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uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction
In the era of antibiotic resistance, in silico prediction of bacterial resistome profiles, likely to be associated with inactivation of new potential antibiotics is of utmost importance. Despite this, to the best of our knowledge, no tool exists for such prediction. Therefore, under the rationale th...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Chongqing Medical University
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278538/ https://www.ncbi.nlm.nih.gov/pubmed/34291144 http://dx.doi.org/10.1016/j.gendis.2020.06.008 |
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author | Saha, Saurav Bhaskar Gupta, Vijai Kumar Ramteke, Pramod Wasudeo |
author_facet | Saha, Saurav Bhaskar Gupta, Vijai Kumar Ramteke, Pramod Wasudeo |
author_sort | Saha, Saurav Bhaskar |
collection | PubMed |
description | In the era of antibiotic resistance, in silico prediction of bacterial resistome profiles, likely to be associated with inactivation of new potential antibiotics is of utmost importance. Despite this, to the best of our knowledge, no tool exists for such prediction. Therefore, under the rationale that drugs with similar structures have similar resistome profiles, we developed two models, a deterministic model and a stochastic model, to predict the bacterial resistome likely to neutralize uncharacterized but potential chemical structures. The current version of the tool involves the prediction of a resistome for Escherichia coli and Pseudomonas aeruginosa. The deterministic model on omitting two diverse but relatively less characterized drug classes, polyketides and polypeptides showed an accuracy of 87%, a sensitivity of 85%, and a precision of 89%, whereas the stochastic model predicted antibiotic classes of the test set compounds with an accuracy of 72%, a sensitivity of 75%, and a precision of 83%. The models have been implemented in both a standalone package and an online server, uCAREChemSuiteCLI and uCARE Chem Suite, respectively. In addition to resistome prediction, the online version of the suite enables the user to visualize the chemical structure, classify compounds in 19 predefined drug classes, perform pairwise alignment, and cluster with database compounds using a graphical user interface. AVAILABILITY: uCARE Chem Suite can be browsed at: https://sauravsaha.shinyapps.io/ucarechemsuite2/, and uCAREChemSuiteCLI can be installed from: 1. CRAN (https://cran.r-project.org/package=uCAREChemSuiteCLI) and 2. GitHub (https://github.com/sauravbsaha/uCAREChemSuiteCLI). |
format | Online Article Text |
id | pubmed-8278538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Chongqing Medical University |
record_format | MEDLINE/PubMed |
spelling | pubmed-82785382021-07-20 uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction Saha, Saurav Bhaskar Gupta, Vijai Kumar Ramteke, Pramod Wasudeo Genes Dis Full Length Article In the era of antibiotic resistance, in silico prediction of bacterial resistome profiles, likely to be associated with inactivation of new potential antibiotics is of utmost importance. Despite this, to the best of our knowledge, no tool exists for such prediction. Therefore, under the rationale that drugs with similar structures have similar resistome profiles, we developed two models, a deterministic model and a stochastic model, to predict the bacterial resistome likely to neutralize uncharacterized but potential chemical structures. The current version of the tool involves the prediction of a resistome for Escherichia coli and Pseudomonas aeruginosa. The deterministic model on omitting two diverse but relatively less characterized drug classes, polyketides and polypeptides showed an accuracy of 87%, a sensitivity of 85%, and a precision of 89%, whereas the stochastic model predicted antibiotic classes of the test set compounds with an accuracy of 72%, a sensitivity of 75%, and a precision of 83%. The models have been implemented in both a standalone package and an online server, uCAREChemSuiteCLI and uCARE Chem Suite, respectively. In addition to resistome prediction, the online version of the suite enables the user to visualize the chemical structure, classify compounds in 19 predefined drug classes, perform pairwise alignment, and cluster with database compounds using a graphical user interface. AVAILABILITY: uCARE Chem Suite can be browsed at: https://sauravsaha.shinyapps.io/ucarechemsuite2/, and uCAREChemSuiteCLI can be installed from: 1. CRAN (https://cran.r-project.org/package=uCAREChemSuiteCLI) and 2. GitHub (https://github.com/sauravbsaha/uCAREChemSuiteCLI). Chongqing Medical University 2020-06-30 /pmc/articles/PMC8278538/ /pubmed/34291144 http://dx.doi.org/10.1016/j.gendis.2020.06.008 Text en © 2020 Chongqing Medical University. Production and hosting by Elsevier B.V. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Full Length Article Saha, Saurav Bhaskar Gupta, Vijai Kumar Ramteke, Pramod Wasudeo uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction |
title | uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction |
title_full | uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction |
title_fullStr | uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction |
title_full_unstemmed | uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction |
title_short | uCARE Chem Suite and uCAREChemSuiteCLI: Tools for bacterial resistome prediction |
title_sort | ucare chem suite and ucarechemsuitecli: tools for bacterial resistome prediction |
topic | Full Length Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278538/ https://www.ncbi.nlm.nih.gov/pubmed/34291144 http://dx.doi.org/10.1016/j.gendis.2020.06.008 |
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