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Targeting Mycobacterial Dormancy Survival Regulator (DosR) With Generative Artificial Intelligence and Omics Methods.

Monishka Battula1, Samiksha Bhor1, Shovonlal Bhowmick1

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Researchers identified novel Mycobacterium tuberculosis DosR inhibitors using computational methods. These compounds show promise for treating dormant tuberculosis, a persistent global health issue.

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REINVENT4consensus sequence analysisdormancy mechanismsdormancy survival regulator (DosR) proteinmolecular dockingmolecular dynamics (MD) simulations

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Area of Science:

  • Biochemistry and Molecular Biology
  • Computational Chemistry
  • Drug Discovery

Background:

  • Tuberculosis (TB) remains a significant global health threat, primarily due to Mycobacterium tuberculosis's ability to enter a dormant state.
  • This dormancy allows the pathogen to evade immune responses and resist conventional antibiotic treatments.
  • The dormancy survival regulator (DosR) protein is crucial for this survival mechanism, making it a key therapeutic target.

Purpose of the Study:

  • To identify novel inhibitors of the DosR protein using a comprehensive in silico approach.
  • To develop a robust computational framework for discovering new drugs against dormant tuberculosis.

Main Methods:

  • In silico analysis including domain and motif analysis, multiple sequence alignment (MSA), and consensus sequence generation.
  • Screening of FDA-approved compounds via molecular docking against the DosR active site.
  • De novo molecule generation using REINVENT4, followed by ADMET analysis, molecular dynamics (MD) simulations, and MMGBSA.

Main Results:

  • Identified conserved regions within the DosR protein across various Mycobacterium species.
  • Screened FDA-approved compounds and generated a novel library of potential inhibitors.
  • Selected top 5 compounds, including RI081, RI089, and RI107, demonstrating stability and strong binding affinity to DosR.

Conclusions:

  • The multi-tiered computational approach successfully identified promising novel inhibitors of the DosR protein.
  • These findings provide a strong foundation for developing new therapeutic strategies against dormant tuberculosis.
  • The developed framework can be applied to the discovery of inhibitors for other essential bacterial proteins.