Computational Biochemistry

84.567:201, Spring 2007

Lectures: 2:00am - 3:15pm, Tuesday and Thursday
Instructor: Dr. Valeri Barsegov
Office: Room 401B, Olney Hall
Phone: 978-934-3661
Email: Valeri_Barsegov@uml.edu

Description: The course offers an introduction to various computational methods for simulating biological macromolecules, such as proteins, DNA, and RNA. It is designed for graduate and senior undergraduate students, who are interested in computational biology and whose background is in biology, physics, chemistry, computer science, or mathematics.

Course Outline (see downloadable 'Lectures')

Part 1: Introduction to Biomolecules (10 lectures)

  1. Computer Simulations as a New Tool for Scientific Research
  2. Problems in Computational Biology
    • Bioinformatics: From sequence to structure
    • Protein folding
    • Protein misfolding (aggregation)
    • Single molecule force-induced unfolding and unbinding
  3. Protein Architecture
    • Sequence of amino acids
    • Secondary structure of proteins
    • Tertiary structure of proteins
      • alpha-helices
      • beta-strands
      • variety of protein native folds
    • "Catalog" of protein interactions
  4. Nucleic Acid Structure
    • Building blocks of DNAs
    • Interactions and conformations of DNAs
    • RNA

Part 2: Computer Simulations of Biomolecules (18 lectures)

  1. Foundations of Biomolecular Simulations
    • Classical versus quantum descriptions
    • Statistical mechanics of biomolecules (e.g., canonical ensemble, ergodicity)
    • Assumptions in biomolecular simulations
  2. Modeling Interactions in Proteins
    • Bond-length and bond-angle potentials
    • Dihedral angle potential
    • Non-bonded interactions
  3. Computation of Non-bonded Energy Terms
    • Distance cut-offs
    • Ewald method for electrostatic interactions
    • Implicit solvent models
  4. Molecular Dynamics Simulations
    • Idea of MD
    • Structure of MD code
      • Initialization
      • Force computation
      • Numerical integration of Newton equations of motion (Verlet algorithms)
      • Constraints in MD (RATTLE, SHAKE)
    • Simulating different ensembles
      • Microcanonical (NVE) ensemble
      • Canonical (NVT) ensemble (Andersen and Nose-Hoover thermostats)
      • Isobaric-isothermal (NPT) ensemble
    • Langevin dynamics
    • MD program packages (CHARMM, NAMD, AMBER)
    • Practical tips on setting and running MD simulations

Recommended Books

  • D. Frankel and B. Smit "Understanding Molecular Simulations: From Algorithms to Applications"
  • T. E. Creighton "Proteins" (2nd edition, W.H. Freeman, and Co., New York)

Grading Basis

Homework: 50%, Class presentation: 50%

[Lectures]