A Unified Approach to the Prediction of Protein Structure and Function

  1. Richard A. Friesner
  1. Jeffrey Skolnick1,
  2. Andrzej Kolinski1,2

Published Online: 13 MAR 2002

DOI: 10.1002/0471224421.ch4

Computational Methods for Protein Folding, Volume 120

Computational Methods for Protein Folding, Volume 120

How to Cite

Skolnick, J. and Kolinski, A. (2002) A Unified Approach to the Prediction of Protein Structure and Function, in Computational Methods for Protein Folding, Volume 120 (ed R. A. Friesner), John Wiley & Sons, Inc., New York, USA. doi: 10.1002/0471224421.ch4

Editor Information

  1. Columbia University, New York, New York, USA

Author Information

  1. 1

    Laboratory of Computational Genomics, Danforth Plant Science Center, Creve Coeur, MO, U.S.A.

  2. 2

    Department of Chemistry, University of Warsaw, Warsaw, Poland

Publication History

  1. Published Online: 13 MAR 2002
  2. Published Print: 4 JAN 2002

Book Series:

  1. Advances in Chemical Physics

Book Series Editors:

  1. I. Prigogine4,5,
  2. Stuart A. Rice6

Series Editor Information

  1. 4

    Center for Studies in Statistical Mechanics and Complex Systems, The University of Texas, Austin, Texas, USA

  2. 5

    International Solvay Institutes, Université Libre de Bruxelles, Brussels, Belgium

  3. 6

    Department of Chemistry and The James Franck Institute, The University of Chicago, Chicago, Illinois, USA

ISBN Information

Print ISBN: 9780471209553

Online ISBN: 9780471224426

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Keywords:

  • protein structure;
  • unified folding scheme;
  • threading;
  • comparative models;
  • ab initio folding;
  • reduced models;
  • atomic models;
  • biochemical function;
  • low-resolution structures;
  • ligand identification

Summary

The major focus of this review is to describe a unified approach to protein structure prediction that reduces to threading plus structure refinement when an example of the probe sequence is found; but if not, it incorporates information from weakly significant probe sequence-template structure matches and then does ab initio folding with the structural information gleaned from such matches. It has the advantage that it can predict a novel fold even though some of the information comes from threading on already solved structures.