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BInD: Bond and Interaction-Generating Diffusion Model for Multi-Objective Structure-Based Drug Design.


ABSTRACT: Recent remarkable advancements in geometric deep generative models, coupled with accumulated structural data, enable structure-based drug design (SBDD) using only target protein information. However, existing models often struggle to balance multiple objectives, excelling only in specific tasks. BInD, a diffusion model with knowledge-based guidance, is introduced to address this limitation by co-generating molecules and their interactions with a target protein. This approach ensures balanced consideration of key objectives, including target-specific interactions, molecular properties, and local geometry. Comprehensive evaluations demonstrate that BInD achieves robust performance across all objectives, matching or surpassing state-of-the-art methods. Additionally, an NCI-driven molecule design and optimization method is proposed, enabling the enhancement of target binding and specificity by elaborating the adequate interaction patterns.

SUBMITTER: Lee J 

PROVIDER: S-EPMC12463045 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature

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BInD: Bond and Interaction-Generating Diffusion Model for Multi-Objective Structure-Based Drug Design.

Lee Joongwon J   Zhung Wonho W   Seo Jisu J   Kim Woo Youn WY  

Advanced science (Weinheim, Baden-Wurttemberg, Germany) 20250711 35


Recent remarkable advancements in geometric deep generative models, coupled with accumulated structural data, enable structure-based drug design (SBDD) using only target protein information. However, existing models often struggle to balance multiple objectives, excelling only in specific tasks. BInD, a diffusion model with knowledge-based guidance, is introduced to address this limitation by co-generating molecules and their interactions with a target protein. This approach ensures balanced con  ...[more]

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