Abstract
The identification of new anticancer agents is essential for addressing chemotherapy resistance, a significant obstacle in cancer treatment. Soil microorganisms have proven to be a rich source of bioactive substances, and the integration of Artificial Intelligence (AI) is transforming drug discovery by streamlining screening and development processes. This systematic review examines the contributions of microbial metabolites from soil in cancer therapy, their mechanisms against chemotherapy resistance, and the role of AI in improving drug discovery. A systematic review of the literature was performed in accordance with PRISMA guidelines, utilizing databases such as PubMed, Scopus, and Web of Science. Included studies focused on anticancer compounds derived from microorganisms, their molecular actions, AI-facilitated drug discovery methods, and approaches to Mitigate Multidrug Resistance (MDR). Soil-derived microorganisms, particularly those from the genera Streptomyces, Bacillus, and Nocardiopsis, generate significant anticancer agents like doxorubicin, mitomycin C, and bleomycin. These agents demonstrate cytotoxicity through mechanisms such as inducing apoptosis, intercalating DNA, and inhibiting angiogenesis. Techniques driven by AI-such as deep learning and machine learning-have improved the detection of new microbial metabolites while facilitating predictions regarding drug interactions and enhancing chemotherapy effectiveness. Additionally, compounds from these microorganisms combat MDR by blocking efflux pumps, influencing apoptosis pathways, and disrupting DNA repair mechanisms. Utilizing soil microorganisms for the development of anticancer drugs alongside AI-enhanced screening represents a promising strategy to tackle chemotherapy resistance. Future investigations should prioritize metagenomic research, AI-guided genome exploration, and translational studies aimed at bringing microbial-derived compounds into clinical use. This interdisciplinary approach has great potential for creating next-generation cancer therapies that are more effective with minimized resistance.
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Keywords
Soil Microorganisms
Anticancer Compounds
Artificial Intelligence
Drug Discovery
Chemotherapy Resistance
Multidrug Resistance
Microbial Metabolites
Oncology
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