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Protein Meta-Functional Signatures from Combining Sequence, Structure, Evolution, and Amino Acid Property Information
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...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2526173/ https://www.ncbi.nlm.nih.gov/pubmed/18818722 http://dx.doi.org/10.1371/journal.pcbi.1000181 |
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author | Wang, Kai Horst, Jeremy A. Cheng, Gong Nickle, David C. Samudrala, Ram |
author_facet | Wang, Kai Horst, Jeremy A. Cheng, Gong Nickle, David C. Samudrala, Ram |
author_sort | Wang, Kai |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2526173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25261732008-09-26 Protein Meta-Functional Signatures from Combining Sequence, Structure, Evolution, and Amino Acid Property Information Wang, Kai Horst, Jeremy A. Cheng, Gong Nickle, David C. Samudrala, Ram PLoS Comput Biol Research Article 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. Public Library of Science 2008-09-26 /pmc/articles/PMC2526173/ /pubmed/18818722 http://dx.doi.org/10.1371/journal.pcbi.1000181 Text en Wang et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Wang, Kai Horst, Jeremy A. Cheng, Gong Nickle, David C. Samudrala, Ram Protein Meta-Functional Signatures from Combining Sequence, Structure, Evolution, and Amino Acid Property Information |
title | Protein Meta-Functional Signatures from Combining Sequence, Structure, Evolution, and Amino Acid Property Information |
title_full | Protein Meta-Functional Signatures from Combining Sequence, Structure, Evolution, and Amino Acid Property Information |
title_fullStr | Protein Meta-Functional Signatures from Combining Sequence, Structure, Evolution, and Amino Acid Property Information |
title_full_unstemmed | Protein Meta-Functional Signatures from Combining Sequence, Structure, Evolution, and Amino Acid Property Information |
title_short | Protein Meta-Functional Signatures from Combining Sequence, Structure, Evolution, and Amino Acid Property Information |
title_sort | protein meta-functional signatures from combining sequence, structure, evolution, and amino acid property information |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2526173/ https://www.ncbi.nlm.nih.gov/pubmed/18818722 http://dx.doi.org/10.1371/journal.pcbi.1000181 |
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