CORRECTION article

Front. Pharmacol., 09 January 2024

Sec. Drugs Outcomes Research and Policies

Volume 14 - 2023 | https://doi.org/10.3389/fphar.2023.1340724

Corrigendum: Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study

  • 1. Medicinal Chemistry and Molecular Modelling Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, New Delhi, Delhi, India

  • 2. Medical Biotechnology Laboratory, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India

  • 3. Department of Bioinformatics, School of Interdisciplinary Studies, Jamia Hamdard University, New Delhi, India

  • 4. Department of Pharmaceutics, School of Pharmaceutical Sciences, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha, India

  • 5. Department of Pharmaceutics, Unaizah College of Pharmacy, Qassim University, Unaizah, Saudi Arabia

  • 6. Faculty of Medicine and Health Technology, Tampere University, Tampere, Pirkanmaa, Finland

  • 7. Fimlab Ltd., Tampere University Hospital, Tampere, Pirkanmaa, Finland

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In the published article, there was an error in the Author list, and author “Ravi Kant2 and Daman Saluja2” was erroneously “excluded”. The corrected Author list appears below.

“Ratul Bhowmik1, Ravi Kant2, Ajay Manaithiya1 *, Daman Saluja2, Bharti Vyas3, Ranajit Nath4, Kamal A. Qureshi5, Seppo Parkkila6,7, and Ashok Aspatwar6 *

1 Medicinal Chemistry and Molecular Modelling Lab, Department of Pharmaceutical Chemistry, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi, India

2 Medical Biotechnology Laboratory, Dr. B. R. Ambedkar Center for Biomedical Research, Delhi School of Public Health, IoE, University of Delhi, Delhi, India

3 Department of Bioinformatics, School of Interdisciplinary Studies, Jamia Hamdard, New Delhi, India

4 Department of Pharmaceutics, School of Pharmaceutical Sciences, Siksha ‘O’ Anusandhan University, Bhubaneswar, Odisha, India

5 Department of Pharmaceutics, Unaizah College of Pharmacy, Qassim University, Unaizah, Al-Qassim, Saudi Arabia

6 Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland

7 Fimlab Ltd., Tampere University Hospital, Tampere, Finland”

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

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Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Summary

Keywords

molecular docking, tuberculosis, drug resistance, QSAR, pharmacophore modeling

Citation

Bhowmik R, Kant R, Manaithiya A, Saluja D, Vyas B, Nath R, Qureshi KA, Parkkila S and Aspatwar A (2024) Corrigendum: Navigating bioactivity space in anti-tubercular drug discovery through the deployment of advanced machine learning models and cheminformatics tools: a molecular modeling based retrospective study. Front. Pharmacol. 14:1340724. doi: 10.3389/fphar.2023.1340724

Received

18 November 2023

Accepted

22 December 2023

Published

09 January 2024

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Frontiers Editorial Office, Frontiers Media SA, Switzerland

Volume

14 - 2023

Updates

Copyright

*Correspondence: Ajay Manaithiya, ; Ashok Aspatwar,

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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