ArticleBMC bioinformatics2008
The contrasting properties of conservation and correlated phylogeny in protein functional residue prediction.
Article in BMC bioinformatics, 2008. 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.
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- The Dundee Resource for Sequence Analysis and Structure Prediction.Protein science : a publication of the Protein Society · 2020Article
- Sequence-based prediction of physicochemical interactions at protein functional sites using a function-and-interaction-annotated domain profile database.BMC bioinformatics · 2018Article
- JABAWS 2.2 distributed web services for Bioinformatics: protein disorder, conservation and RNA secondary structure.Bioinformatics (Oxford, England) · 2018Article
- Dynamic roles for the N-terminus of the yeast G protein-coupled receptor Ste2p.Biochimica et biophysica acta. Biomembranes · 2017Article
- Uncovering missing pieces: duplication and deletion history of arrestins in deuterostomes.BMC evolutionary biology · 2017Article
- Sequence specificity between interacting and non-interacting homologs identifies interface residues--a homodimer and monomer use case.BMC bioinformatics · 2015Article
- Computational analysis of C-reactive protein for assessment of molecular dynamics and interaction properties.Cell biochemistry and biophysics · 2013Article
- Comparison of different ranking methods in protein-ligand binding site prediction.International journal of molecular sciences · 2012Article
- A new protein-ligand binding sites prediction method based on the integration of protein sequence conservation information.BMC bioinformatics · 2011Article
- Functionally important positions can comprise the majority of a protein's architecture.Proteins · 2011Article
- Networks of high mutual information define the structural proximity of catalytic sites: implications for catalytic residue identification.PLoS computational biology · 2010Article
- Conserved residue clusters at protein-protein interfaces and their use in binding site identification.BMC bioinformatics · 2010Article
- Comparing the functional roles of nonconserved sequence positions in homologous transcription repressors: implications for sequence/function analyses.Journal of molecular biology · 2010Article
- SitesIdentify: a protein functional site prediction tool.BMC bioinformatics · 2009Article
- Combining specificity determining and conserved residues improves functional site prediction.BMC bioinformatics · 2009Article
- Characterization and prediction of residues determining protein functional specificity.Bioinformatics (Oxford, England) · 2008Article
- Exploring the structure and function paradigm.Current opinion in structural biology · 2008Review
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Abstract
backgroundAmino acids responsible for structure, core function or specificity may be inferred from multiple protein sequence alignments where a limited set of residue types are tolerated. The rise in available protein sequences continues to increase the power of techniques based on this principle.
resultsA new algorithm, SMERFS, for predicting protein functional sites from multiple sequences alignments was compared to 14 conservation measures and to the MINER algorithm. Validation was performed on an automatically generated dataset of 1457 families derived from the protein interactions database SNAPPI-DB, and a smaller manually curated set of 148 families. The best performing measure overall was Williamson property entropy, with ROC0.1 scores of 0.0087 and 0.0114 for domain and small molecule contact prediction, respectively. The Lancet method performed worse than random on protein-protein interaction site prediction (ROC0.1 score of 0.0008). The SMERFS algorithm gave similar accuracy to the phylogenetic tree-based MINER algorithm but was superior to Williamson in prediction of non-catalytic transient complex interfaces. SMERFS predicts sites that are significantly more solvent accessible compared to Williamson.
conclusionWilliamson property entropy is the the best performing of 14 conservation measures examined. The difference in performance of SMERFS relative to Williamson in manually defined complexes was dependent on complex type. The best choice of analysis method is therefore dependent on the system of interest. Additional computation employed by Miner in calculation of phylogenetic trees did not produce improved results over SMERFS. SMERFS performance was improved by use of windows over alignment columns, illustrating the necessity of considering the local environment of positions when assessing their functional significance.
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