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September 2, 2026Beni-Suef University Journal of Basic and Applied SciencesOpen Access

An overview of bioinformatics approaches to understand drug resistance and identifying novel inhibitors against multidrug-resistant Mycobacterium tuberculosis

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Authors

EGErik GeorgeMSMahima SenthilkumarKTKavitha Thirupugazh

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Overview

Review demonstrates computational strategies to target multidrug-resistant Mycobacterium tuberculosis, highlighting the role of bioinformatics and artificial intelligence in accelerating drug...

Key Points

  • To comprehensively evaluate bioinformatics strategies that integrate drug-resistance mutation profiles with computational drug discovery to identify novel targets and inhibitors against multidrug-resistant Mycobacterium tuberculosis.
  • Synthesized computational discovery pipelines including subtractive genomics, molecular docking, and molecular dynamics simulations to isolate pathogen-specific targets lacking host homology.
  • Assessed machine learning prioritisation, multi-omics data integration, peptide exploration, natural product screening, and drug repurposing techniques.
  • Integrative computational pipelines accelerate early-stage discovery and substantially lower costs by identifying high-affinity, pathogen-specific targets.
  • Combining multi-omics data with artificial intelligence enables strain-specific treatment strategies, though hurdles remain in translating predictions to clinical validation.

Cite This Study

George et al. (2026) studied this question.

synapsesocial.com/papers/6a97e29ec562ede874ec6dfbhttps://doi.org/10.1186/s43088-026-00825-z
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