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Identification of hydantoin based Decaprenylphosphoryl-β-d-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools
Tuberculosis (TB) is one of the emerging infectious diseases in the world. DprE1 (Decaprenylphosphoryl-β-d-ribose 2′-epimerase), an enzyme accountable for mycobacterial cell wall synthesis was the first drug gable target based on discoveries of inhibitors via HTS (high throughput screening). Since t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525719/ https://www.ncbi.nlm.nih.gov/pubmed/36180452 http://dx.doi.org/10.1038/s41598-022-20325-1 |
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author | Mali, Suraj N. Pandey, Anima Bhandare, Richie R. Shaik, Afzal B. |
author_facet | Mali, Suraj N. Pandey, Anima Bhandare, Richie R. Shaik, Afzal B. |
author_sort | Mali, Suraj N. |
collection | PubMed |
description | Tuberculosis (TB) is one of the emerging infectious diseases in the world. DprE1 (Decaprenylphosphoryl-β-d-ribose 2′-epimerase), an enzyme accountable for mycobacterial cell wall synthesis was the first drug gable target based on discoveries of inhibitors via HTS (high throughput screening). Since then, many literature reports have been published so far enlightening varieties of chemical scaffolds acting as inhibitors of DprE1. Herein, in our present study, we have developed statistically robust GA-MLR (genetic algorithm multiple linear regression), atom-based as well as field based-3D-QSAR models. Both atom-based as well as field based-3D-QSAR models (internally as well as externally validated) were obtained with robust Training set, R(2) > 0.69 and Test set, Q(2) > 0.50. We have also developed top ranked 5 point hypothesis AAAHR_1 among 14 CPHs (common pharmacophore hypotheses). We found that our dataset molecule had more docking score (XP mode = − 9.068 kcal/mol) than the standards isoniazid and ethambutol; when docked into binding pockets of enzyme 4P8C with Glide module. We further queried our best docked dataset molecule 151 for ligand based virtual screening using “SwissSimilarity” platform. Among 9 identified hits, we found ZINC12196803 had best binding energies and docking score (docking score = − 9.437 kcal/mol, MMGBSA dgBind = − 70.508 kcal/mol). Finally, our molecular dynamics studies for 1.2–100 ns depicts that these complexes are stable. We have also carried out in-silico ADMET predictions, Cardiac toxicity, ‘SwissTargetPredictions’ and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) binding energy calculations for further explorations of dataset as well as hit molecules. Our current studies showed that the hit molecule ZINC12196803 may enlighten the path for future developments of DprE1 inhibitors. |
format | Online Article Text |
id | pubmed-9525719 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-95257192022-10-02 Identification of hydantoin based Decaprenylphosphoryl-β-d-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools Mali, Suraj N. Pandey, Anima Bhandare, Richie R. Shaik, Afzal B. Sci Rep Article Tuberculosis (TB) is one of the emerging infectious diseases in the world. DprE1 (Decaprenylphosphoryl-β-d-ribose 2′-epimerase), an enzyme accountable for mycobacterial cell wall synthesis was the first drug gable target based on discoveries of inhibitors via HTS (high throughput screening). Since then, many literature reports have been published so far enlightening varieties of chemical scaffolds acting as inhibitors of DprE1. Herein, in our present study, we have developed statistically robust GA-MLR (genetic algorithm multiple linear regression), atom-based as well as field based-3D-QSAR models. Both atom-based as well as field based-3D-QSAR models (internally as well as externally validated) were obtained with robust Training set, R(2) > 0.69 and Test set, Q(2) > 0.50. We have also developed top ranked 5 point hypothesis AAAHR_1 among 14 CPHs (common pharmacophore hypotheses). We found that our dataset molecule had more docking score (XP mode = − 9.068 kcal/mol) than the standards isoniazid and ethambutol; when docked into binding pockets of enzyme 4P8C with Glide module. We further queried our best docked dataset molecule 151 for ligand based virtual screening using “SwissSimilarity” platform. Among 9 identified hits, we found ZINC12196803 had best binding energies and docking score (docking score = − 9.437 kcal/mol, MMGBSA dgBind = − 70.508 kcal/mol). Finally, our molecular dynamics studies for 1.2–100 ns depicts that these complexes are stable. We have also carried out in-silico ADMET predictions, Cardiac toxicity, ‘SwissTargetPredictions’ and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) binding energy calculations for further explorations of dataset as well as hit molecules. Our current studies showed that the hit molecule ZINC12196803 may enlighten the path for future developments of DprE1 inhibitors. Nature Publishing Group UK 2022-09-30 /pmc/articles/PMC9525719/ /pubmed/36180452 http://dx.doi.org/10.1038/s41598-022-20325-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Mali, Suraj N. Pandey, Anima Bhandare, Richie R. Shaik, Afzal B. Identification of hydantoin based Decaprenylphosphoryl-β-d-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools |
title | Identification of hydantoin based Decaprenylphosphoryl-β-d-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools |
title_full | Identification of hydantoin based Decaprenylphosphoryl-β-d-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools |
title_fullStr | Identification of hydantoin based Decaprenylphosphoryl-β-d-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools |
title_full_unstemmed | Identification of hydantoin based Decaprenylphosphoryl-β-d-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools |
title_short | Identification of hydantoin based Decaprenylphosphoryl-β-d-Ribose Oxidase (DprE1) inhibitors as antimycobacterial agents using computational tools |
title_sort | identification of hydantoin based decaprenylphosphoryl-β-d-ribose oxidase (dpre1) inhibitors as antimycobacterial agents using computational tools |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9525719/ https://www.ncbi.nlm.nih.gov/pubmed/36180452 http://dx.doi.org/10.1038/s41598-022-20325-1 |
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