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REVIEW article

Front. Mol. Biosci.
Sec. Structural Biology
Volume 11 - 2024 | doi: 10.3389/fmolb.2024.1414916

AlphaFold2 in biomedical research: Facilitating the development of diagnostic strategies for disease

Provisionally accepted
Hong Zhang Hong Zhang Jiajing Lan Jiajing Lan Huijie Wang Huijie Wang Ruijie Lu Ruijie Lu Nanqi Zhang Nanqi Zhang Xiaobai He Xiaobai He Linjie Chen Linjie Chen *
  • School of Laboratory Medicine, Hangzhou Medical College, Hangzhou, Zhejiang Province, China

The final, formatted version of the article will be published soon.

    Proteins, as the primary executors of physiological activity, serve as a key factor in disease diagnosis and treatment. Research into their structures, functions, and interactions is essential to better understand disease mechanisms and potential therapies. DeepMind's AlphaFold2, a deep-learning protein structure prediction model, has proven to be remarkably accurate, and it is widely employed in various aspects of diagnostic research, such as the study of disease biomarkers, microorganism pathogenicity, antigen-antibody structures, and missense mutations. Thus, AlphaFold2 serves as an exceptional tool to bridge fundamental protein research with breakthroughs in disease diagnosis, developments in diagnostic strategies, and the design of novel therapeutic approaches and enhancements in precision medicine. This review outlines the architecture, highlights, and limitations of AlphaFold2, placing particular emphasis on its applications within diagnostic research grounded in disciplines such as immunology, biochemistry, molecular biology, and microbiology.

    Keywords: AlphaFold2, deep learning, protein structure prediction, Structural Biology, Disease diagnosis

    Received: 09 Apr 2024; Accepted: 15 Jul 2024.

    Copyright: © 2024 Zhang, Lan, Wang, Lu, Zhang, He and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Linjie Chen, School of Laboratory Medicine, Hangzhou Medical College, Hangzhou, 310053, Zhejiang Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.