Structure-based Drug Design with Equivariant Diffusion Models

• URL: http://arxiv.org/abs/2210.13695v2
• Date: Fri, 30 Jun 2023 09:55:28 GMT
• Title: Structure-based Drug Design with Equivariant Diffusion Models
• Authors: Arne Schneuing, Yuanqi Du, Charles Harris, Arian Jamasb, Ilia Igashov, Weitao Du, Tom Blundell, Pietro Li\'o, Carla Gomes, Max Welling, Michael Bronstein, Bruno Correia
• Abstract summary: We formulate DiffSBDD as a 3D-conditional generation problem for structure-based drug design (SBDD) Comprehensive in silico experiments demonstrate the efficiency and effectiveness of DiffSBDD in generating novel and diverse drug-like with competitive docking. We further explore the flexibility of diffusion framework for a broader range of tasks in drug design campaigns, such as off-the-shelf property optimization and partial molecular design with inpainting.
• Score: 43.12251246600906
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. In this paper, we formulate SBDD as a 3D-conditional generation problem and present DiffSBDD, an SE(3)-equivariant 3D-conditional diffusion model that generates novel ligands conditioned on protein pockets. Comprehensive in silico experiments demonstrate the efficiency and effectiveness of DiffSBDD in generating novel and diverse drug-like ligands with competitive docking scores. We further explore the flexibility of the diffusion framework for a broader range of tasks in drug design campaigns, such as off-the-shelf property optimization and partial molecular design with inpainting.

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