Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine

Inhibitor-resistant TEM (IRT) type β-lactamase mutation is largely known. Therefore, it is of interest to identify new yet improved leads against IRT from traditional Chinese medicine. Hence, we screened more than 10,000 compounds from Chinese medicine (tcm@taiwan database) with mutant molecular IRT...

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Detalles Bibliográficos
Autores principales: Zhu, Qifeng, Yin, Yanxia, Liu, Hanjie, Tian, Jinhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Biomedical Informatics 2014
Materias:
Hypothesis
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4312368/
https://www.ncbi.nlm.nih.gov/pubmed/25670878
http://dx.doi.org/10.6026/97320630010750
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author Zhu, Qifeng
Yin, Yanxia
Liu, Hanjie
Tian, Jinhong
author_facet Zhu, Qifeng
Yin, Yanxia
Liu, Hanjie
Tian, Jinhong
author_sort Zhu, Qifeng
collection PubMed
description Inhibitor-resistant TEM (IRT) type β-lactamase mutation is largely known. Therefore, it is of interest to identify new yet improved leads against IRT from traditional Chinese medicine. Hence, we screened more than 10,000 compounds from Chinese medicine (tcm@taiwan database) with mutant molecular IRT models through docking techniques. This exercise identified compounds affeic acid, curcumin, salvianolic acid E, ferulic acid and p-coumaric acid with high binding score with the mutants. This was further validated in vitro where salvianolic acid E combined with cefoperazone and sulbactam effectively inhibit the R244S mutant.
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spelling pubmed-43123682015-02-10 Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine Zhu, Qifeng Yin, Yanxia Liu, Hanjie Tian, Jinhong Bioinformation Hypothesis Inhibitor-resistant TEM (IRT) type β-lactamase mutation is largely known. Therefore, it is of interest to identify new yet improved leads against IRT from traditional Chinese medicine. Hence, we screened more than 10,000 compounds from Chinese medicine (tcm@taiwan database) with mutant molecular IRT models through docking techniques. This exercise identified compounds affeic acid, curcumin, salvianolic acid E, ferulic acid and p-coumaric acid with high binding score with the mutants. This was further validated in vitro where salvianolic acid E combined with cefoperazone and sulbactam effectively inhibit the R244S mutant. Biomedical Informatics 2014-12-31 /pmc/articles/PMC4312368/ /pubmed/25670878 http://dx.doi.org/10.6026/97320630010750 Text en © 2014 Biomedical Informatics This is an open-access article, which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original author and source are credited.
spellingShingle Hypothesis
Zhu, Qifeng
Yin, Yanxia
Liu, Hanjie
Tian, Jinhong
Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine
title Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine
title_full Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine
title_fullStr Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine
title_full_unstemmed Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine
title_short Computer aided screening of potent inhibitor compounds against inhibitor resistant TEM β-lactamase mutants from traditional Chinese medicine
title_sort computer aided screening of potent inhibitor compounds against inhibitor resistant tem β-lactamase mutants from traditional chinese medicine
topic Hypothesis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4312368/
https://www.ncbi.nlm.nih.gov/pubmed/25670878
http://dx.doi.org/10.6026/97320630010750
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