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BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins
Efflux proteins are transport proteins, which are involved in transporting different substrates from the cell to the external environment, including antibiotics. The efflux mechanism and efflux pumps are a major reason underlying emerging rampant antibiotic resistance (AR) in microbes. To reduce the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7283322/ https://www.ncbi.nlm.nih.gov/pubmed/32518231 http://dx.doi.org/10.1038/s41598-020-65981-3 |
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author | Pandey, Deeksha Kumari, Bandana Singhal, Neelja Kumar, Manish |
author_facet | Pandey, Deeksha Kumari, Bandana Singhal, Neelja Kumar, Manish |
author_sort | Pandey, Deeksha |
collection | PubMed |
description | Efflux proteins are transport proteins, which are involved in transporting different substrates from the cell to the external environment, including antibiotics. The efflux mechanism and efflux pumps are a major reason underlying emerging rampant antibiotic resistance (AR) in microbes. To reduce the resources required and time of identification, characterization and classification of bacterial efflux proteins, we have developed a fast and accurate support vector machine based two-tier prediction system, BacEffluxPred, which can predict bacterial efflux proteins responsible for AR and identify their corresponding families. A leave-one-out cross-validation also called jackknife procedure was used for performance evaluation. The accuracy to discriminate bacterial AR efflux from non-AR efflux was obtained as 85.81% (at tier-I) while accuracies for prediction of efflux pump families like ABC, MFS, RND and MATE family were found 92.13%, 85.39%, 91.01% and 99.44%, respectively (at tier-II). Benchmarking on an independent dataset also showed that BacEffluxPred had comparable accuracy for prediction of bacterial AR efflux pumps and their families. This is the first in-silico tool for predicting bacterial AR efflux proteins and their families and is freely available as both web-server and standalone versions at http://proteininformatics.org/mkumar/baceffluxpred/. |
format | Online Article Text |
id | pubmed-7283322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-72833222020-06-15 BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins Pandey, Deeksha Kumari, Bandana Singhal, Neelja Kumar, Manish Sci Rep Article Efflux proteins are transport proteins, which are involved in transporting different substrates from the cell to the external environment, including antibiotics. The efflux mechanism and efflux pumps are a major reason underlying emerging rampant antibiotic resistance (AR) in microbes. To reduce the resources required and time of identification, characterization and classification of bacterial efflux proteins, we have developed a fast and accurate support vector machine based two-tier prediction system, BacEffluxPred, which can predict bacterial efflux proteins responsible for AR and identify their corresponding families. A leave-one-out cross-validation also called jackknife procedure was used for performance evaluation. The accuracy to discriminate bacterial AR efflux from non-AR efflux was obtained as 85.81% (at tier-I) while accuracies for prediction of efflux pump families like ABC, MFS, RND and MATE family were found 92.13%, 85.39%, 91.01% and 99.44%, respectively (at tier-II). Benchmarking on an independent dataset also showed that BacEffluxPred had comparable accuracy for prediction of bacterial AR efflux pumps and their families. This is the first in-silico tool for predicting bacterial AR efflux proteins and their families and is freely available as both web-server and standalone versions at http://proteininformatics.org/mkumar/baceffluxpred/. Nature Publishing Group UK 2020-06-09 /pmc/articles/PMC7283322/ /pubmed/32518231 http://dx.doi.org/10.1038/s41598-020-65981-3 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 | Article Pandey, Deeksha Kumari, Bandana Singhal, Neelja Kumar, Manish BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins |
title | BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins |
title_full | BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins |
title_fullStr | BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins |
title_full_unstemmed | BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins |
title_short | BacEffluxPred: A two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins |
title_sort | baceffluxpred: a two-tier system to predict and categorize bacterial efflux mediated antibiotic resistance proteins |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7283322/ https://www.ncbi.nlm.nih.gov/pubmed/32518231 http://dx.doi.org/10.1038/s41598-020-65981-3 |
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