Oxford Protein Informatics Group (OPIG) (@opig.stats.ox.ac.uk)

MolSnapper has been published in @pubs.acs.org Journal of Chemical Information and Modeling! MolSnapper integrates expert knowledge into diffusion models for structure-based drug design using conditioning Congratulations Yael Ziv, Fergus Imrie, Brian Marsden, and Charlotte Deane shorturl.at/8PeWT

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MolSnapper: Conditioning Diffusion for Structure-Based Drug Design Generative models have emerged as potentially powerful methods for molecular design, yet challenges persist in generating molecules that effectively bind to the intended target. The ability to control the design process and incorporate prior knowledge would be highly beneficial for better tailoring molecules to fit specific binding sites. In this paper, we introduce MolSnapper, a novel tool that is able to condition diffusion models for structure-based drug design by seamlessly integrating expert knowledge in the form of 3D pharmacophores. We demonstrate through comprehensive testing on both the CrossDocked and Binding MOAD data sets that our method generates molecules better tailored to fit a given binding site, achieving high structural and chemical similarity to the original molecules. Additionally, MolSnapper yields approximately twice as many valid molecules as alternative methods. https://pubs.acs.org/doi/10.1021/acs.jcim.4c02008