Haiping Zhang

TL;DR: A protein 3D model of 3C-like protease is built using homology modeling and a pipeline is used to perform large scale virtual screening by using a deep learning based method to accurately rank/identify protein–ligand interacting pairs developed recently in this group.

TL;DR: A new deep neural network-based model named DeepBindRG is proposed to predict the binding affinity of protein–ligand complex, which learns all the effects, binding mode, and specificity implicitly implicitly by learning protein-ligand interface contact information from a large protein—ligand dataset.

TL;DR: This paper collected virus RNA sequences from the GISAID database, translated the RNA sequences into protein sequences, and built a protein 3D model using homology modeling, which focused on drug screening based on the modeled 2019-nCov_main_protease structure.

TL;DR: In this paper, a hybrid drug screening procedure was proposed and applied to identify potential drug candidates targeting RNA-dependent RNA polymerase (RdRp) from 1906 approved drugs, and Pralatrexate and Azithromycin were confirmed to effectively inhibit SARS-CoV-2 replication in vitro with EC50 values of 0.008μM and 9.453 μM, respectively.

TL;DR: In this paper, the authors propose gradient amplification approach for training deep learning models to prevent vanishing gradients and also develop a training strategy to enable or disable gradient amplification method across several epochs with different learning rates.