most citedDecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design

26 citations · 37 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design

Xiangxin Zhou, Jiaqi Guan, Yijia Zhang +3

Dual-target therapeutic strategies have become a compelling approach and attracted significant attention due to various benefits, such as their potential in overcoming drug resista…

q-bio.BM20241 cited

Bridging Text and Molecule: A Survey on Multimodal Frameworks for Molecule

Yi Xiao, Xiangxin Zhou, Qiang Liu +1

Artificial intelligence has demonstrated immense potential in scientific research. Within molecular science, it is revolutionizing the traditional computer-aided paradigm, ushering…

q-bio.BM20248 cited

DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization

Xiangxin Zhou, Xiwei Cheng, Yuwei Yang +3

Recently, 3D generative models have shown promising performances in structure-based drug design by learning to generate ligands given target binding sites. However, only modeling t…

q-bio.BM202426 cited

DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design

Jiaqi Guan, Xiangxin Zhou, Yuwei Yang +6

Designing 3D ligands within a target binding site is a fundamental task in drug discovery. Existing structured-based drug design methods treat all ligand atoms equally, which ignor…

q-bio.BM20242 cited

Binding-Adaptive Diffusion Models for Structure-Based Drug Design

Zhilin Huang, Ling Yang, Zaixi Zhang +6

Structure-based drug design (SBDD) aims to generate 3D ligand molecules that bind to specific protein targets. Existing 3D deep generative models including diffusion models have sh…