184 citations · 249 across the 10 of their papers we have counts for
4 papers · 1 filter
Accelerating Discovery of Novel and Bioactive Ligands With Pharmacophore-Informed Generative Models
Weixin Xie, Jianhang Zhang, Qin Xie +4
Deep generative models have gained significant advancements to accelerate drug discovery by generating bioactive chemicals against desired targets. Nevertheless, most generated com…
Synthesis-driven design of 3D molecules for structure-based drug discovery using geometric transformers
Yibo Li, Jianfeng Pei, Luhua Lai
Finding drug-like compounds with high bioactivity is essential for drug discovery, but the task is complicated by the high cost of chemical synthesis and validation. With their out…
Learning to design drug-like molecules in three-dimensional space using deep generative models
Yibo Li, Jianfeng Pei, Luhua Lai
Recently, deep generative models for molecular graphs are gaining more and more attention in the field of de novo drug design. A variety of models have been developed to generate t…
Automatic Retrosynthetic Pathway Planning Using Template-free Models
Kangjie Lin, Youjun Xu, Jianfeng Pei +1
We present an attention-based Transformer model for automatic retrosynthesis route planning. Our approach starts from reactants prediction of single-step organic reactions for give…