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AI-powered structure-based drug design inspired by the lock-and-key model

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.

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Fig. 1: Comparison of SurfGen to other frameworks for structure-based drug design for 3CL, a COVID-19 drug target.

References

  1. 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.

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  2. 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.

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  3. 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.

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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)

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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

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