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Probabilistic identification of saccharide moieties in biomolecules and their protein complexes
The chemical composition of saccharide complexes underlies their biomedical activities as biomarkers for cardiometabolic disease, various types of cancer, and other conditions. However, because these molecules may undergo major structural modifications, distinguishing between compounds of saccharide...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335193/ https://www.ncbi.nlm.nih.gov/pubmed/32620933 http://dx.doi.org/10.1038/s41597-020-0547-y |
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author | Dashti, Hesam Westler, William M. Wedell, Jonathan R. Demler, Olga V. Eghbalnia, Hamid R. Markley, John L. Mora, Samia |
author_facet | Dashti, Hesam Westler, William M. Wedell, Jonathan R. Demler, Olga V. Eghbalnia, Hamid R. Markley, John L. Mora, Samia |
author_sort | Dashti, Hesam |
collection | PubMed |
description | The chemical composition of saccharide complexes underlies their biomedical activities as biomarkers for cardiometabolic disease, various types of cancer, and other conditions. However, because these molecules may undergo major structural modifications, distinguishing between compounds of saccharide and non-saccharide origin becomes a challenging computational problem that hinders the aggregation of information about their bioactive moieties. We have developed an algorithm and software package called “Cheminformatics Tool for Probabilistic Identification of Carbohydrates” (CTPIC) that analyzes the covalent structure of a compound to yield a probabilistic measure for distinguishing saccharides and saccharide-derivatives from non-saccharides. CTPIC analysis of the RCSB Ligand Expo (database of small molecules found to bind proteins in the Protein Data Bank) led to a substantial increase in the number of ligands characterized as saccharides. CTPIC analysis of Protein Data Bank identified 7.7% of the proteins as saccharide-binding. CTPIC is freely available as a webservice at (http://ctpic.nmrfam.wisc.edu). |
format | Online Article Text |
id | pubmed-7335193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-73351932020-07-09 Probabilistic identification of saccharide moieties in biomolecules and their protein complexes Dashti, Hesam Westler, William M. Wedell, Jonathan R. Demler, Olga V. Eghbalnia, Hamid R. Markley, John L. Mora, Samia Sci Data Analysis The chemical composition of saccharide complexes underlies their biomedical activities as biomarkers for cardiometabolic disease, various types of cancer, and other conditions. However, because these molecules may undergo major structural modifications, distinguishing between compounds of saccharide and non-saccharide origin becomes a challenging computational problem that hinders the aggregation of information about their bioactive moieties. We have developed an algorithm and software package called “Cheminformatics Tool for Probabilistic Identification of Carbohydrates” (CTPIC) that analyzes the covalent structure of a compound to yield a probabilistic measure for distinguishing saccharides and saccharide-derivatives from non-saccharides. CTPIC analysis of the RCSB Ligand Expo (database of small molecules found to bind proteins in the Protein Data Bank) led to a substantial increase in the number of ligands characterized as saccharides. CTPIC analysis of Protein Data Bank identified 7.7% of the proteins as saccharide-binding. CTPIC is freely available as a webservice at (http://ctpic.nmrfam.wisc.edu). Nature Publishing Group UK 2020-07-03 /pmc/articles/PMC7335193/ /pubmed/32620933 http://dx.doi.org/10.1038/s41597-020-0547-y Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Analysis Dashti, Hesam Westler, William M. Wedell, Jonathan R. Demler, Olga V. Eghbalnia, Hamid R. Markley, John L. Mora, Samia Probabilistic identification of saccharide moieties in biomolecules and their protein complexes |
title | Probabilistic identification of saccharide moieties in biomolecules and their protein complexes |
title_full | Probabilistic identification of saccharide moieties in biomolecules and their protein complexes |
title_fullStr | Probabilistic identification of saccharide moieties in biomolecules and their protein complexes |
title_full_unstemmed | Probabilistic identification of saccharide moieties in biomolecules and their protein complexes |
title_short | Probabilistic identification of saccharide moieties in biomolecules and their protein complexes |
title_sort | probabilistic identification of saccharide moieties in biomolecules and their protein complexes |
topic | Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7335193/ https://www.ncbi.nlm.nih.gov/pubmed/32620933 http://dx.doi.org/10.1038/s41597-020-0547-y |
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