Inspired by the classic lock-and-key model and advances in equivariant deep network design, we present a structure-based drug design model, SurfGen, which uses two types of equivariant graph neural networks to learn on protein surfaces and geometric structures to directly design small-molecule drugs.
This is a preview of subscription content, log in via an institution to check access.
References
Wang, X., Song, K., Li, L. & Chen, L. Structure-based drug design dstrategies and challenges. Curr. Top. Med. Chem. 18, 998–1006 (2018). A review article that illustrates the concept of structure-based drug design historically.
Isert, C., Atz, K. & Schneider, G. Structure-based drug design with geometric deep learning. Curr. Opin. Struct. Biol. 79, 102548 (2023). This paper reports the current development of structure-based drug design models.
Lancet, D., Horovitz, A. & Katchalski‐Katzir, E. In The Lock-and-Key Principle: The State of the Art — 100 Years On (ed. Behr, J.-P.) 25–71 (Wiley, 1994). This chapter provides an insightful discussion of the basis of the lock-and-key model.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This is a summary of: Zhang, O. et al. Learning on topological surface and geometric structure for 3D molecular generation. Nat. Comput. Sci. https://doi.org/10.1038/s43588-023-00530-2 (2023)
Rights and permissions
About this article
Cite this article
AI-powered structure-based drug design inspired by the lock-and-key model. Nat Comput Sci 3, 827–828 (2023). https://doi.org/10.1038/s43588-023-00552-w
Published:
Issue Date:
DOI: https://doi.org/10.1038/s43588-023-00552-w
- Springer Nature America, Inc.