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ContactPFP: Protein Function Prediction Using Predicted Contact Information

Computational function prediction is one of the most important problems in bioinformatics as elucidating the function of genes is a central task in molecular biology and genomics. Most of the existing function prediction methods use protein sequences as the primary source of input information becaus...

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Autores principales: Kagaya, Yuki, Flannery, Sean T., Jain, Aashish, Kihara, Daisuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302406/
https://www.ncbi.nlm.nih.gov/pubmed/35875419
http://dx.doi.org/10.3389/fbinf.2022.896295
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author Kagaya, Yuki
Flannery, Sean T.
Jain, Aashish
Kihara, Daisuke
author_facet Kagaya, Yuki
Flannery, Sean T.
Jain, Aashish
Kihara, Daisuke
author_sort Kagaya, Yuki
collection PubMed
description Computational function prediction is one of the most important problems in bioinformatics as elucidating the function of genes is a central task in molecular biology and genomics. Most of the existing function prediction methods use protein sequences as the primary source of input information because the sequence is the most available information for query proteins. There are attempts to consider other attributes of query proteins. Among these attributes, the three-dimensional (3D) structure of proteins is known to be very useful in identifying the evolutionary relationship of proteins, from which functional similarity can be inferred. Here, we report a novel protein function prediction method, ContactPFP, which uses predicted residue-residue contact maps as input structural features of query proteins. Although 3D structure information is known to be useful, it has not been routinely used in function prediction because the 3D structure is not experimentally determined for many proteins. In ContactPFP, we overcome this limitation by using residue-residue contact prediction, which has become increasingly accurate due to rapid development in the protein structure prediction field. ContactPFP takes a query protein sequence as input and uses predicted residue-residue contact as a proxy for the 3D protein structure. To characterize how predicted contacts contribute to function prediction accuracy, we compared the performance of ContactPFP with several well-established sequence-based function prediction methods. The comparative study revealed the advantages and weaknesses of ContactPFP compared to contemporary sequence-based methods. There were many cases where it showed higher prediction accuracy. We examined factors that affected the accuracy of ContactPFP using several illustrative cases that highlight the strength of our method.
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spelling pubmed-93024062022-07-21 ContactPFP: Protein Function Prediction Using Predicted Contact Information Kagaya, Yuki Flannery, Sean T. Jain, Aashish Kihara, Daisuke Front Bioinform Bioinformatics Computational function prediction is one of the most important problems in bioinformatics as elucidating the function of genes is a central task in molecular biology and genomics. Most of the existing function prediction methods use protein sequences as the primary source of input information because the sequence is the most available information for query proteins. There are attempts to consider other attributes of query proteins. Among these attributes, the three-dimensional (3D) structure of proteins is known to be very useful in identifying the evolutionary relationship of proteins, from which functional similarity can be inferred. Here, we report a novel protein function prediction method, ContactPFP, which uses predicted residue-residue contact maps as input structural features of query proteins. Although 3D structure information is known to be useful, it has not been routinely used in function prediction because the 3D structure is not experimentally determined for many proteins. In ContactPFP, we overcome this limitation by using residue-residue contact prediction, which has become increasingly accurate due to rapid development in the protein structure prediction field. ContactPFP takes a query protein sequence as input and uses predicted residue-residue contact as a proxy for the 3D protein structure. To characterize how predicted contacts contribute to function prediction accuracy, we compared the performance of ContactPFP with several well-established sequence-based function prediction methods. The comparative study revealed the advantages and weaknesses of ContactPFP compared to contemporary sequence-based methods. There were many cases where it showed higher prediction accuracy. We examined factors that affected the accuracy of ContactPFP using several illustrative cases that highlight the strength of our method. Frontiers Media S.A. 2022-06-02 /pmc/articles/PMC9302406/ /pubmed/35875419 http://dx.doi.org/10.3389/fbinf.2022.896295 Text en Copyright © 2022 Kagaya, Flannery, Jain and Kihara. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioinformatics
Kagaya, Yuki
Flannery, Sean T.
Jain, Aashish
Kihara, Daisuke
ContactPFP: Protein Function Prediction Using Predicted Contact Information
title ContactPFP: Protein Function Prediction Using Predicted Contact Information
title_full ContactPFP: Protein Function Prediction Using Predicted Contact Information
title_fullStr ContactPFP: Protein Function Prediction Using Predicted Contact Information
title_full_unstemmed ContactPFP: Protein Function Prediction Using Predicted Contact Information
title_short ContactPFP: Protein Function Prediction Using Predicted Contact Information
title_sort contactpfp: protein function prediction using predicted contact information
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302406/
https://www.ncbi.nlm.nih.gov/pubmed/35875419
http://dx.doi.org/10.3389/fbinf.2022.896295
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