MTech Biomolecular Simulations syllabus for 2 Sem 2020 scheme 20BBI23

Module-1 Molecular Mechanics 0 hours

Molecular Mechanics:

Introduction, The Morse Potential, The Harmonic Oscillator Model for Molecules, Comparison of Morse and Harmonic Potential, Two atoms connected by a bond, Poly atomic Molecules, Energy due to Stretch, Bend, Stretch-Bend, Torsional strain, van der Waals and Dipole-Diploe interactions. Types of Potentials: Lennard-Jones, Truncated Lennard-jones, Exponential-6, Ionic and Polar potentials. Types of Force Fields: AMBER, CHARMM, Merck Molecular Force Field, Consistent Force Field, MM2, MM3 and MM4 force fields.

Module-2 Potential Energy Surface 0 hours

Potential Energy Surface:

Convergence Criteria, Characterizing Stationary Points, Search for Transition States. Optimization:- multivariable Optimization Algorithms, level Sets, Level Curves, Gradients, Optimization Criteria, Unidirectional Search, Finding Minimum Point, Gradient based Methods-Steepest Descent and Conjugate Gradient Methods

A d v e r t i s e m e n t
Module-3 Molecular Dynamics Simulation 0 hours

Molecular Dynamics Simulation:

Introduction, Radial distribution functions, Pair Correlation function, Newtonian dynamics, Integrators- Leapfrog and Verlet algorithm, Potential truncation and shifted-force potentials, Implicit and explicit Solvation models, Periodic boundary conditions, Temperature and pressure control in molecular dynamics simulations

Module-4 Molecular modeling in Drug design 0 hours

Molecular modeling in Drug design:

Conformational analysis, lead identification, optimization and validation. Methods and Tools in Computer-aided molecular Design, Analog Based drug design:-Pharmacophores and QSAR. Structure based drug design:- Docking, De Novo Drug Design, Virtual screening.

Module-5 Structure Activity Relationship 0 hours

Structure Activity Relationship:

Introduction to QSAR, QSPR, Various Descriptors used in QSARs, Regression Analysis, Significance and Validity of QSAR Regression Equations, Partial Least Squares (PLS) Analysis, Multi Linear Regression Analysis. Application of Genetic Algorithms, Neural Networks and Principle Components Analysis in QSAR analysis.

 

Course outcomes:

At the end of the course the student will be able to:

  • Understand the basic principles of biomolecular simulations
  • Appreciate and apply the various algorithms used for diverse applications.
  • Understand the utilities of various tools and their multitude of applications.

 

Question paper pattern:

The SEE question paper will be set for 100 marks and the marks scored will be proportionately reduced to 60.

  • The question paper will have ten full questions carrying equal marks.
  • Each full question is for 20 marks.
  • There will be two full questions (with a maximum of four sub questions) from each module.
  • Each full question will have sub question covering all the topics under a module.
  • The students will have to answer five full questions, selecting one full question from each module.

 

Textbook/ Textbooks

1 Computational Chemistry and Molecular Modelling-Principles and Applications Ramachandran, Deepa and Namboodri, Springer_Verlag. 2008

2 Mathematical Approaches to Biomolecular Structure and Dynamics Jill P. Mesirov, Klaus Schulten, De Witt L. Sumners Springer 1996.

 

Reference Books

1 Molecular Modeling for Beginners. Alan Hinchliffe John Wiley & Sons Ltd. (2nd Edition), 2008

2 Foundations of Molecular Modeling and Simulation. Peter T. Cummings, Phillip R.Westmorland, Brice Carnahan, American Institute of Chemical Engineers 2001

3 New Algorithms for Macromolecular Simulation Timothy J. Barth, Michael Griebel, David E.Keyes, Risto M. Nieminen, Dirk Roose, Tamar Schlick, Springer 2011

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