Recognition of related proteins by iterative template refinement (ITR)

Recognition of related proteins by iterative template refinement (ITR) Predicting the structural fold of a protein is an important and challenging problem. Available computer programs for determining whether a protein sequence is compatible with a known 3‐dimensional structure fall into 2 categories: (1) structure‐based methods, in which structural features such as local conformation and solvent accessibility are encoded in a template, and (2) sequence‐based methods, in which aligned sequences of a set of related proteins are encoded in a template. In both cases, the programs use a static template based on a predetermined set of proteins. Here, we describe a computer‐based method, called iterative template refinement (ITR), that uses templates combining structure‐based and sequence‐based information and employs an iterative search procedure to detect related proteins and sequentially add them to the templates. Starting from a single protein of known structure, ITR performs sequential cycles of database search to construct an expanding tree of templates with the aim of identifying subtle relationships among proteins. Evaluating the performance of ITR on 6 proteins, we found that the method automatically identified a variety of subtle structural similarities to other proteins. For example, the method identified structural similarity between arabinose‐binding protein and phosphofructokinase, a relationship that has not been widely recognized. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Protein Science Wiley

Recognition of related proteins by iterative template refinement (ITR)

Protein Science, Volume 3 (8) – Aug 1, 1994

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Publisher
Wiley
Copyright
Copyright © 1994 The Protein Society
ISSN
0961-8368
eISSN
1469-896X
DOI
10.1002/pro.5560030818
pmid
7987226
Publisher site
See Article on Publisher Site

Abstract

Predicting the structural fold of a protein is an important and challenging problem. Available computer programs for determining whether a protein sequence is compatible with a known 3‐dimensional structure fall into 2 categories: (1) structure‐based methods, in which structural features such as local conformation and solvent accessibility are encoded in a template, and (2) sequence‐based methods, in which aligned sequences of a set of related proteins are encoded in a template. In both cases, the programs use a static template based on a predetermined set of proteins. Here, we describe a computer‐based method, called iterative template refinement (ITR), that uses templates combining structure‐based and sequence‐based information and employs an iterative search procedure to detect related proteins and sequentially add them to the templates. Starting from a single protein of known structure, ITR performs sequential cycles of database search to construct an expanding tree of templates with the aim of identifying subtle relationships among proteins. Evaluating the performance of ITR on 6 proteins, we found that the method automatically identified a variety of subtle structural similarities to other proteins. For example, the method identified structural similarity between arabinose‐binding protein and phosphofructokinase, a relationship that has not been widely recognized.

Journal

Protein ScienceWiley

Published: Aug 1, 1994

References

  • Statistical methods and insights for protein and DNA sequences
    Karlin, Karlin; Bucher, Bucher; Brendel, Brendel

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