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Instructor: Andrew Leaver-Fay (leaverfa@email.unc.edu)

Meeting Dates: 01/11/2022 – 02/10/2022

Times: TTh 11:00AM-12:15PM

Location: TBD

BIOC 670 Syllabus

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.