4 citations · 15 across the 7 of their papers we have counts for
7 papers
Deep Lead Optimization: Leveraging Generative AI for Structural Modification
Odin Zhang, Haitao Lin, Hui Zhang +7
The idea of using deep-learning-based molecular generation to accelerate discovery of drug candidates has attracted extraordinary attention, and many deep generative models have be…
AAVDiff: Experimental Validation of Enhanced Viability and Diversity in Recombinant Adeno-Associated Virus (AAV) Capsids through Diffusion Generation
Lijun Liu, Jiali Yang, Jianfei Song +8
Recombinant adeno-associated virus (rAAV) vectors have revolutionized gene therapy, but their broad tropism and suboptimal transduction efficiency limit their clinical applications…
Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation
Odin Zhang, Yufei Huang, Shichen Cheng +14
Most earlier 3D structure-based molecular generation approaches follow an atom-wise paradigm, incrementally adding atoms to a partially built molecular fragment within protein pock…
Delete: Deep Lead Optimization Enveloped in Protein Pocket through Unified Deleting Strategies and a Structure-aware Network
Haotian Zhang, Huifeng Zhao, Xujun Zhang +10
Drug discovery is a highly complicated process, and it is unfeasible to fully commit it to the recently developed molecular generation methods. Deep learning-based lead optimizatio…
MolHF: A Hierarchical Normalizing Flow for Molecular Graph Generation
Yiheng Zhu, Zhenqiu Ouyang, Ben Liao +5
Molecular de novo design is a critical yet challenging task in scientific fields, aiming to design novel molecular structures with desired property profiles. Significant progress h…
An Equivariant Generative Framework for Molecular Graph-Structure Co-Design
Zaixi Zhang, Qi Liu, Chee-Kong Lee +2
Designing molecules with desirable physiochemical properties and functionalities is a long-standing challenge in chemistry, material science, and drug discovery. Recently, machine…