ArticlePLoS computational biology2008
Protein meta-functional signatures from combining sequence, structure, evolution, and amino acid property information.
Article in PLoS computational biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Deconvolving mutation effects on protein stability and function with disentangled protein language models.bioRxiv : the preprint server for biology · 2026Article
- Accurate informatic modeling of tooth enamel pellicle interactions by training substitution matrices with Mat4Pep.Frontiers in materials · 2024Article
- Discovering functionally important sites in proteins.Nature communications · 2023Article
- CSmetaPred: a consensus method for prediction of catalytic residues.BMC bioinformatics · 2017Article
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- Exploring Polypharmacology in Drug Discovery and Repurposing Using the CANDO Platform.Current pharmaceutical design · 2016Review
- An overview of the prediction of protein DNA-binding sites.International journal of molecular sciences · 2015Review
- Basis for substrate recognition and distinction by matrix metalloproteinases.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
- Exome sequencing identifies a recurrent de novo ZSWIM6 mutation associated with acromelic frontonasal dysostosis.American journal of human genetics · 2014Article
- Structure prediction of partial-length protein sequences.International journal of molecular sciences · 2013Article
- Self-assembly of filamentous amelogenin requires calcium and phosphate: from dimers via nanoribbons to fibrils.Biomacromolecules · 2012Article
- Recognizing protein-ligand binding sites by global structural alignment and local geometry refinement.Structure (London, England : 1993) · 2012Article
- FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions.PloS one · 2012Article
- Article
- Pressurized pepsin digestion in proteomics: an automatable alternative to trypsin for integrated top-down bottom-up proteomics.Molecular & cellular proteomics : MCP · 2011Article
- Disease risk of missense mutations using structural inference from predicted function.Current protein & peptide science · 2010Article
- A protein sequence meta-functional signature for calcium binding residue prediction.Pattern recognition letters · 2010Article
- Defining the functional domain of programmed cell death 10 through its interactions with phosphatidylinositol-3,4,5-trisphosphate.PloS one · 2010Article
- Evolution: a guide to perturb protein function and networks.Current opinion in structural biology · 2010Review
- EasyMIFS and SiteHound: a toolkit for the identification of ligand-binding sites in protein structures.Bioinformatics (Oxford, England) · 2009Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Protein function is mediated by different amino acid residues, both their positions and types, in a protein sequence. Some amino acids are responsible for the stability or overall shape of the protein, playing an indirect role in protein function. Others play a functionally important role as part of active or binding sites of the protein. For a given protein sequence, the residues and their degree of functional importance can be thought of as a signature representing the function of the protein. We have developed a combination of knowledge- and biophysics-based function prediction approaches to elucidate the relationships between the structural and the functional roles of individual residues and positions. Such a meta-functional signature (MFS), which is a collection of continuous values representing the functional significance of each residue in a protein, may be used to study proteins of known function in greater detail and to aid in experimental characterization of proteins of unknown function. We demonstrate the superior performance of MFS in predicting protein functional sites and also present four real-world examples to apply MFS in a wide range of settings to elucidate protein sequence-structure-function relationships. Our results indicate that the MFS approach, which can combine multiple sources of information and also give biological interpretation to each component, greatly facilitates the understanding and characterization of protein function.
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