ArticleBMC bioinformatics2009
SitesIdentify: a protein functional site prediction tool.
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 11 papers.
What it found
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Who cites it
11 citing papers in PubMed.
- Comparative evaluation of methods for the prediction of protein-ligand binding sites.Journal of cheminformatics · 2024Article
- Article
- Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms.PloS one · 2016Article
- Rsite: a computational method to identify the functional sites of noncoding RNAs.Scientific reports · 2015Article
- Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently.Chemical Society reviews · 2015Review
- Biochemical functional predictions for protein structures of unknown or uncertain function.Computational and structural biotechnology journal · 2015Review
- Recent advances in functional region prediction by using structural and evolutionary information - Remaining problems and future extensions.Computational and structural biotechnology journal · 2013Review
- Top-down clustering for protein subfamily identification.Evolutionary bioinformatics online · 2013Article
- Computational tools for the synthetic design of biochemical pathways.Nature reviews. Microbiology · 2012Review
- Prediction of functionally important residues in globular proteins from unusual central distances of amino acids.BMC structural biology · 2011Article
- Knowledge-based annotation of small molecule binding sites in proteins.BMC bioinformatics · 2010Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundThe rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application.
resultsHere we present a functional site prediction tool (SitesIdentify), based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites.
conclusionSitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/
Indexed as
Identifiers
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Registered trials
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