Integrating computational and biological approaches for the discovery of putative MmpL3 inhibitors against Mycobacterium tuberculosis

Research output: Contribution to journalArticlepeer-review

Abstract

The rapid emergence of drug-resistant Mycobacterium tuberculosis strains has progressively undermined the efficacy of existing anti-tuberculosis therapies, underscoring the urgent need for new therapeutic agents. MmpL3, an essential transporter involved in mycobacterial cell wall biosynthesis, represents a promising drug target. In this study, an integrated virtual screening strategy that combined pharmacophore-based and structure-based approaches was applied to screen the ChemDiv database, followed by biological evaluation, to identify potential MmpL3 inhibitors. Six compounds (F784-0295, Y205-0192, F624-3971, C200-4969, Y508-1233, and 8018 − 0330) showed measurable antimycobacterial activity. Among them, the previously unreported pyrazolo[1,5-a]pyrimidine derivative Y508-1233 exhibited potent activity against both H37Rv and multidrug-resistant Mycobacterium tuberculosis strains, with an MIC90 of 37.3 µM for each strain. ADMET predictions indicated generally acceptable pharmacokinetics, though somewhat lipophilic with limited solubility. Molecular dynamics simulations revealed that Y508-1233 remains stably bound within the central channel of the MmpL3 transmembrane domain, primarily through nonpolar interactions with helices TM4 and TM10, accompanied by a persistent hydrogen bond between its carboxamide nitrogen and Asp640. Structural analysis identified an unoccupied subpocket delineated by Leu243 and Ile244, providing a structural basis for further molecular optimization. Furthermore, τ-random acceleration molecular dynamics simulations predicted that Y508-1233 may exhibit a relatively favorable residence time. These findings indicate that Y508-1233 is a putative MmpL3-targeting candidate with promising activity against drug-resistant tuberculosis, warranting further optimization and experimental validation.

Original languageEnglish
JournalMolecular Diversity
DOIs
Publication statusAccepted/In press - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • MmpL3 inhibitors
  • Molecular dynamics simulation
  • Mycobacterium tuberculosis
  • Pharmacophore model
  • Structure-based virtual screening
  • Tuberculosis
  • τRAMD simulation

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