biostudies-literatureLee JMinistry of Health and WelfareMinistry of Science and ICT, South Koreae02702https://www.ebi.ac.uk/biostudies/studies/S-EPMC12463045biostudies-literatureUnknown12(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 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.Advanced science (Weinheim, Baden-Wurttemberg, Germany)BInD: Bond and Interaction-Generating Diffusion Model for Multi-Objective Structure-Based Drug Design.PMC12463045RS‐2024‐00512498NRF-2022M3J6A1063021RS-2023-NR077040RS‐2023‐00257479RS-2024-00512498RS‐2023‐NR077040RS-2023-00257479NRF‐2022M3J6A1063021Seo JKim WYLee JZhung WfalseBInD: Bond and Interaction-Generating Diffusion Model for Multi-Objective Structure-Based Drug Design.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.2025-01-01T00:00:00Z2025 Sep2026-06-03T21:16:00.729Z2026-05-01T03:11:07.244ZS-EPMC124630454064289610.1002/advs.202502702