| Molecular Mechanisms Underlying Antimicrobial Resistance and the Role of Artificial Intelligence in Developing Novel Therapeutics |
| Paper ID : 1289-IGA |
| Authors |
|
Sara Najafi * Department of Biology, Faculty of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran |
| Abstract |
| Background and Aim: Antimicrobial resistance (AMR) has emerged as a critical global health challenge, driven by complex molecular mechanisms such as efflux pump overexpression, enzymatic degradation, target modification, and biofilm formation. Despite extensive research, traditional approaches have struggled to keep pace with the rapid evolution of resistant pathogens. Artificial intelligence (AI) offers promising tools for accelerating the discovery and optimization of new therapeutics. This review aims to summarize the molecular basis of AMR and explore how AI technologies are being employed to develop novel treatment strategies. Methods: A comprehensive literature search was conducted using PubMed, Scopus, and Web of Science. Keywords included “antimicrobial resistance,” “molecular mechanisms,” “artificial intelligence,” “machine learning,” “drug discovery,” and “resistance genes.” Inclusion criteria encompassed English-language articles published between 2020 and 2025, focusing on AI applications in relation to molecular AMR mechanisms and drug development. Studies were screened and categorized based on AI method (e.g., deep learning, natural language processing) and biological focus (e.g., resistance gene prediction, compound screening). Results: The review identified key molecular mechanisms contributing to AMR and highlighted various AI-based approaches that target these mechanisms. AI models have been employed to predict resistance genes, identify novel antimicrobial compounds, optimize drug-target interactions, and repurpose existing drugs. These tools significantly reduced time and cost in early-phase therapeutic development. Conclusion: Understanding the molecular mechanisms of AMR is essential for designing targeted therapies. AI serves as a transformative tool, enabling faster, data-driven solutions for combating drug-resistant pathogens and supporting precision antimicrobial therapy. |
| Keywords |
| Antimicrobial Resistance (AMR), Molecular Mechanisms, Artificial Intelligence (AI), Drug Discovery, Machine Learning |
| Status: Accepted |
