Advancements in protein structure prediction: A comparative overview of AlphaFold and its derivatives

作者：Yuktika Malhotra, Jerry John, Deepika Yadav, Deepshikha Sharma, Vanshika, Kamal Rawal, Vaibhav Mishra, Navaneet Chaturvedi · 发表于：Comput. Biol. Medicine · 年份：2025 · DOI：10.1016/j.compbiomed.2025.109842 · 被引用次数：33 · 研究领域：Medicine、Computer Science

This review provides a comprehensive analysis of AlphaFold (AF) and its derivatives (AF2 and AF3) in protein structure prediction. These tools have revolutionized structural biology with their highly accurate predictions, driving progress in protein modeling, drug discovery, and the study of protein dynamics. Its exceptional accuracy has redefined our understanding of protein folding, which enables groundbreaking advancements in protein design, disease research and discusses future integration with experimental techniques. In addition, their achievement features, architectures, important case studies, and noteworthy effects in the field of biology and medicine were evaluated. In consideration of the fact that AF2 is a relatively recent innovation, it has already been taken into account in many studies that highlight its applications in many ways. Moreover, the limitations of AF2 that directed to the introduction of AF3 are also reported, which is a great improvement as it provides precise predictions of the structures and interactions of proteins, DNA, RNA, and ligands, thereby aiding in the understanding of the molecular level. Addressing current challenges and forecasting future developments, this work underscores the lasting significance of AF in reshaping the scientific landscape of protein research.