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Studying Bioinformatics in Saarbrücken
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Proseminar Bioinformatik:

Biomolecular Simulations

Winter Term 03/04


Lecturer: Prof. Dr. Volkhard Helms, Wei Gu, Yungki Park

Blockseminar: Friday, January 23rd, 2 pm

Requirements: basic knowledge of Computational Chemistry

Timetable: Friday, January 23rd

The "Scheine" are available in building 17.1, room 1.05 between 9:00 am and 12:00 am (mo - fr).

Projects for student presentations:

  1. Force fields (Sandra Fischer)
  1. All-atom empirical potential for molecular modeling and dynamics studies of proteins. J. Phys. Chem:, B 102, 3586-3617, (1998) (CHARMM, PROTEIN, ALL-ATOM)
  2. An all-atom empirical energy function for the simulation of nucleic acids. J. AM. Chem. Soc. 117, 11946-11975, (1995) (CHARMM, NA)
  3. van Gunsteren, W. F., Daura, X. and Mark, A. E. (1997) "The GROMOS force field" In Encyclopaedia of Computational Chemistry (GROMOS, PROTEIN, JOINT-ATOM)
  1. MD algorithms
  1. H. J. Berendsen, J. P. M. Postma, W. F. van Gunsteren, A. Di Nola and J. R. Haak: "Molecular Dynamics with Coupling to an External Bath", J. Chem. Phys. 81, 3684-3690, (1984) (TEMP, PRES COUP)
  2. J. P. Ryckaert, "Special Geometrical Constraints in the Molecular Dynamics of Chain Molecules", Molec. Phys. 55, 549-556, (SHAKE)
  3. P. A. Kollman, "Free Energy Calculations: Applications to Chemical and Biochemical Phenomena." Chem.Rev. 93, 2395, (FREE ENERGY)
  1. Solvation Models
  1. Evaluation of a Fast Implicit Solvent Model for Molecular Dynamics Simulations, Proteins, 46, 24-33
  2. Comparison of Generalized Born and Poisson Models: Energetics and Dynamics of HIV Protease, J. Comp. Chem., 21(4), 295-309
  3. Effective Energy Function for Proteins in Solution, Proteins, 35, 133-152
  1. Long-range forces
  1. P. J. Steinbach and B. R. Brooks, "New Spherical-Cutoff Methods for Long-Range Forces in Macromolecular Simulation", J. Comp. Chem., 15, 667, (1994) (CUTOFF)
  2. I. G. Tironi, R. Sperb, P. E. Smith, W. F. van Gunsteren, J. Chem. Phys. 102, 5451, (1995) (REACTION FIELD)
  3. T. A. Darden, D. M. York, L. G. Pedersen. Particle mesh Ewald: "An. N.log(N) method for Ewald sums in large systens."J. Chem. Phys., 98, 10089-10092 (1993) (PME)
  1. Conformational sampling, local enhanced sampling (Thomas Binsl)
  1. B. Roux "The calculation of the potential of mean force using computer simulations", Comp. Phys. Commun., 91, 275, (1995) (PMF)
  2. Sugita Y., Okamoto Y.: Replica Exchange molecular dynamics method for protein folding", Chem. Phys. Lett., 314, 141-151, (1999) (MULTI-REPLICA)
  3. G. M. Torrie and J. P. Valleau, J. Comp. Phys., 23, 187, (1977) (UMBRELLA-SAMPLING)
  1. Steered Molecular Dynamics
  1. http://www.sfu.ca/physics/biophysics_school/materials/Schulten/SMD.pdf
  2. Energetics of glycerol conduction though aquaglyceroporin GlpF, PNAS, 99 (10), 6731-6736
  3. Gatting of MscL Studied by Steered Molecular Dynamics, Biophysical Journal, 85 (4), 2087-2099
  1. Normal model calculations
  1. K. Hinsen: "Analysis of domain motions by approximate normal mode calculations", Proteins, 33, 417-429 (1998)
  2. K. Hinsen, A. Thomas, M. J. Field: "Analysis of domain motions in large proteins", Proteins, 34, 369-382 (1999)
  1. Long-time Dynamics
  1. Principal Component Analysis and Long Time Protein Dynamics, Journal of Physical Chemistry, 100, 2567-2672 (1996)
  2. Kinetics of Cytochrome C Folding: Atomically Detailed Simulations, Proteins, 51, 245-257
  1. Membrane Simulations (Bettina Schneider)
  1. Membrane simulations: bigger and better? Current Opinion in Structural Biology, 10, 174-181
  2. Oren M. Becker, Alexander D. MacKerell, Jr., Benoit Roux, Masakatsu Watanabe: Computational Biochemistry and Biophysics, Marcel Dekker, Inc., 465-496
  3. Structure and Dynamics of the Pore-Lining Helix of the Nicotinic Receptor: MD Simulations in Water, Lipid Bilayers and Transbilayers Bundles, Proteins, 39, 47-55
  1. Protein Folding Simulations (Oliver Müller)
  1. Folding simulations of a three-stranded antiparallel beta-sheet peptide, PNAS, 97 (20), 10780-10785
  2. Replica exchange molecular dynamics simulations of reversible folding, Journal of Chemical Physics, 119 (7), 4035-4042
  3. Replica exchange molecular dynamics method for protein folding, Chemical Physics Letters, 314, 141-151
  1. Statistical Potentials
  1. Knowledge-based potentials for proteins, Current Opinion in Structural Biology, 5, 229-235
  2. Structure-derived potentials and protein simulations, Current Opinion in Structural Biology, 6,195-209
  3. Statistical potentials for fold assessment, Protein Science, 11, 430-448
  1. Structure Prediction for Proteins (Yasir Iqbal)
  1. Comparative Protein structure modeling of genes and genomes, Annual Review of Biophysics and Biomolecular Structure, 29, 291-325
  2. Tools for comparative protein structure modeling and analysis, Nucleic Acids Research, 31, 3375-3380
  3. Protein structure prediction in 2002, Current Opinion in Structural Biology, 12, 348-354
  1. de novo design (Weng In Siu)
  1. D. B. Gordon, S. A. Marshall and S. L. Mayo: Energy Functions for Protein Design, Current Opinion in Structural Biology, 9, 509-513 (1999)
  2. D. B. Gordon and S. L. Mayo: Branch-and-Terminate: A Combinatorial Optimization Algorithm for Protein Design, Structure with Folding and Design, 7, 1089-1098 (1999)
  3. N. A. Pierce, J. A. Spriet, J. Desmet, S. L. Mayo: Conformational Splitting: A More Powerful Criterion for Dead-End Elimination, Journal for Computational Chemistry, 21, 999-1009 (2000)
  1. Protein-Ligand Interactions (Susanne Pfeifer)
  1. Principles of Docking: An Overview of Search Algorithms and a Guide to Scoring Functions, Proteins, 47, 409-443, (2002) (DOCKING)
  2. Ligand docking and screening with FlexX, Med. Chem. Res., 7/8, 463-478 81999) (FlexX)
  1. Brownian Dynamics Simulations
  1. D. L. Ermak and J. A. McCammon: Brownian dynamics with hydrodynamic interaction, J. Chem. Phys., 69, 1352 (1978)
  2. J. K. G. Dhont: An Introduction to Dynamics of Colloids, Elsevier Science, Amsterdam (1996)