Computer aided drug designing

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Presented By: Abhishek Pandey MSc Biotechnology IVth Semester Department of Biotechnology Babasaheb Bhimrao Ambedkar University- Lucknow – 226 025:

Structural Basis of drug Designing: A Computational Drug Designing Presented By: Abhishek Pandey MSc Biotechnology IV th Semester Department of Biotechnology Babasaheb Bhimrao Ambedkar University- Lucknow – 226 025

Drug Discovery:

Drug Discovery Successful process More than 10 years and more than $300 million More than 10000 tested compounds For one drug! I. Choose a disease VI. Market V. Clinical Trials IV. Optimize lead III. Find a lead compound II. Choose a drug target Modern drug discovery process Target identification Target validation Lead identification Lead optimization Preclinical phase Drug discovery 2-5 years 6-9 years

Three Molecular Aspects:

Three Molecular Aspects Interfere the biological function of viruses, bacteria and parasite. Block the interaction of viruses, bacteria and parasite with our system. Interfere with or enhance our own biological functions. Target Based Approaches Structural Based Approaches De novo Approaches

Approaches:

Approaches QSAR Pharmacophore Mapping Hits Bioavailability & Toxicity checking Score Docking Database Denovo Receptor

Program made for different problems:

Program made for different problems Problem Ligand designed Method Programmed used Ligand with Conformational and structural variation The atom by atom ligand design method LEGAND, CONCEPTS, GROWMOL Generate ligand that are chemically or synthetically possible Fragment addition design method SPROUT, MCSS Ligand for ring structure or no receptor structure available The pharmacophore pattern ligand design method CAVEAT , LINIAR, RCEPS

Slide 6:

Drug Design Structure based Ligand based ? If protein sequence are known If protein sequence not known

Slide 7:

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

Slide 8:

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:

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?

Slide 10:

Different views of Docking

Slide 11:

Approaches to Docking Qualitative Geometric shape complementarily and fitting Quantitative Energy Calculations determine minimum energy structures Hybrid Geometric and energy complementarily 2 phase process: rigid and flexible docking

Slide 12:

Docking of Drug molecule to the Active site of Protein

Molecular Docking:

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.

1. Autodock window:

1. Autodock window

2. Open docking file which is save by PyMOL :

2. Open docking file which is save by PyMOL

3. Seeing the E Value:

3. Seeing the E Value

4. Docking Energy:

4. Docking Energy

5. Final docking sites:

5. Final docking sites

Some Available Programs to Perform Docking:

Some Available Programs to Perform Docking Affinity Auto Dock Bio Med CAChe CAChe for Medicinal Chemists DOCK Dock Vision Flex X Glide GOLD Hammerhead PRO_LEADS SLIDE VRDD

COMPUTER AIDED DRUG DESIGNING METHOD BY PLATFORM “PyMOL” :

COMPUTER AIDED DRUG DESIGNING METHOD BY PLATFORM “PyMOL” Research paper : Markus A. Lill . Matthew L Danielson 13 August 2010/ accepted: 20 October 2010/ published online: 30 October 2010 @Springer Science+Buisness Media B.V. 2010 DOI 10.1007/s 10822-010-9395-8

Program used in this platform:

Program used in this platform pymol ( www. pymol .org ) Amber ( http://ambermd.org ) Autodock ( http://autodock.scripps.edu/ )

Steps of the research paper:

Steps of the research paper

Steps involved in Drug designing by pyMOL:

Steps involved in Drug designing by pyMOL PDB file download of desired(Target molecule) by RCSB. Enter ID Enter desired protein which PDB file is to be download

Slide 24:

2. The PDB file is visualized by pyMOL

Slide 25:

3. By the help of AMBER we are going to visualize the Target molecule as well as produce our desired drug molecule for docking and the file save for docking analysis.

Slide 26:

4. After that we have to estimate free energy of the refined protein-ligand structure and can be automatically estimated using the sum of Vander walls, electrostatic interaction and Poission – Boltzmann surface area calculation(MMPBSA) or alternatively using SIE (Solvent Interaction Energies Method).

5. The target molecule are going to dock with the drug molecule and see the energy as well as conformation of the drugs as well as target molecules. :

5. The target molecule are going to dock with the drug molecule and see the energy as well as conformation of the drugs as well as target molecules.

Slide 28:

Fig: Screenshot of the notebook dialog used to define the docking search volume (a), flexible residues, and output settings. The corresponding box defining the docking search volume for a protein is shown below (b)

6. After docking we will go again to the PyMOL to visualize the target molecule with the specific drug.(e.g. HIV 1 Protease with antiviral agent SAQUINAVIR):

6. After docking we will go again to the PyMOL to visualize the target molecule with the specific drug.(e.g. HIV 1 Protease with antiviral agent SAQUINAVIR)

Slide 30:

Selection of molecule by stability score

After docking, Images::

After docking, Images: HIV 1 Protease ANTIVIRAL DRUG SAQUINAVIR Active Site

DOCKING:

DOCKING

Slide 34:

Typical Contributions of CADD to Drug Discovery Projects Suggestions of structures which, when retrieved from a compound collection or synthesized, were found upon testing to be active or inactive as predicted Development of structure-activity relationships Visualization of receptor models, pharmacophoric models, molecular alignments, or data models Reanalyzing available data to achieve new insights Creative search of available structures to find new leads

Slide 35:

Identification of preferred sites for structure elaboration Development of models to improve drug transport, specificity, safety or stability Development of mechanistic insights Use of leads in one area to derive new leads in a related assay Establishment of useful databases of project structures and properties Computation of physical or chemical properties to correlate with activities

References::

References: Cruciani et al., Molecular fields in quantitative structure-permeation relationships: the VolSurf approach, J. Mol. Struct . ( Theochem ), 2000, 503:17-30 Cramer et al.,Comparative Molecular Field Analysis ( CoMFA ). 1. Effect of shape on Binding of steroids to Carrier proteins, J. Am. Chem. Soc. 1988, 110:5959-5967 Ekins et al., Progress in predicting human ADME parameters in silico , J. Pharmacological and Toxicological Methods 2000, 44:251-272 De Voss et al., Substrate Docking Algorithms and Prediction of the Substrate Specifity of Cytochrome P450cam and its L244A Mutant, J. Am. Chem. Soc. 1997, 119:5489-5498 Ekins et al., Three-Dimensional Quantative Structure Activity Relationship Analyses of Substrates for CYP2B6, J. Pharmacology and Experimental Therapeutics, 1999, 288:21-29 Ekins et al., Three-Dimensional Quantative Structure Activity Relationship Analysis of Cytochrome P-450 3A4 Substrates, J. Pharmacology and Experimental Therapeutics, 1999, 291:424-433 Sechenykh et al., Indirect estimation of protein-ligand complexes Kd in database searching, www.ibmh.msk.su/qsar/abstracts/sech.htm A) Research Paper Used:

B)Software and tools used:-:

B)Software and tools used:- PyMOL Arguslab Autodock SLIDES Amber

Acknowledgement:

Acknowledgement I would like to thanks to our respected departmental teachers as well as my friends who help me and encouraged me to present this topic in my seminar. I would also like to thanks Mr. Pawan Kumar research Scholar of Bioinformatics Centre (Biotech Park) –Lucknow , without whom it can’t be possible.