Molecular Dynamics 0800-DYNAMO

An outline:

1. What is molecular dynamics - a historical note.
2. Hamilton equations of motion. The Langragian.
3. The phase space concept.
4. Liouville space, trajectories.
5. Basic facts from quantum mechanics revisited.
The Born- Oppenheimer approximation.
6. A concept of potential energy surface (PES).
7. A force field as a classical approximation to PES.
8. Newton's equations of motions.
9. Langevin dynamics.
10. Formal classification of dynamical systems.
11. Chaotic motion, ergodicity.
12. Detailed description of CHARMM forcefield.
13. Parametrisation problem. New developements.
13. AMBER forcefield is best suited for DNA.
14. GROMOS and its peculiarities.
15. Computer models of water. Open problems.
16. Attempts to construct the Universal FF.
17. Other options for the second generation force fields.
18. Information flow in a typical MD code.
19. Periodic vs stochastic boundary conditions.
20. Ewald and Partial Ewald summation methods.
21. Geometry optimization: multiple minima problem.
22. Algorithms: steepest descent, conjugate gradients, others.
23. The Powell algorithm.
24. Features of "good" numerical integration algorithms.
25. Classical methods of numerical integration. Monte Carlo.
26. Verlet algorithms.
27. Beeman algorithm.
28. GPU specific intergrators.
29. Temperature and pressure in MD. Nose-Hoover thermostat. Langevin piston.
30. Useful tricks: Shake i Rattle.
31. Role of PDB in the MD community.
31. A protocol for a classical MD simulation.
32. Examples of applications of MD in proteins and nanosystems modeling.
33. Entropy in MD. Free energy concept.
34. Zwanzing method to calculate free energy changes.
35. Potential of mean force.
36. Jarzynski theorem.
37. Applications of Jarzynski theorem. An experimental proof based on optical tweezers with RNA experiment.
38. How to calculate PMF effectively.
39. Advanced variants of MD.
40. Locally Enhanced Sampling equations.
41. LES - applications
42. Replica Exchange MD.
43. Meta-dynamics.
44. Excited states MD. The Landau-Zener approximation.
45. Steered MD. Applications of SMD in nanomechanics.
46. MD and GPU.
47. MD and computer graphics.
48. MD and scientific news, discoveries.
49. Role of MD in drug design. Docking of ligands.
50. Future prospects, 1 mln atoms simulations, viruses in computers.

Total student workload

30 h - participation in lectures (optional) 30 h - practical exercises, (lab, obligatory) 30h - preparations for the exam, MD project

Learning outcomes - knowledge

- The student has basic knowledge of Physics corresponding to the second cycle programme level as well as advanced knowledge of molecular dynamics simulations as a part of theoretical physics. - The student knows advanced research and numerical methods that allow to plan and carry out a complex physical simulations experiment, with particular emphsis on bionanomaterials.

Learning outcomes - skills

-The student is able to use scientific methods in problem-solving, conducting computer experiments and conclusive reasoning. - The student is able to perform simulations of proteins dynamis. - The student is able to perform a critical analysis of simulations results as well as to assess the accuracy of results.

Learning outcomes - social competencies

The students understand the need for promoting knowledge of Physics, including the latest scientific and technological developments in computer simulations. They know the link between science and health issues (computer assisted drug design). The student is able to work both individually and as a member of a team and is aware of the responsibility for jointly implemented tasks.

Teaching methods

The classical lecture with mutimedia enhamcements (simulations, colour slides etc). Brain storms. Computer exercises. A small scientific research project.

Observation/demonstration teaching methods

- simulation (simulation games)

Expository teaching methods

- problem-based lecture
- informative (conventional) lecture

Exploratory teaching methods

- experimental
- practical
- project work
- brainstorming

Type of course

compulsory course

Prerequisites

BSc diploma or equivalent in science (physics, chemistry, mathematics, etc.). Basic knowledge of calcula and algebra.

Course coordinators

Wiesław Nowak

Assessment criteria

Lecture: Results of exam will decide about the final note. One has to:
- descibe theoretical methods presented in the course,
- understand correctly the nature of approximations used,
- know at least a few modern methods of molecular dynamics simulations (SMD, RED etc.)
- show some examples of typical appllications of MD methods

Practical: one mid-term report and one final report are expected.
The final report should contain results of a small reserach project conducted in students teams.
Good quality an extensive work will be enumerated.
The presence at prectical classes is obligatory.

Practical placement

none

Bibliography

1. Daan Frenkel, Berend Smit, "Understanding Molecular Simulation, Second Edition: From Algorithms to Applications (Computational Science) Academic Press, 2001
2. Haile, J. M., “Molecular Dynamics Simulation: Elementary Methods”, John Wiley & Sons, Inc.: New York, ISBN 0471819662, 1992.
3. Hinchliffe, A., “Molecular Modelling for Beginners”, 2nd edition; John Wiley & Sons, Ltd: Chichester, ISBN 9780470513149, 2008.
4. A.Hinchliffe „Modeling Molecular Structures”, Wiley, Chichester, 1996.
5. J. Foresman, A, Frish, „Exploring Chemistry with Electronic Structure Methods”, 2nd Ed. Gaussian Inc. , Pittsburgh, USA, 1996.
6. L. Piela, „Idee chemii kwantowej”, PWN, Warszawa, 2009.
7. D. C. Rapaport, "The Art of Molecular Dynamics Simulation Hard, Cambridge 2004
8. Doucet, J.-P.; Weber, J., “Computer-Aided Molecular Design”, Academic Press, London, ISBN 0122212851,1996.
9. A. R. Leach, "Molecular Modelling: Principles and Applications", 2001, ISBN 0-582-38210-6.
10. M. Griebel, S. Knapek, Stephan, G. Zumbusch, "Numerical Simulation in Molecular Dynamics", Series: Texts in Computational Science and Engineering, Vol. 5, Springer, 2007.
11. W. Nowak, “Applications of computational methods to simulations of proteins dynamics”, w “Handbook of Computational Chemistry”, Springer, 2012 – a book chapter, pp.129-1149. (ISBN 978-94-007-0712-2).
12. W. Nowak, „Molecular modeling - interdisciplinary approach" - unpublished pdf.
13. Review articles indicated during the lecture

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 0800-DYNAMO in USOSweb