Redefining Biomolecular Frontiers: The Impact of Artificial Intelligence in Biochemistry and Medicine

David Anih, Kayode Arowora, Moses Abah, Kenneth Ugwuoke and Bilyaminu Habibu

Artificial Intelligence (AI) is redefining the frontiers of biochemistry and medicine by enhancing molecular understanding, diagnostic precision and therapeutic discovery. This review examines the transformative roles of AI across key biomedical domains, including medical imaging, disease prediction, protein structure modeling, drug development, enzyme engineering and multiomics integration. Deep learning architectures, such as convolutional neural networks and transformers, now surpass traditional diagnostic approaches in accuracy and efficiency, particularly in neuroimaging for conditions like Alzheimer’s disease. Tools like AlphaFold2 and generative models (e.g., ChemBERTa, MolGPT) have revolutionized protein structure prediction and de novo drug design. AI-driven strategies also empower personalized medicine through real-time health monitoring, wearable integration and omics-based systems biology. Despite these advances, challenges remain including data heterogeneity, model interpretability, ethical concerns and global disparities in AI access. This manuscript addresses these barriers by highlighting solutions such as explainable AI, open-source platforms and international collaboration. Furthermore, emerging applications, including AI-enhanced microplastic toxicology, sleep biochemistry, herbal compound modeling and gut microbiota host interaction mapping, illustrate the interdisciplinary breadth and future potential of AI in biochemistry. By synthesizing foundational developments with next-generation innovations, this review affirms AI’s role as a catalyst for accelerating discovery, improving healthcare equity and reshaping the molecular sciences for the next era of research and clinical translation.

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