BIOC 670

Structural Bioinformatics

Instructor: Brian Kuhlman; 919-843-0188, bkhuhlman@med.unc.edu

Meeting Dates/Times and Locations: 1/7/15-2/9/15; 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.

Homology modeling (predicting structure based on the structure of a related protein)

Fold recognition

Sequence alignments in the context of structure prediction

Loop modeling / refining low-resolution models

De novo structure prediction (predicting protein structures from scratch)

Real-time protein folding simulations / molecular dynamics

Knowledge based approaches/Rosetta

Domain parsing (finding structural domains in genes)

Structure to Function

Algorithms for structure comparison

Motif identification

Protein – protein docking

Search protocols

Scoring functions

Protein Design

Algorithms for sequence optimization

Energy functions for protein design

Integration of experimental and computational techniques in structural genomics projects. Protein Data Bank. Overview of experimental structure determination: NMR, X-ray crystallography.

The taxonomy of protein structure. Algorithms for structure comparison and fold classification schemes.

Empirical and statistical macromolecular force fields for structure simulation and prediction.

The complexity of the protein folding problem; Protein folding simulations.

Knowledge-Based Protein Homology Modeling. Sequence alignment in the context of structure prediction.

Fold recognition approach to structure prediction. The ongoing challenge on Critical Assessment of Structure Prediction (CASP): Successes and failures.

Protein design and stability.

The relationship between protein structure and function. Computational structural genomics approaches to function prediction.

Computational Approaches to Structure-Based Drug Design: Methods and Applications.