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In Silico Studies of Indole Derivatives as Antibacterial Agents

OBJECTIVES: Molecular docking and QSAR studies of indole derivatives as antibacterial agents. METHODS: In this study, we used a multiple linear regressions (MLR) approach to construct a 2D quantitative structure activity relationship of 14 reported indole derivatives. It was performed on the reporte...

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Autores principales: Shah, Mridul, Kumar, Adarsh, Singh, Ankit Kumar, Singh, Harshwardhan, Narasimhan, Balasubramanian, Kumar, Pradeep
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Pharmacopuncture Institute (KPI) 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10315882/
https://www.ncbi.nlm.nih.gov/pubmed/37405113
http://dx.doi.org/10.3831/KPI.2023.26.2.147
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author Shah, Mridul
Kumar, Adarsh
Singh, Ankit Kumar
Singh, Harshwardhan
Narasimhan, Balasubramanian
Kumar, Pradeep
author_facet Shah, Mridul
Kumar, Adarsh
Singh, Ankit Kumar
Singh, Harshwardhan
Narasimhan, Balasubramanian
Kumar, Pradeep
author_sort Shah, Mridul
collection PubMed
description OBJECTIVES: Molecular docking and QSAR studies of indole derivatives as antibacterial agents. METHODS: In this study, we used a multiple linear regressions (MLR) approach to construct a 2D quantitative structure activity relationship of 14 reported indole derivatives. It was performed on the reported antibacterial activity data of 14 compounds based on theoretical chemical descriptors to construct statistical models that link structural properties of indole derivatives to antibacterial activity. We have also performed molecular docking studies of same compounds by using Maestro module of Schrodinger. A set the molecular descriptors like hydrophobic, geometric, electronic and topological characters were calculated to represent the structural features of compounds. The conventional antibiotics sultamicillin and ampicillin were not used in the model development since their structures are different from those of the created compounds. Biological activity data was first translated into pMIC values (i.e. –log MIC) and used as a dependent variable in QSAR investigation. RESULTS: Compounds with high electronic energy and dipole moment were effective antibacterial agents against S. aureus, indole derivatives with lower κ(2) values were excellent antibacterial agents against MRSA standard strain, and compounds with lower R value and a high (2)χ(v) value were effective antibacterial agents against MRSA isolate. CONCLUSION: Compounds 12 and 2 showed better binding score against penicillin binding protein 2 and penicillin binding protein 2a respectively.
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spelling pubmed-103158822023-07-04 In Silico Studies of Indole Derivatives as Antibacterial Agents Shah, Mridul Kumar, Adarsh Singh, Ankit Kumar Singh, Harshwardhan Narasimhan, Balasubramanian Kumar, Pradeep J Pharmacopuncture Original Article OBJECTIVES: Molecular docking and QSAR studies of indole derivatives as antibacterial agents. METHODS: In this study, we used a multiple linear regressions (MLR) approach to construct a 2D quantitative structure activity relationship of 14 reported indole derivatives. It was performed on the reported antibacterial activity data of 14 compounds based on theoretical chemical descriptors to construct statistical models that link structural properties of indole derivatives to antibacterial activity. We have also performed molecular docking studies of same compounds by using Maestro module of Schrodinger. A set the molecular descriptors like hydrophobic, geometric, electronic and topological characters were calculated to represent the structural features of compounds. The conventional antibiotics sultamicillin and ampicillin were not used in the model development since their structures are different from those of the created compounds. Biological activity data was first translated into pMIC values (i.e. –log MIC) and used as a dependent variable in QSAR investigation. RESULTS: Compounds with high electronic energy and dipole moment were effective antibacterial agents against S. aureus, indole derivatives with lower κ(2) values were excellent antibacterial agents against MRSA standard strain, and compounds with lower R value and a high (2)χ(v) value were effective antibacterial agents against MRSA isolate. CONCLUSION: Compounds 12 and 2 showed better binding score against penicillin binding protein 2 and penicillin binding protein 2a respectively. The Korean Pharmacopuncture Institute (KPI) 2023-06-30 2023-06-30 /pmc/articles/PMC10315882/ /pubmed/37405113 http://dx.doi.org/10.3831/KPI.2023.26.2.147 Text en © 2023 Korean Pharmacopuncture Institute https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Shah, Mridul
Kumar, Adarsh
Singh, Ankit Kumar
Singh, Harshwardhan
Narasimhan, Balasubramanian
Kumar, Pradeep
In Silico Studies of Indole Derivatives as Antibacterial Agents
title In Silico Studies of Indole Derivatives as Antibacterial Agents
title_full In Silico Studies of Indole Derivatives as Antibacterial Agents
title_fullStr In Silico Studies of Indole Derivatives as Antibacterial Agents
title_full_unstemmed In Silico Studies of Indole Derivatives as Antibacterial Agents
title_short In Silico Studies of Indole Derivatives as Antibacterial Agents
title_sort in silico studies of indole derivatives as antibacterial agents
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10315882/
https://www.ncbi.nlm.nih.gov/pubmed/37405113
http://dx.doi.org/10.3831/KPI.2023.26.2.147
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