Evidence map›Paper›PMID 19508719›Full record

ArticleBMC bioinformatics2009

Combining specificity determining and conserved residues improves functional site prediction.

Olga V Kalinina, Mikhail S Gelfand, Robert B Russell

Abstract read
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Article in BMC bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

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20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
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  9. Principal components analysis of protein sequence clusters.Journal of structural and functional genomics · 2014
    Article
  10. Emerging methods in protein co-evolution.Nature reviews. Genetics · 2013
    Review
  11. Article
  12. Article
  13. Article
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  18. Article
  19. Predicting mutational function using machine learning.Mutation research. Reviews in mutation research
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Olga V KalininaEMBL Heidelberg, Heidelberg, Germany. kalinina@embl.de
Mikhail S Gelfand
Robert B Russell

Funding

Howard Hughes Medical Institute 55005610
6 · The paper itself

Abstract

backgroundPredicting the location of functionally important sites from protein sequence and/or structure is a long-standing problem in computational biology. Most current approaches make use of sequence conservation, assuming that amino acid residues conserved within a protein family are most likely to be functionally important. Most often these approaches do not consider many residues that act to define specific sub-functions within a family, or they make no distinction between residues important for function and those more relevant for maintaining structure (e.g. in the hydrophobic core). Many protein families bind and/or act on a variety of ligands, meaning that conserved residues often only bind a common ligand sub-structure or perform general catalytic activities.

resultsHere we present a novel method for functional site prediction based on identification of conserved positions, as well as those responsible for determining ligand specificity. We define Specificity-Determining Positions (SDPs), as those occupied by conserved residues within sub-groups of proteins in a family having a common specificity, but differ between groups, and are thus likely to account for specific recognition events. We benchmark the approach on enzyme families of known 3D structure with bound substrates, and find that in nearly all families residues predicted by SDPsite are in contact with the bound substrate, and that the addition of SDPs significantly improves functional site prediction accuracy. We apply SDPsite to various families of proteins containing known three-dimensional structures, but lacking clear functional annotations, and discusse several illustrative examples.

conclusionThe results suggest a better means to predict functional details for the thousands of protein structures determined prior to a clear understanding of molecular function.

Indexed as

Amino Acid SequenceComputational BiologyConserved SequenceDatabases, ProteinProtein ConformationProteinsSequence Analysis, ProteinProteins

Identifiers

PMID19508719
PMCPMC2709924

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.