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Coumarin-based combined computational study to design novel drugs against Candida albicans

Candida species cause the most prevalent fungal illness, candidiasis. Candida albicans is known to cause bloodstream infections. This species is a commensal bacterium, but it can cause hospital-acquired diseases, particularly in COVID-19 patients with impaired immune systems. Candida infections have...

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Autores principales: Maurya, Akhilesh Kumar, Mishra, Nidhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Microbiological Society of Korea 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9647762/
https://www.ncbi.nlm.nih.gov/pubmed/36355278
http://dx.doi.org/10.1007/s12275-022-2279-5
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author Maurya, Akhilesh Kumar
Mishra, Nidhi
author_facet Maurya, Akhilesh Kumar
Mishra, Nidhi
author_sort Maurya, Akhilesh Kumar
collection PubMed
description Candida species cause the most prevalent fungal illness, candidiasis. Candida albicans is known to cause bloodstream infections. This species is a commensal bacterium, but it can cause hospital-acquired diseases, particularly in COVID-19 patients with impaired immune systems. Candida infections have increased in patients with acute respiratory distress syndrome. Coumarins are both naturally occurring and synthetically produced. In this study, the biological activity of 40 coumarin derivatives was used to create a three-dimensional quantitative structure activity relationship (3D-QSAR) model. The training and test minimum inhibitory concentration values of C. albicans active compounds were split, and a regression model based on statistical data was established. This model served as a foundation for the creation of coumarin derivative QSARs. This is a unique way to create new therapeutic compounds for various ailments. We constructed novel structural coumarin derivatives using the derived QSAR model, and the models were confirmed using molecular docking and molecular dynamics simulation. Supplemental material for this article may be found at 10.1007/s12275-022-2279-5.
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spelling pubmed-96477622022-11-14 Coumarin-based combined computational study to design novel drugs against Candida albicans Maurya, Akhilesh Kumar Mishra, Nidhi J Microbiol Systems and Synthetic Microbiology and Bioinformatics Candida species cause the most prevalent fungal illness, candidiasis. Candida albicans is known to cause bloodstream infections. This species is a commensal bacterium, but it can cause hospital-acquired diseases, particularly in COVID-19 patients with impaired immune systems. Candida infections have increased in patients with acute respiratory distress syndrome. Coumarins are both naturally occurring and synthetically produced. In this study, the biological activity of 40 coumarin derivatives was used to create a three-dimensional quantitative structure activity relationship (3D-QSAR) model. The training and test minimum inhibitory concentration values of C. albicans active compounds were split, and a regression model based on statistical data was established. This model served as a foundation for the creation of coumarin derivative QSARs. This is a unique way to create new therapeutic compounds for various ailments. We constructed novel structural coumarin derivatives using the derived QSAR model, and the models were confirmed using molecular docking and molecular dynamics simulation. Supplemental material for this article may be found at 10.1007/s12275-022-2279-5. The Microbiological Society of Korea 2022-11-10 2022 /pmc/articles/PMC9647762/ /pubmed/36355278 http://dx.doi.org/10.1007/s12275-022-2279-5 Text en © Author(s) 2022, under the exclusive license with the Microbiological Society of Korea This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Systems and Synthetic Microbiology and Bioinformatics
Maurya, Akhilesh Kumar
Mishra, Nidhi
Coumarin-based combined computational study to design novel drugs against Candida albicans
title Coumarin-based combined computational study to design novel drugs against Candida albicans
title_full Coumarin-based combined computational study to design novel drugs against Candida albicans
title_fullStr Coumarin-based combined computational study to design novel drugs against Candida albicans
title_full_unstemmed Coumarin-based combined computational study to design novel drugs against Candida albicans
title_short Coumarin-based combined computational study to design novel drugs against Candida albicans
title_sort coumarin-based combined computational study to design novel drugs against candida albicans
topic Systems and Synthetic Microbiology and Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9647762/
https://www.ncbi.nlm.nih.gov/pubmed/36355278
http://dx.doi.org/10.1007/s12275-022-2279-5
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