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iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition
BACKGROUND: In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacteri...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bentham Science Publishers
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728902/ https://www.ncbi.nlm.nih.gov/pubmed/31555063 http://dx.doi.org/10.2174/1389202920666190325162307 |
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author | Ehsan, Asma Mahmood, Muhammad K. Khan, Yaser D. Barukab, Omar M. Khan, Sher A. Chou, Kuo-Chen |
author_facet | Ehsan, Asma Mahmood, Muhammad K. Khan, Yaser D. Barukab, Omar M. Khan, Sher A. Chou, Kuo-Chen |
author_sort | Ehsan, Asma |
collection | PubMed |
description | BACKGROUND: In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacterized protein sequence requires extensive, time-consuming and expensive tests. METHODS: With the torrential slide of protein sequences produced in the post-genomic age, certain remarkable computational strategies are desired to overwhelm the issue. Keeping in view the composition and sequence order effect within polypeptide chains, an innovative in-silico> predictor via a mathematical model is proposed. RESULTS: Later, it was stringently verified using self-consistency, cross-validation and jackknife tests on benchmark datasets. It was established after a rigorous jackknife test that the new predictor values are superior to the values predicted by previous methodologies. CONCLUSION: This new mathematical technique is the most appropriate and encouraging as compared with the existing models. |
format | Online Article Text |
id | pubmed-6728902 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Bentham Science Publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-67289022019-09-25 iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition Ehsan, Asma Mahmood, Muhammad K. Khan, Yaser D. Barukab, Omar M. Khan, Sher A. Chou, Kuo-Chen Curr Genomics Article BACKGROUND: In various biological processes and cell functions, Post Translational Modifications (PTMs) bear critical significance. Hydroxylation of proline residue is one kind of PTM, which occurs following protein synthesis. The experimental determination of hydroxyproline sites in an uncharacterized protein sequence requires extensive, time-consuming and expensive tests. METHODS: With the torrential slide of protein sequences produced in the post-genomic age, certain remarkable computational strategies are desired to overwhelm the issue. Keeping in view the composition and sequence order effect within polypeptide chains, an innovative in-silico> predictor via a mathematical model is proposed. RESULTS: Later, it was stringently verified using self-consistency, cross-validation and jackknife tests on benchmark datasets. It was established after a rigorous jackknife test that the new predictor values are superior to the values predicted by previous methodologies. CONCLUSION: This new mathematical technique is the most appropriate and encouraging as compared with the existing models. Bentham Science Publishers 2019-02 2019-02 /pmc/articles/PMC6728902/ /pubmed/31555063 http://dx.doi.org/10.2174/1389202920666190325162307 Text en © 2019 Bentham Science Publishers https://creativecommons.org/licenses/by-nc/4.0/legalcode This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited. |
spellingShingle | Article Ehsan, Asma Mahmood, Muhammad K. Khan, Yaser D. Barukab, Omar M. Khan, Sher A. Chou, Kuo-Chen iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition |
title | iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition |
title_full | iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition |
title_fullStr | iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition |
title_full_unstemmed | iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition |
title_short | iHyd-PseAAC (EPSV): Identifying Hydroxylation Sites in Proteins by Extracting Enhanced Position and Sequence Variant Feature via Chou's 5-Step Rule and General Pseudo Amino Acid Composition |
title_sort | ihyd-pseaac (epsv): identifying hydroxylation sites in proteins by extracting enhanced position and sequence variant feature via chou's 5-step rule and general pseudo amino acid composition |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6728902/ https://www.ncbi.nlm.nih.gov/pubmed/31555063 http://dx.doi.org/10.2174/1389202920666190325162307 |
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