Biochem 670

Structural bioinformatics

Cross-listed as PBCB 717: Kuhlman, 843-0188, bkuhlman@email.unc.edu; 1/8/14-2/10/14; T, Th 9:30-11:00AM, 3007 Genetics Medicine

This module will introduce methods and techniques for predicting a proteins structure and function from its sequence.  Techniques that will be covered include homology modeling, de novo structure prediction, protein-protein docking, predicting function from structure, and protein design.  It will consist of nine lectures (1.5 h each), homework assignments and an exam.

  1. Homology modeling (predicting structure based on the structure of a related protein)
  1. Fold recognition
  2. Sequence alignments in the context of structure prediction
  3. Loop modeling / refining low-resolution models
  1. De novo structure prediction (predicting protein structures from scratch)
    1. Real-time protein folding simulations / molecular dynamics
    2. Knowledge based approaches  / Rosetta
  2. Domain parsing (finding structural domains in genes)
  3. Structure to Function
    1. Algorithms for structure comparison
    2. Motif identification
  4. Protein – protein docking
    1. Search protocols
    2. Scoring functions
  5. Protein Design
    1. Algorithms for sequence optimization
    2. Energy functions for protein design
      1. Integration of experimental and computational techniques in structural genomics projects. Protein Data Bank.  Overview of experimental structure determination: NMR, X-ray crystallography.
      2. The taxonomy of protein structure. Algorithms for structure comparison and fold classification schemes.
      3. Empirical and statistical macromolecular force fields for structure simulation and prediction.
      4. The complexity of the protein folding problem; Protein folding simulations.
      5. Knowledge-Based Protein Homology Modeling.  Sequence alignment in the context of structure prediction.
      6. Fold recognition approach to structure prediction. The ongoing challenge on Critical Assessment of Structure Prediction (CASP): Successes and failures.
      7. Protein design and stability.
      8. The relationship between protein structure and function.  Computational structural genomics approaches to function prediction.
      9. Computational Approaches to Structure-Based Drug Design: Methods and Applications.