The AI Revolution in Protein Science Current Status and Future Prospects for Biopharmaceutical Applications

Abstract

Artificial intelligence has catalyzed a paradigm shift in protein science, transforming our ability to predict protein structures, design novel proteins, and develop next-generation biopharmaceuticals. This review synthesizes recent breakthroughs in AI-driven protein structure prediction, de novo protein design, and biopharmaceutical engineering. We examine how AlphaFold, RoseTTAFold, and generative AI models have achieved unprecedented accuracy in structure prediction and enabled the creation of functional proteins with tailored properties. The review highlights successful applications in therapeutic antibody design, enzyme engineering, and toxin neutralization, while addressing current limitations and future opportunities at the intersection of AI and protein science. We further explore how these technologies are being integrated with plant-based biopharmaceutical production systems to overcome traditional challenges in yield, stability, and post-translational modifications. As AI continues to advance, its integration with experimental validation will accelerate the development of novel protein-based therapeutics and sustainable biomanufacturing platforms.