Computer Aided Drug Design Pharma 7th Sem Syllabus for B.Tech 2017 Regulation Anna Univ (Professional Elective V) detail syllabus for Pharmacy (Pharma), 2017 regulation is collected from the Anna Univ official website and presented for students of Anna University. The details of the course are: course code (PY8016), Category (PE), Contact Periods/week (3), Teaching hours/week (3), Practical Hours/week (0). The total course credits are given in combined syllabus.
For all other pharma 7th sem syllabus for b.tech 2017 regulation anna univ you can visit Pharma 7th Sem syllabus for B.Tech 2017 regulation Anna Univ Subjects. For all other Professional Elective V subjects do refer to Professional Elective V. The detail syllabus for computer aided drug design is as follows.
Course Objective:
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
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Unit II
Molecular Modeling
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
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
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Unit V
Molecular Docking
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, drugreceptor complexes, Monte Carlo simulations and Molecular dynamics in performing conformational search and docking.
Course Outcome:
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:
- Andrew R. Leach, Molecular Modelling Principle and Application, 2nd Edition, Prentice Hall, England,2001.
- Richard B. Silverman, Mark W. Holladay, Organic Chemistry of Drug Design and Drug Action, 3rd Edition, Academic Press, USA, 2014.
- Paul S. Charifson, Practical Applications of computer aided drug design, 1st Edition, Marcel Dekker, New York, 1997.
- J. M. Goodman, Chemical Applications of Molecular Modelling, The Royal Society of Chemistry, Cambridge, 1998.
References:
- Donald J. Abraham, Burgers Medicinal Chemistry and Drug Discovery, Vol V, 6th Edition, John Wiley and Sons, Inc., 2003.
- John B. Taylor and David J. Triggle, Comprehensive Medicinal Chemistry II, Vol IV, Elsevier Science, 2006.
- Graham L. Patrick, An Introduction to Medicinal Chemistry, 5th Edition, Oxford University Press, UK, 2013.
- David. C. Young, Computational Drug Design – A Guide for Computational and Medicinal Chemists, John Wiley and Sons Ltd, Hoboken, United States, 2009.
- Alan Hinchliffe, Molecular Modelling for Beginners, 2nd Edition, Wiley, United University of California, 2008.
For detail syllabus of all other subjects of B.Tech Pharma, 2017 regulation do visit Pharma 7th Sem syllabus for 2017 Regulation.
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