Biochemoinformatics approaches to combating bacterial resistance: advances, challenges and perspectives

Antimicrobial resistance constitutes a major global public health problem that undermines treatment efficacy and increases morbidity and mortality associated with bacterial infections. In light of this challenging scenario and the limitations of conventional therapies, the development of innovative strategies for discovering new antimicrobial agents has become essential. Within this context, this article aims to review the advances, challenges, and future perspectives of biochemoinformatics in combating bacterial resistance. The methodology consists of a narrative literature review addressing molecular mechanisms of resistance, the use of structural databases such as the Protein Data Bank (PDB), and the application of hierarchical pipelines that integrate virtual screening, molecular modeling, ADME/Tox prediction, and experimental validation. The analyzed studies indicate that biochemoinformatics accelerates drug discovery, reduces costs, and identifies promising candidates with higher potential for biological activity, including against critical pathogens such as Klebsiella pneumoniae. Thus, the integration of computational tools, artificial intelligence, and biological validation establishes this approach as a promising strategy for drug design against multidrug-resistant strains.