PY8016 - COMPUTER AIDED DRUG DESIGN (Syllabus) 2017-regulation Anna University

PY8016 - COMPUTER AIDED DRUG DESIGN (Syllabus) 2017-regulation Anna University

PY8016

COMPUTER AIDED DRUG DESIGN

 LPTC

3003

OBJECTIVES: The objective of this course is
• to find a chemical compound that can fit to a specific cavity on a protein target both geometrically and chemically.
• to know the informatics approaches to the prediction of chemical properties of new drugs
• to present the appropriate tools for such a modelling, ranging from electronic Structure methods, Molecular modelling, Structure Activity Relationships in drug design, QSAR, Molecular docking and Molecular dynamics

UNIT I

ELECTRONIC STRUCTURE METHODS

8

Quantum chemical methods semi-empirical and ab initio methods. Conformational analysis, energy minimization, predicting the mechanism of organic reactions using electronic structure methods.

UNIT II

MOLECULAR MODELING

9

Bioactive vs. global minimum conformations. Automated methods of conformational search. Advantages and limitations of available software. Molecular graphics. Computer methodologies behind molecular modeling including artificial intelligence methods.


UNIT III

STRUCTURE ACTIVITY RELATIONSHIPS IN DRUG DESIGN

9

Qualitative versus quantitative approaches advantages and disadvantages. Random screening, Non-random screening, rational approaches to lead discovery. Homologation, chain branching, ring-chain transformations. Insights into molecular recognition phenomenon. Structure based drug design, ligand based drug design.

UNIT IV

QSAR: ELECTRONIC EFFECTS

9

Hammett equation, lipophilicity effects. Hansch equation, steric effects. Taft equation. Experimental and theoretical approaches for the determination of physicochemical parameters, parameter inter-dependence: Regression analysis, Descriptor calculation. The importance of biological data in the correct form; 2D QSAR; 3D-QSAR examples of CoMFA and CoMSIA.

UNIT V

MOLECULAR DOCKING

10

Rigid docking, flexible docking, manual docking. Advantages and disadvantages of Flex-X, Flex-S, Autodock and Dock softwares, with successful examples. Dynamics of drugs, biomolecules, drug- receptor complexes, Monte Carlo simulations and Molecular dynamics in performing conformational search and docking.

TOTAL : 45 PERIODS

OUTCOMES: The student able
• To gain knowledge about fundamental concepts, challenges, and rich opportunities in developing and applying algorithms for structural bioinformatics and healthcare.
• To interpret and practice the fundamental concepts of Molecular Modeling and Computer- aided Drug Design.
• To develop practical skills in computational approaches to analyze, predict, and engineer biomolecules and biomolecular systems.

TEXT BOOKS:
1. Andrew R. Leach, Molecular Modelling Principle and Application, 2nd Edition, Prentice Hall, England,2001.
2. Richard B. Silverman, Mark W. Holladay, Organic Chemistry of Drug Design and Drug Action, 3rd Edition, Academic Press, USA, 2014.
3. Paul S. Charifson, Practical Applications of computer aided drug design, 1st Edition, Marcel Dekker, New York, 1997.
4. J. M. Goodman, Chemical Applications of Molecular Modelling, The Royal Society of Chemistry, Cambridge, 1998.

REFERENCES:
1. Donald J. Abraham, Burger’s Medicinal Chemistry and Drug Discovery, Vol V, 6th Edition, John Wiley and Sons, Inc., 2003.
2. John B. Taylor and David J. Triggle, Comprehensive Medicinal Chemistry II, Vol IV, Elsevier Science, 2006.
3. Graham L. Patrick, An Introduction to Medicinal Chemistry, 5th Edition, Oxford University Press, UK, 2013.
4. David. C. Young, Computational Drug Design – A Guide for Computational and Medicinal Chemists, John Wiley and Sons Ltd, Hoboken, United States, 2009.
5. Alan Hinchliffe, Molecular Modelling for Beginners, 2nd Edition, Wiley, United University of California, 2008.

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