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In silico approaches for predicting the half-life of natural and modified peptides in blood
This paper describes a web server developed for designing therapeutic peptides with desired half-life in blood. In this study, we used 163 natural and 98 modified peptides whose half-life has been determined experimentally in mammalian blood, for developing in silico models. Firstly, models have bee...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983457/ https://www.ncbi.nlm.nih.gov/pubmed/29856745 http://dx.doi.org/10.1371/journal.pone.0196829 |
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author | Mathur, Deepika Singh, Sandeep Mehta, Ayesha Agrawal, Piyush Raghava, Gajendra P. S. |
author_facet | Mathur, Deepika Singh, Sandeep Mehta, Ayesha Agrawal, Piyush Raghava, Gajendra P. S. |
author_sort | Mathur, Deepika |
collection | PubMed |
description | This paper describes a web server developed for designing therapeutic peptides with desired half-life in blood. In this study, we used 163 natural and 98 modified peptides whose half-life has been determined experimentally in mammalian blood, for developing in silico models. Firstly, models have been developed on 261 peptides containing natural and modified residues, using different chemical descriptors. The best model using 43 PaDEL descriptors got a maximum correlation of 0.692 between the predicted and the actual half-life peptides. Secondly, models were developed on 163 natural peptides using amino acid composition feature of peptides and achieved a maximum correlation of 0.643. Thirdly, models were developed on 163 natural peptides using chemical descriptors and attained a maximum correlation of 0.743 using 45 selected PaDEL descriptors. In order to assist researchers in the prediction and designing of half-life of peptides, the models developed have been integrated into PlifePred web server (http://webs.iiitd.edu.in//raghava/plifepred/). |
format | Online Article Text |
id | pubmed-5983457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-59834572018-06-17 In silico approaches for predicting the half-life of natural and modified peptides in blood Mathur, Deepika Singh, Sandeep Mehta, Ayesha Agrawal, Piyush Raghava, Gajendra P. S. PLoS One Research Article This paper describes a web server developed for designing therapeutic peptides with desired half-life in blood. In this study, we used 163 natural and 98 modified peptides whose half-life has been determined experimentally in mammalian blood, for developing in silico models. Firstly, models have been developed on 261 peptides containing natural and modified residues, using different chemical descriptors. The best model using 43 PaDEL descriptors got a maximum correlation of 0.692 between the predicted and the actual half-life peptides. Secondly, models were developed on 163 natural peptides using amino acid composition feature of peptides and achieved a maximum correlation of 0.643. Thirdly, models were developed on 163 natural peptides using chemical descriptors and attained a maximum correlation of 0.743 using 45 selected PaDEL descriptors. In order to assist researchers in the prediction and designing of half-life of peptides, the models developed have been integrated into PlifePred web server (http://webs.iiitd.edu.in//raghava/plifepred/). Public Library of Science 2018-06-01 /pmc/articles/PMC5983457/ /pubmed/29856745 http://dx.doi.org/10.1371/journal.pone.0196829 Text en © 2018 Mathur et al 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 author and source are credited. |
spellingShingle | Research Article Mathur, Deepika Singh, Sandeep Mehta, Ayesha Agrawal, Piyush Raghava, Gajendra P. S. In silico approaches for predicting the half-life of natural and modified peptides in blood |
title | In silico approaches for predicting the half-life of natural and modified peptides in blood |
title_full | In silico approaches for predicting the half-life of natural and modified peptides in blood |
title_fullStr | In silico approaches for predicting the half-life of natural and modified peptides in blood |
title_full_unstemmed | In silico approaches for predicting the half-life of natural and modified peptides in blood |
title_short | In silico approaches for predicting the half-life of natural and modified peptides in blood |
title_sort | in silico approaches for predicting the half-life of natural and modified peptides in blood |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983457/ https://www.ncbi.nlm.nih.gov/pubmed/29856745 http://dx.doi.org/10.1371/journal.pone.0196829 |
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