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PIRSitePredict for protein functional site prediction using position-specific rules

Methods focused on predicting ‘global’ annotations for proteins (such as molecular function, biological process and presence of domains or membership in a family) have reached a relatively mature stage. Methods to provide fine-grained ‘local’ annotation of functional sites (at the level of individua...

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Autores principales: Chen, Chuming, Wang, Qinghua, Huang, Hongzhan, Vinayaka, Cholanayakanahalli R, Garavelli, John S, Arighi, Cecilia N, Natale, Darren A, Wu, Cathy H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389862/
https://www.ncbi.nlm.nih.gov/pubmed/30805646
http://dx.doi.org/10.1093/database/baz026
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author Chen, Chuming
Wang, Qinghua
Huang, Hongzhan
Vinayaka, Cholanayakanahalli R
Garavelli, John S
Arighi, Cecilia N
Natale, Darren A
Wu, Cathy H
author_facet Chen, Chuming
Wang, Qinghua
Huang, Hongzhan
Vinayaka, Cholanayakanahalli R
Garavelli, John S
Arighi, Cecilia N
Natale, Darren A
Wu, Cathy H
author_sort Chen, Chuming
collection PubMed
description Methods focused on predicting ‘global’ annotations for proteins (such as molecular function, biological process and presence of domains or membership in a family) have reached a relatively mature stage. Methods to provide fine-grained ‘local’ annotation of functional sites (at the level of individual amino acid) are now coming to the forefront, especially in light of the rapid accumulation of genetic variant data. We have developed a computational method and workflow that predicts functional sites within proteins using position-specific conditional template annotation rules (namely PIR Site Rules or PIRSRs for short). Such rules are curated through review of known protein structural and other experimental data by structural biologists and are used to generate high-quality annotations for the UniProt Knowledgebase (UniProtKB) unreviewed section. To share the PIRSR functional site prediction method with the broader scientific community, we have streamlined our workflow and developed a stand-alone Java software package named PIRSitePredict. We demonstrate the use of PIRSitePredict for functional annotation of de novo assembled genome/transcriptome by annotating uncharacterized proteins from Trinity RNA-seq assembly of embryonic transcriptomes of the following three cartilaginous fishes: Leucoraja erinacea (Little Skate), Scyliorhinus canicula (Small-spotted Catshark) and Callorhinchus milii (Elephant Shark). On average about 1200 lines of annotations were predicted for each species.
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spelling pubmed-63898622019-03-04 PIRSitePredict for protein functional site prediction using position-specific rules Chen, Chuming Wang, Qinghua Huang, Hongzhan Vinayaka, Cholanayakanahalli R Garavelli, John S Arighi, Cecilia N Natale, Darren A Wu, Cathy H Database (Oxford) Original Article Methods focused on predicting ‘global’ annotations for proteins (such as molecular function, biological process and presence of domains or membership in a family) have reached a relatively mature stage. Methods to provide fine-grained ‘local’ annotation of functional sites (at the level of individual amino acid) are now coming to the forefront, especially in light of the rapid accumulation of genetic variant data. We have developed a computational method and workflow that predicts functional sites within proteins using position-specific conditional template annotation rules (namely PIR Site Rules or PIRSRs for short). Such rules are curated through review of known protein structural and other experimental data by structural biologists and are used to generate high-quality annotations for the UniProt Knowledgebase (UniProtKB) unreviewed section. To share the PIRSR functional site prediction method with the broader scientific community, we have streamlined our workflow and developed a stand-alone Java software package named PIRSitePredict. We demonstrate the use of PIRSitePredict for functional annotation of de novo assembled genome/transcriptome by annotating uncharacterized proteins from Trinity RNA-seq assembly of embryonic transcriptomes of the following three cartilaginous fishes: Leucoraja erinacea (Little Skate), Scyliorhinus canicula (Small-spotted Catshark) and Callorhinchus milii (Elephant Shark). On average about 1200 lines of annotations were predicted for each species. Oxford University Press 2019-02-26 /pmc/articles/PMC6389862/ /pubmed/30805646 http://dx.doi.org/10.1093/database/baz026 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Chen, Chuming
Wang, Qinghua
Huang, Hongzhan
Vinayaka, Cholanayakanahalli R
Garavelli, John S
Arighi, Cecilia N
Natale, Darren A
Wu, Cathy H
PIRSitePredict for protein functional site prediction using position-specific rules
title PIRSitePredict for protein functional site prediction using position-specific rules
title_full PIRSitePredict for protein functional site prediction using position-specific rules
title_fullStr PIRSitePredict for protein functional site prediction using position-specific rules
title_full_unstemmed PIRSitePredict for protein functional site prediction using position-specific rules
title_short PIRSitePredict for protein functional site prediction using position-specific rules
title_sort pirsitepredict for protein functional site prediction using position-specific rules
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6389862/
https://www.ncbi.nlm.nih.gov/pubmed/30805646
http://dx.doi.org/10.1093/database/baz026
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