Standard Article

Measuring evolutionary constraints as protein properties reflecting underlying mechanisms

Part 4. Bioinformatics

4.3. Protein Function and Annotation

Short Specialist Review

  1. Andrew F. Neuwald1,
  2. Jun S. Liu2

Published Online: 15 JUL 2005

DOI: 10.1002/047001153X.g403310

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Neuwald, A. F. and Liu, J. S. 2005. Measuring evolutionary constraints as protein properties reflecting underlying mechanisms. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.3:35.

Author Information

  1. 1

    Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA

  2. 2

    Harvard University, Cambridge, MA, USA

Publication History

  1. Published Online: 15 JUL 2005

Abstract

Selective constraints are revealed in protein multiple sequence and structural alignments as conserved residues and corresponding atomic interactions. These patterns of conservation contain implicit information about underlying protein mechanisms, just as crystalline X-ray diffraction patterns contain implicit information about a protein's structure. Contrast hierarchical alignment and interaction network (CHAIN) analysis measures and characterizes selective constraints on the basis of co-conserved patterns and fits mechanistic models to these and other constraints. Just as the quantity and quality of X-ray diffraction patterns determines how well one can fit an atomic model to the inferred electron density, the quantity and quality of co-conserved patterns determines how well one can fit possible mechanisms to these inferred constraints. In principle, given sufficient data, biological mechanisms may be identified with high certainty. Nevertheless, even at “low resolution”, this information can prune the possibilities down to a manageable number for further experimental follow-up.

Keywords:

  • Bayesian partitioning with pattern selection (BPPS);
  • Markov chain Monte Carlo methods;
  • CHAIN analysis;
  • contrast hierarchical alignment