Molecular Modelling Methods

The lecture is dedicated to PhD students and student of natural sciences - physics, chemistry and biology, as well as applied mathematics and interdisciplinary sciences. Students should have basic knowledge in physics and applied informatics, in particular ability of programming in C++ and/or FORTRAN, as well as knowledge in basics of mathematical and computational modeling in natural sciences.

Basic computational physics/chemistry methods will be overviewed, including theories of atomic and molecular systems and mechanical models of macromolecular systems.

The basic purpose of this lecture is to teach molecular molecular modeling and bioinformatics methods, which should allow students studying biomolecular systems and processes. Students will have possibility to practice molecular modeling methods in the computer laboratory with the use of popular molecular modeling tools.

Plan of the lecture:

1. Basics of bioinformatics methods. From sequences of nucleic acids and proteins to their structures. Overview of methods which allow to predict 2D and 3D structures.
2. Hierarchical and multi-scale structure of biomolecular systems and processes.
3. Overview of quantum-mechanical methods which allow determination of microscopic quantum-mechanical interaction potentials between atomioc and molecular systems:
   • Born-Oppenheimer approximation
   • Hartree-Fock and Moeller-Plesset methods.
   • Configurational Interaction procedures.
   • Density Functional methods.
4. Studies of stability of biological molecules, in particular carriers of the genetic code, using molecular quantum-mechanical methods.
5. Quantum models of intermolecular interactions.
6. Methods of molecular mechanics (MM) and molecular dynamics (MD), and their applications in studies of nucleic acids and proteins.
7. Methods of quantum-classical molecular dynamics (QCMD) and their applications in simulations of enzymatic processes.
8. Basics of statistical physics and relations between mesoscopic and microscopic models and theories.
9. Monte-Carlo (MC) methods.
10. Free energy of biomolecular systems. Methods of its simulation.
11. Mezoscopic models of electrostatic fields in biomolecular systems. Poisson-Boltzmann (PB) and Generalized Born (GB) models.
12. Mezoscopic description of hydrophobic interactions.
13. Mechanisms of molecular recognition processes and structure-formation phenomena.
14. Selected topics in drug design.

Literature:

1. M.P.Allen & D.J.Tildesley, Computer Simulation of Liquids, Clarendon Press, Oxford, 1989.
2. J.M.Haile, Molecular Dynamics Simulation. Elementary Methods, John Wiley & Sons, Inc., New York, 1992.
3. R.W.Hockney & J.W.Eastwood, Computer Simulation Using Particles, McGraw Hill, New York, 1981.
4. A.R.Leach, Molecular Modelling: Principles and Applications (2nd Edition), Prentice Hall; ISBN: 0582382106, 2001.
5. B.Lesyng & J.A.McCammon, Molecular Modeling Methods. Basic Techniques and Challenging Problems, Pharmac.Ther., 60, 149-167, 1993.
6. B. Lesyng, Simulations of Biomolecular Systems and Processes: Perspectives and Limitations, in "Modelling and Simulation: A Tool for the Next Millenium", 13th European Simulation Multiconference, June 1-4, 1999, Warsaw, Poland. A Publication of the Society for Computer Simulation International, vol. 1, pp. 26-32, 1999.
7. B.Lesyng & W.Rudnicki, Molecular Modelling in Drug Design, in "Optimization of Aerosol Drug Delivery", Kluwer, Dordrech, 2003.
8. J.A.McCammon & S.Harvey, Dynamics of Proteins and Nucleic Acids, Cambridge University Press, Cambridge, 1987 .