Using homology relations within a database markedly boosts protein sequence similarity search

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Abstract
Significance: In the field of protein structure prediction, identifying homology to known folds offers the most successful and practically useful strategy to provide protein spatial structure models. For protein sequence targets without closely related structures, even very distant homologs can provide reasonable templates for modeling. Despite significant progress in the field, remote sequence similarity search is far from perfection and fresh ideas are needed to extend detection limits. In computer science, the concept of utilizing internal relations within a database to improve similarity search was key to the success of search engines such as Google. Here, we show that similar consideration of the homology network within a protein database of structure templates can dramatically improve the accuracy of homology search.
Funding Information
  • HHS | National Institutes of Health (GM094575)
  • Welch Foundation (I-1505)

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