A, Thornton JM(May,2005). ‘Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons’. Bioinformatics 21(10): 2347-55 www.ncbi.nlm.nih.gov/pubmed/18446297