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Residue–Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites
Lysine crotonylation (Kcr) is involved in plenty of activities in the human body. Various technologies have been developed for Kcr prediction. Sequence-based features are typically adopted in existing methods, in which only linearly neighboring amino acid composition was considered. However, modifie...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764140/ https://www.ncbi.nlm.nih.gov/pubmed/35058968 http://dx.doi.org/10.3389/fgene.2021.788467 |
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author | Wang, Rulan Wang, Zhuo Li, Zhongyan Lee, Tzong-Yi |
author_facet | Wang, Rulan Wang, Zhuo Li, Zhongyan Lee, Tzong-Yi |
author_sort | Wang, Rulan |
collection | PubMed |
description | Lysine crotonylation (Kcr) is involved in plenty of activities in the human body. Various technologies have been developed for Kcr prediction. Sequence-based features are typically adopted in existing methods, in which only linearly neighboring amino acid composition was considered. However, modified Kcr sites are neighbored by not only the linear-neighboring amino acid but also those spatially surrounding residues around the target site. In this paper, we have used residue–residue contact as a new feature for Kcr prediction, in which features encoded with not only linearly surrounding residues but also those spatially nearby the target site. Then, the spatial-surrounding residue was used as a new scheme for feature encoding for the first time, named residue–residue composition (RRC) and residue–residue pair composition (RRPC), which were used in supervised learning classification for Kcr prediction. As the result suggests, RRC and RRPC have achieved the best performance of RRC at an accuracy of 0.77 and an area under curve (AUC) value of 0.78, RRPC at an accuracy of 0.74, and an AUC value of 0.80. In order to show that the spatial feature is of a competitively high significance as other sequence-based features, feature selection was carried on those sequence-based features together with feature RRPC. In addition, different ranges of the surrounding amino acid compositions’ radii were used for comparison of the performance. After result assessment, RRC and RRPC features have shown competitively outstanding performance as others or in some cases even around 0.20 higher in accuracy or 0.3 higher in AUC values compared with sequence-based features. |
format | Online Article Text |
id | pubmed-8764140 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87641402022-01-19 Residue–Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites Wang, Rulan Wang, Zhuo Li, Zhongyan Lee, Tzong-Yi Front Genet Genetics Lysine crotonylation (Kcr) is involved in plenty of activities in the human body. Various technologies have been developed for Kcr prediction. Sequence-based features are typically adopted in existing methods, in which only linearly neighboring amino acid composition was considered. However, modified Kcr sites are neighbored by not only the linear-neighboring amino acid but also those spatially surrounding residues around the target site. In this paper, we have used residue–residue contact as a new feature for Kcr prediction, in which features encoded with not only linearly surrounding residues but also those spatially nearby the target site. Then, the spatial-surrounding residue was used as a new scheme for feature encoding for the first time, named residue–residue composition (RRC) and residue–residue pair composition (RRPC), which were used in supervised learning classification for Kcr prediction. As the result suggests, RRC and RRPC have achieved the best performance of RRC at an accuracy of 0.77 and an area under curve (AUC) value of 0.78, RRPC at an accuracy of 0.74, and an AUC value of 0.80. In order to show that the spatial feature is of a competitively high significance as other sequence-based features, feature selection was carried on those sequence-based features together with feature RRPC. In addition, different ranges of the surrounding amino acid compositions’ radii were used for comparison of the performance. After result assessment, RRC and RRPC features have shown competitively outstanding performance as others or in some cases even around 0.20 higher in accuracy or 0.3 higher in AUC values compared with sequence-based features. Frontiers Media S.A. 2022-01-04 /pmc/articles/PMC8764140/ /pubmed/35058968 http://dx.doi.org/10.3389/fgene.2021.788467 Text en Copyright © 2022 Wang, Wang, Li and Lee. 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 | Genetics Wang, Rulan Wang, Zhuo Li, Zhongyan Lee, Tzong-Yi Residue–Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites |
title | Residue–Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites |
title_full | Residue–Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites |
title_fullStr | Residue–Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites |
title_full_unstemmed | Residue–Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites |
title_short | Residue–Residue Contact Can Be a Potential Feature for the Prediction of Lysine Crotonylation Sites |
title_sort | residue–residue contact can be a potential feature for the prediction of lysine crotonylation sites |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764140/ https://www.ncbi.nlm.nih.gov/pubmed/35058968 http://dx.doi.org/10.3389/fgene.2021.788467 |
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