Guomeng Xing
China Pharmaceutical University
7 Papers
1 Citations
Guomeng Xing is an academic researcher from China Pharmaceutical University. The author has contributed to research in topics: Chemistry & Medicine. The author has an hindex of 2, co-authored 2 publications.
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Papers
Drug repositioning: Progress and challenges in drug discovery for various diseases
TL;DR: In this article , a series of representative drugs that have been repositioned for different diseases and illustrated successful cases in each disease were systematically reviewed and the mechanism of action for the representative drugs in new indications were explicitly explored for each disease, and the review can provide important insights for follow-up research.
119
Discovery of Dual FGFR4 and EGFR Inhibitors by Machine Learning and Biological Evaluation.
Xingye Chen,Wuchen Xie,Yan Yang,Yi Hua,Guomeng Xing,Li Liang,Chenglong Deng,Yuchen Wang,Yuanrong Fan,Haichun Liu,Tao Lu,Yadong Chen,Yanmin Zhang +12 more
TL;DR: The machine learning based QSAR models were established and effectively applied to the discovery of dual-target inhibitors against FGFR4 and EGFR, demonstrating the great potential of machine learning strategies in dual inhibitor discovery.
32
Activity Prediction of Small Molecule Inhibitors for Antirheumatoid Arthritis Targets Based on Artificial Intelligence.
Guomeng Xing,Li Liang,Chenglong Deng,Yi Hua,Xingye Chen,Yan Yang,Haichun Liu,Tao Lu,Yadong Chen,Yanmin Zhang +9 more
TL;DR: The integrated model proposed is promising to screen dual-target inhibitors of SYK/JAK or BTK/ JAK as RA drugs, which is beneficial for the clinical treatment of rheumatoid arthritis.
17
Accurate calculation of absolute free energy of binding for SHP2 allosteric inhibitors using free energy perturbation.
Li Liang,Haichun Liu,Guomeng Xing,Cheng Jin Deng,Yi Hua,Rui Gu,Tao Lu,Yadong Chen,Yanmin Zhang +8 more
TL;DR: This study demonstrates the possibility to accurately calculate the absolute binding free energy of allosteric inhibitors using FEP, which offers exciting prospects for the discovery of more effective allosterIC inhibitors.
5
Effective Reaction-Based De Novo Strategy for Kinase Targets: A Case Study on MERTK Inhibitors
Yi Hua,Xiaobao Fang,Guomeng Xing,Yuan Xu,Li Liang,Cheng Jin Deng,Xiaowen Dai,Haichun Liu,Tao Lu,Yanmin Zhang,Yadong Chen +10 more
TL;DR: This work first adopted a recurrent neural network (RNN) model to generate three groups of building blocks with different functional groups and then constructed an in silico target-focused combinatorial library based on chemical reaction rules.