Computational Studies to Identify Potential Inhibitors Targeting the DprE1 Protein in Mycobacterium tuberculosis

  • Bashir A Sheikh Department of Bioresources, School of Biological Sciences, University of Kashmir, Srinagar, INDIA. https://orcid.org/0000-0002-1087-564X
  • Basharat A Sheikh Department of Bioresources, School of Biological Sciences, University of Kashmir, Srinagar, INDIA. https://orcid.org/0000-0002-4847-4825
  • Masood A Rizvi Department of Chemistry, School of Physical and Mathematical Sciences, University of Kashmir, Srinagar, INDIA. https://orcid.org/0000-0003-0470-6329
  • Zahoor Ahmad Clinical Microbiology PK-PD/ Laboratory, Indian Institute of Integrative Medicine (IIIM), Srinagar, INDIA. https://orcid.org/0000-0001-5694-9600
  • Abdullah Almilaibary Department of Family and Community Medicine, Faculty of Medicine, Albaha University, Albaha, SAUDI ARABIA. https://orcid.org/0000-0002-4933-1711
  • Mustfa Alkhanani Department of Biology, College of Science, Hafr Al Batin University Hafr Albatin, SAUDI ARABIA https://orcid.org/0000-0003-4683-7896
  • Manzoor A Mir Department of Bioresources, School of Biological Sciences, University of Kashmir, Srinagar, INDIA.
Keywords: MD simulation, DprE1, In silico Screening, Mycobacterium tuberculosis, ADMET, Bioavailability, Cytotoxicity

Abstract

Background: DprE1, which is a flavoenzyme, is very important for cell wall biosynthesis in Mycobacterium tuberculosis (Mtb) and for the pathogenesis, virulence, lethality, and stress resistance of the host. Drug-resistant tuberculosis is a challenging global human health issue, necessitating the development of novel, more effective treatment regimens without adverse effects. DprE1 represents a potential therapeutic target. It was explored as a drug target utilizing benzothiazoles (BTZ), which are enormously potential anti-bacterial agents and are currently being explored as anti-mycobacterial entities. Materials and Methods: We used virtual screening of bioactive molecules from PubChem and ZINC databases targeting DprE1, having bioactive thousands of molecules known for anti-microbial activity. In the present study, we selected 100 compounds as the most promising candidates to act as potential DprE1 inhibitors to control this emerging condition of tuberculosis infection. To identify the six topranked compounds, molecular docking was used to calculate the binding affinities (ranging from -8.3 to 10.0 kcal/mol) between various compounds (C1-C6) and the DprE1 protein. Results: Based on the results of an ADMET analysis, these six chemicals are safer potential drug candidates, as neither AMES toxicity nor carcinogenicity is present when toxicological properties are considered. Out of 6 compounds, the top-ranked compound exhibiting the best binding affinity against the drug target DprE1 (Pdb-id;4FEH) receptor was further subjected to molecular dynamic simulation for 100 nanoseconds to check the stability and trajectories by root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) graphs and interacting coordinates using Desmond Schrodinger Software. Conclusion: Our in-silico investigation identified potent inhibitors for the DprE1 protein of Mtb, and these compounds can be considered and recommended as the lead molecules in the treatment of tuberculosis.

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Published
2022-12-16
How to Cite
1.
Sheikh BA, Sheikh BA, Rizvi MA, Ahmad Z, Almilaibary A, Alkhanani M, Mir MA. Computational Studies to Identify Potential Inhibitors Targeting the DprE1 Protein in Mycobacterium tuberculosis. ijpi [Internet]. 16Dec.2022 [cited 27Jan.2023];13(1):129-38. Available from: https://jpionline.org/index.php/ijpi/article/view/1750