Unexpected Applications of AlphaFold in Molecular Sciences
AlphaFold, a groundbreaking artificial intelligence model developed by DeepMind, has transformed the field of structural biology by predicting protein structures with unprecedented accuracy. Despite its widespread recognition and application across academia and industry, comprehensive reviews detailing AlphaFold's unexpected applications within the molecular sciences remain scarce. In this review, we critically examine AlphaFold's emerging roles across diverse molecular scientific disciplines. Specifically, we highlight its applications in enzyme engineering and drug development, nucleic acid modeling and vaccine design, the development of protein-based materials and targeted drug delivery systems, and modeling of complex systems and biological networks. To conclude, the review outlines potential future developments and enduring challenges within the application of AlphaFold to molecular sciences. Overall, this review aims to systematically analyze the most recent advances; explore novel interdisciplinary applications of AlphaFold within the realms of biology, chemistry, and materials science; and offer insights into future directions for research and application.
Authors
- B. S. Shengping Zhang
- Benjamin Jones (ORCID: https://orcid.org/0000-0001-7810-7770)
- Huahai Qiu
- Gang Wei (ORCID: https://orcid.org/0000-0001-7338-818X)
- Yazhou Shi
- Guilin Wang (ORCID: https://orcid.org/0009-0000-4223-6837)
- Tianshou Zhou
- Jian Jiang
- Nicole Hayes
- Daixin Li
Institutions
- Sun Yat-sen University (CN)
- Wuhan Textile University (CN)
- Michigan State University (US)
Publication Details
- Journal
- Annual Review of Biochemistry
- Published
- 2026-03-09
- DOI
- https://doi.org/10.1146/annurev-biochem-051424-071952
- Primary Topic
- Protein Structure and Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00