Journal of Biomedical Advancement Scientific Research

Abstract

Protein engineering has become a cornerstone of modern biotechnology and therapeutic development, en abling the design and optimization of proteins for applications ranging from biologics and vaccines to pre cision therapeutics. Recent advances in artificial intelligence (AI) have fundamentally transformed this field by accelerating protein structure prediction, function analysis, sequence optimization, and de novo protein design. This review provides an overview of the emerging role of AI in protein engineering and its implica tions for therapeutic development and precision medicine. Key AI-driven technologies, including machine learning, deep learning, protein language models, and generative AI, are discussed in the context of protein structure prediction, function prediction, and rational protein design. The review further examines the ap plication of these technologies in therapeutic protein development, antibody engineering, vaccine design, immunotherapy, and AI-assisted drug discovery. Particular attention is given to the integration of AI with multi-omics technologies, which enables the identification of patient-specific molecular characteristics and supports the development of personalized therapeutic strategies. The convergence of AI, protein engineer ing, and precision medicine has created new opportunities for designing biologics tailored to individual disease mechanisms and patient profiles. Despite these advances, challenges related to data quality, model interpretability, experimental validation, ethical considerations, and regulatory oversight remain important barriers to widespread clinical implementation. Emerging technologies, including biological foundation models, generative AI systems, autonomous protein engineering platforms, and digital twin technologies, are expected to further expand the capabilities of AI-driven therapeutic design. Collectively, these develop ments position AI as a transformative force in protein engineering, accelerating therapeutic innovation and supporting the transition toward more precise, personalized, and effective healthcare solutions.