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Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs

BACKGROUND: Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electr...

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Autores principales: Le, Nguyen-Quoc-Khanh, Ou, Yu-Yen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967503/
https://www.ncbi.nlm.nih.gov/pubmed/27475771
http://dx.doi.org/10.1186/s12859-016-1163-x
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author Le, Nguyen-Quoc-Khanh
Ou, Yu-Yen
author_facet Le, Nguyen-Quoc-Khanh
Ou, Yu-Yen
author_sort Le, Nguyen-Quoc-Khanh
collection PubMed
description BACKGROUND: Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. RESULTS: We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9–45 % and its Matthew’s correlation coefficient was 0.14–0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. CONCLUSIONS: We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron transport proteins and can help biologists understand the functions of the electron transport chain, particularly those of FAD binding sites. We also developed a web server which identifies FAD binding sites in electron transporters available for academics.
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spelling pubmed-49675032016-08-02 Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs Le, Nguyen-Quoc-Khanh Ou, Yu-Yen BMC Bioinformatics Research Article BACKGROUND: Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. RESULTS: We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9–45 % and its Matthew’s correlation coefficient was 0.14–0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. CONCLUSIONS: We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron transport proteins and can help biologists understand the functions of the electron transport chain, particularly those of FAD binding sites. We also developed a web server which identifies FAD binding sites in electron transporters available for academics. BioMed Central 2016-07-30 /pmc/articles/PMC4967503/ /pubmed/27475771 http://dx.doi.org/10.1186/s12859-016-1163-x Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Le, Nguyen-Quoc-Khanh
Ou, Yu-Yen
Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs
title Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs
title_full Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs
title_fullStr Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs
title_full_unstemmed Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs
title_short Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs
title_sort prediction of fad binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4967503/
https://www.ncbi.nlm.nih.gov/pubmed/27475771
http://dx.doi.org/10.1186/s12859-016-1163-x
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