Preliminary Syllabus

Biophysics 298: Computation of Biological Molecules, Winter 2003

Instructor: Matt Jacobson [matt@cgl.ucsf.edu]

There will be 10 meetings of 2 hours each. I will provide an introduction at the beginning of class, and likely provide some summarization and other thoughts at the end. The rest of class will consist of presentations on specific topics, some conducted by me (and guest lecturers), but most by course participants. Based on the number of topics, I expect that each participant will present 2 topics. The goal of the presentations is to summarize in a concise fashion (no more than 15-20 minutes, to allow time for discussion) key papers, methods, researchers, and computer programs relevant to the topic. Ideally, these summaries will include critical comparisons of methods/models, brief examples of their application, and challenges for the future. You should expect to spend a substantial amount of time preparing for each topic you are in charge of presenting, including the time needed to read key references, synthesize the material concisely, prepare handouts or other visual aids, and enumerate a few possible topics for discussion. When you are not presenting, your only responsibilities are to read, or at least skim, the key references, and participate in discussions. If you take the course for a grade, it will be based on the quality of your presentations, attendance, and participation in discussions.

The topics and readings covered in each session are (tentatively) as follows. Slight adjustments may be made in accordance with participants’ interests or if the pace seems too rushed.

1. Organizational meeting. Assignment of topics. Possible tweaking of syllabus based on individual interests.

2. Force fields. [1/15]

· Topic 1: Fixed charge force fields (AMBER vs. OPLS vs. CHARMM; strategies for parameterization and validation). AMBER: Eli Groban; OPLS: Jerome Nilmeier

· Topic 2: Polarizable force fields (functional forms; parameterization; validation). Neema Salimi

· Topic 3: Atom-typing and partial charge estimation. Terry Downing

3. Solvent models I: Explicit solvent. [1/22]

· Topic 1: Explicit solvent models (SPC, TIP*; polarizable water models; methods of parameterization and validation). Jed Pitera

· Topic 2: Periodic boundary conditions (Ewald summation and its variants; non-cubic boundary conditions). Jed Pitera

· Topic 3: Explicit solvent without periodic boundaries. Jed Pitera

· Topic 4: Predicting buried waters. [possibly me]

4. Solvent models II: Implicit solvent. [1/29]

· Topic 1: Poisson-Boltzmann (methods of solution; linear vs. nonlinear; prediction of protonation states). Dave Savage

· Topic 2: Generalized Born models (volume and surface integral formulations; generalizations and simplifications). Ben Sellers

· Topic 3: Hydrophobic solvation (simple surface area based estimates; what is the actual physics of hydrophobic solvation?). Alenka Luzar

· Topic 4: Other implicit models (distance dependent dielectric; atomic solvation parameters).

5. Sampling methods I. Dynamics. [2/5]

· Topic 1: Integration methods (single and multiple timescale).

· Topic 2: Multiple temperature methods (simulated annealing and more complicated schemes). Mike Kim

· Topic 3: Approximate methods (Brownian and Langevin dynamics). Katarzyna Bernacki

6. Sampling methods II. Monte Carlo and global optimization. [2/12]

· Topic 1: Introduction to Monte Carlo sampling methods.

· Topic 2: Direct minimization (Cartesian vs. internal coordinate; Hessian-based minimization, and its role in sampling. [probably me]

· Topic 3: Monte Carlo in global optimization (Monte Carlo plus minimization, J- and S-walking). Vince Voelz

7. Sampling methods III. Analysis and applications. [2/19] Jed Pitera

· Topic 1: Analysis of trajectories (i.e., I’ve got a trajectory, now what do I do?; various ensemble averages; Principal Component Analysis).

· Topic 2: Applications to protein and peptide folding.

· Topic 3: Free energy methods (thermodynamic integration/free energy perturbation; potentials of mean force).

8. Mixed quantum/classical methods. [2/26] John Chodera, ???

9. Model building. [3/5]

· Topic 1: From experimental data (Xray and NMR; XPLOR). Hod Greeley

· Topic 2: Side chain optimization algorithms.

· Topic 3: Loop optimization algorithms.

· Topic 4: Homology modeling.

10. Intermolecular interactions. [3/12]

· Topic 1: Small molecule ligand docking.

· Topic 2: Protein-protein docking.

· Topic 3: Protein-DNA/RNA interactions.

· Topic 4: Cell membranes.