ArticleBMC bioinformatics2009
Combining specificity determining and conserved residues improves functional site prediction.
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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20 citing papers in PubMed.
- Article
- Deep Analysis of Residue Constraints (DARC): identifying determinants of protein functional specificity.Scientific reports · 2020Article
- Porphyromonas gingivalis Tyrosine Phosphatase Php1 Promotes Community Development and Pathogenicity.mBio · 2019Article
- Molecular mechanisms of the protein-protein interaction-regulated binding specificity of basic-region leucine zipper transcription factors.Journal of molecular modeling · 2019Article
- Recognition of sites of functional specialisation in all known eukaryotic protein kinase families.PLoS computational biology · 2018Article
- Article
- Inference of Functionally-Relevant N-acetyltransferase Residues Based on Statistical Correlations.PLoS computational biology · 2016Article
- pocketZebra: a web-server for automated selection and classification of subfamily-specific binding sites by bioinformatic analysis of diverse protein families.Nucleic acids research · 2014Article
- Principal components analysis of protein sequence clusters.Journal of structural and functional genomics · 2014Article
- Emerging methods in protein co-evolution.Nature reviews. Genetics · 2013Review
- CLIPS-1D: analysis of multiple sequence alignments to deduce for residue-positions a role in catalysis, ligand-binding, or protein structure.BMC bioinformatics · 2012Article
- Functionally important positions can comprise the majority of a protein's architecture.Proteins · 2011Article
- Molecular dynamics and docking simulations as a proof of high flexibility in E. coli FabH and its relevance for accurate inhibitor modeling.Journal of computer-aided molecular design · 2011Article
- Comparative Bioinformatic Analysis of Active Site Structures in Evolutionarily Remote Homologues of α,β-Hydrolase Superfamily Enzymes.Acta naturae · 2011Article
- An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies.Algorithms for molecular biology : AMB · 2010Article
- Multi-Harmony: detecting functional specificity from sequence alignment.Nucleic acids research · 2010Article
- Comparing the functional roles of nonconserved sequence positions in homologous transcription repressors: implications for sequence/function analyses.Journal of molecular biology · 2010Article
- CASBench: A Benchmarking Set of Proteins with Annotated Catalytic and Allosteric Sites in Their Structures.Acta naturaeArticle
- Predicting mutational function using machine learning.Mutation research. Reviews in mutation researchReview
- Article
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Authors and funding
3 authors.
Funding
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.
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