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Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities

BACKGROUND: In eukaryotes, ubiquitin-conjugation is an important mechanism underlying proteasome-mediated degradation of proteins, and as such, plays an essential role in the regulation of many cellular processes. In the ubiquitin-proteasome pathway, E3 ligases play important roles by recognizing a...

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Autores principales: Nguyen, Van-Nui, Huang, Kai-Yao, Huang, Chien-Hsun, Chang, Tzu-Hao, Bretaña, Neil Arvin, Lai, K Robert, Weng, Julia Tzu-Ya, Lee, Tzong-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331700/
https://www.ncbi.nlm.nih.gov/pubmed/25707307
http://dx.doi.org/10.1186/1471-2105-16-S1-S1
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author Nguyen, Van-Nui
Huang, Kai-Yao
Huang, Chien-Hsun
Chang, Tzu-Hao
Bretaña, Neil Arvin
Lai, K Robert
Weng, Julia Tzu-Ya
Lee, Tzong-Yi
author_facet Nguyen, Van-Nui
Huang, Kai-Yao
Huang, Chien-Hsun
Chang, Tzu-Hao
Bretaña, Neil Arvin
Lai, K Robert
Weng, Julia Tzu-Ya
Lee, Tzong-Yi
author_sort Nguyen, Van-Nui
collection PubMed
description BACKGROUND: In eukaryotes, ubiquitin-conjugation is an important mechanism underlying proteasome-mediated degradation of proteins, and as such, plays an essential role in the regulation of many cellular processes. In the ubiquitin-proteasome pathway, E3 ligases play important roles by recognizing a specific protein substrate and catalyzing the attachment of ubiquitin to a lysine (K) residue. As more and more experimental data on ubiquitin conjugation sites become available, it becomes possible to develop prediction models that can be scaled to big data. However, no development that focuses on the investigation of ubiquitinated substrate specificities has existed. Herein, we present an approach that exploits an iteratively statistical method to identify ubiquitin conjugation sites with substrate site specificities. RESULTS: In this investigation, totally 6259 experimentally validated ubiquitinated proteins were obtained from dbPTM. After having filtered out homologous fragments with 40% sequence identity, the training data set contained 2658 ubiquitination sites (positive data) and 5532 non-ubiquitinated sites (negative data). Due to the difficulty in characterizing the substrate site specificities of E3 ligases by conventional sequence logo analysis, a recursively statistical method has been applied to obtain significant conserved motifs. The profile hidden Markov model (profile HMM) was adopted to construct the predictive models learned from the identified substrate motifs. A five-fold cross validation was then used to evaluate the predictive model, achieving sensitivity, specificity, and accuracy of 73.07%, 65.46%, and 67.93%, respectively. Additionally, an independent testing set, completely blind to the training data of the predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (76.13%) and outperform other ubiquitination site prediction tool. CONCLUSION: A case study demonstrated the effectiveness of the characterized substrate motifs for identifying ubiquitination sites. The proposed method presents a practical means of preliminary analysis and greatly diminishes the total number of potential targets required for further experimental confirmation. This method may help unravel their mechanisms and roles in E3 recognition and ubiquitin-mediated protein degradation.
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spelling pubmed-43317002015-03-19 Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities Nguyen, Van-Nui Huang, Kai-Yao Huang, Chien-Hsun Chang, Tzu-Hao Bretaña, Neil Arvin Lai, K Robert Weng, Julia Tzu-Ya Lee, Tzong-Yi BMC Bioinformatics Proceedings BACKGROUND: In eukaryotes, ubiquitin-conjugation is an important mechanism underlying proteasome-mediated degradation of proteins, and as such, plays an essential role in the regulation of many cellular processes. In the ubiquitin-proteasome pathway, E3 ligases play important roles by recognizing a specific protein substrate and catalyzing the attachment of ubiquitin to a lysine (K) residue. As more and more experimental data on ubiquitin conjugation sites become available, it becomes possible to develop prediction models that can be scaled to big data. However, no development that focuses on the investigation of ubiquitinated substrate specificities has existed. Herein, we present an approach that exploits an iteratively statistical method to identify ubiquitin conjugation sites with substrate site specificities. RESULTS: In this investigation, totally 6259 experimentally validated ubiquitinated proteins were obtained from dbPTM. After having filtered out homologous fragments with 40% sequence identity, the training data set contained 2658 ubiquitination sites (positive data) and 5532 non-ubiquitinated sites (negative data). Due to the difficulty in characterizing the substrate site specificities of E3 ligases by conventional sequence logo analysis, a recursively statistical method has been applied to obtain significant conserved motifs. The profile hidden Markov model (profile HMM) was adopted to construct the predictive models learned from the identified substrate motifs. A five-fold cross validation was then used to evaluate the predictive model, achieving sensitivity, specificity, and accuracy of 73.07%, 65.46%, and 67.93%, respectively. Additionally, an independent testing set, completely blind to the training data of the predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (76.13%) and outperform other ubiquitination site prediction tool. CONCLUSION: A case study demonstrated the effectiveness of the characterized substrate motifs for identifying ubiquitination sites. The proposed method presents a practical means of preliminary analysis and greatly diminishes the total number of potential targets required for further experimental confirmation. This method may help unravel their mechanisms and roles in E3 recognition and ubiquitin-mediated protein degradation. BioMed Central 2015-01-21 /pmc/articles/PMC4331700/ /pubmed/25707307 http://dx.doi.org/10.1186/1471-2105-16-S1-S1 Text en Copyright © 2015 Nguyen et al.; licensee BioMed Central Ltd. 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 use, distribution, and reproduction in any medium, provided the original work is properly cited. 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 Proceedings
Nguyen, Van-Nui
Huang, Kai-Yao
Huang, Chien-Hsun
Chang, Tzu-Hao
Bretaña, Neil Arvin
Lai, K Robert
Weng, Julia Tzu-Ya
Lee, Tzong-Yi
Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities
title Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities
title_full Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities
title_fullStr Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities
title_full_unstemmed Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities
title_short Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities
title_sort characterization and identification of ubiquitin conjugation sites with e3 ligase recognition specificities
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4331700/
https://www.ncbi.nlm.nih.gov/pubmed/25707307
http://dx.doi.org/10.1186/1471-2105-16-S1-S1
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