ChemiRise: a data-driven retrosynthesis engine

no code implementations • 9 Aug 2021 • Xiangyan Sun, Ke Liu, Yuquan Lin, Lingjie Wu, Haoming Xing, Minghong Gao, Ji Liu, Suocheng Tan, Zekun Ni, Qi Han, Junqiu Wu, Jie Fan

We have developed an end-to-end, retrosynthesis system, named ChemiRise, that can propose complete retrosynthesis routes for organic compounds rapidly and reliably.

Retrosynthesis

Molecular modeling with machine-learned universal potential functions

no code implementations • 6 Mar 2021 • Ke Liu, Zekun Ni, Zhenyu Zhou, Suocheng Tan, Xun Zou, Haoming Xing, Xiangyan Sun, Qi Han, Junqiu Wu, Jie Fan

Molecular modeling is an important topic in drug discovery.

Drug Discovery

Chemi-net: a graph convolutional network for accurate drug property prediction

no code implementations • 16 Mar 2018 • Ke Liu, Xiangyan Sun, Lei Jia, Jun Ma, Haoming Xing, Junqiu Wu, Hua Gao, Yax Sun, Florian Boulnois, Jie Fan

Absorption, distribution, metabolism, and excretion (ADME) studies are critical for drug discovery.

Drug Discovery Property Prediction

Prediction of amino acid side chain conformation using a deep neural network

no code implementations • 26 Jul 2017 • Ke Liu, Xiangyan Sun, Jun Ma, Zhenyu Zhou, Qilin Dong, Shengwen Peng, Junqiu Wu, Suocheng Tan, Günter Blobel, Jie Fan

A deep neural network based architecture was constructed to predict amino acid side chain conformation with unprecedented accuracy.

Protein Design Protein Folding