23 citations · 30 across the 6 of their papers we have counts for
6 papers
PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross Docking
Yize Jiang, Xinze Li, Yuanyuan Zhang +13
Existing protein-ligand docking studies typically focus on the self-docking scenario, which is less practical in real applications. Moreover, some studies involve heavy frameworks…
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…
MolMiner: You only look once for chemical structure recognition
Youjun Xu, Jinchuan Xiao, Chia-Han Chou +13
Molecular structures are always depicted as 2D printed form in scientific documents like journal papers and patents. However, these 2D depictions are not machine-readable. Due to a…
Deep Learning Model of Dock by Dock Process Significantly Accelerate the Process of Docking-based Virtual Screening
Wei Ma, Qin Xie, Jianhang Zhang +4
Docking-based virtual screening (VS process) selects ligands with potential pharmacological activities from millions of molecules using computational docking methods, which greatly…
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…
Deep Learning Based Regression and Multi-class Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction
Youjun Xu, Jianfeng Pei, Luhua Lai
For quantitative structure-property relationship (QSPR) studies in chemoinformatics, it is important to get interpretable relationship between chemical properties and chemical feat…