Review of AlphaFold3: A Groundbreaking Tool for Biomedical Applications

Abstract

AlphaFold3 (AF3) is the latest generation of protein structure prediction models released by DeepMind in collaboration with Homology Labs in 2024, achieving a technological leap forward from the previous two generations of AlphaFold (AF) models. AF3 pioneers a diffusion-based model, significantly enhancing its ability to predict three-dimensional structures for diverse biomolecules—including proteins, ligands, nucleic acids, and their complexes. It demonstrates exceptional precision in modeling interactions such as protein-protein, protein-nucleic acid, and antibody-antigen pairs. This paper systematically reviews the development history, core principles, and typical applications of AF3 in critical medical fields, including structural biology, disease mechanism analysis, drug target screening, and antibody design. It outlines breakthroughs and advantages over previous models while analyzing limitations in dynamic conformation prediction, environmental factor modeling, structural plausibility, and accessibility. It further summarizes enhancement strategies employed by multiple derivative models for affinity prediction and complex modeling, while projecting future research trends toward AI modeling integrated with experimental validation and multi-omics fusion. This work provides theoretical support and technical references for precision medicine and drug discovery.