Xingzhou Li

Dr. Xingzhou Li


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2020 in Acta Pharmaceutica Sinica B
Verified
Journal Article
Open access
CWCanrong Wu
Canrong Wu
YLYang Liu
Yang Liu
YYYueying Yang
Yueying Yang
PZPeng Zhang
Peng Zhang
WZWu Zhong
Wu Zhong
HLHua Li
Hua Li
SARS-CoV-2 has caused tens of thousands of infections and more than one thousand deaths. There are currently no registered therapies for treating coronavirus infections. Because of time consuming process of new drug development, drug repositioning may be the only solution to the epidemic of sudden infectious diseases. We systematically analyzed all the proteins encoded by SARS-CoV-2 genes, compared them with proteins from other coronaviruses, predicted their structures, and built 19 structures that could be done by homology modeling. By performing target-based virtual ligand screening, a total of 21 targets (including two human targets) were screened against compound libraries including ZINC drug database and our own database of natural products. Structure and screening results of important targets such as 3-chymotrypsin-like protease (3CLpro), Spike, RNA-dependent RNA polymerase (RdRp), and papain like protease (PLpro) were discussed in detail. In addition, a database of 78 commonly used anti-viral drugs including those currently on the market and undergoing clinical trials for SARS-CoV-2 was constructed. Possible targets of these compounds and potential drugs acting on a certain target were predicted. This study will provide new lead compounds and targets for further in vitro and in vivo studies of SARS-CoV-2, new insights for those drugs currently ongoing clinical studies, and also possible new strategies for drug repositioning to treat SARS-CoV-2 infections.

1 March 2020 in Bioorganic Chemistry
Verified
Journal Article
Closed access
YLYang Liu
Yang Liu
MLMingxue Li
Mingxue Li
YZYujie Zhang
Yujie Zhang
CWCanrong Wu
Canrong Wu
KYKaiyin Yang
Kaiyin Yang
LCLixia Chen
Lixia Chen

1 December 2020 in European Journal of Medicinal Chemistry
Verified
Journal Article
Closed access
BHBeichen Hu
Beichen Hu
YZYirong Zhou
Yirong Zhou
DSDejuan Sun
Dejuan Sun
YYYueying Yang
Yueying Yang
YLYang Liu
Yang Liu
LCLixia Chen
Lixia Chen

1 November 2019 in Bioorganic Chemistry
Verified
Journal Article
Closed access
KYKai-Yin Yang
Kai-Yin Yang
CWCan-Rong Wu
Can-Rong Wu
MZMeng-Zhu Zheng
Meng-Zhu Zheng
RTRuo-Tian Tang
Ruo-Tian Tang
XLXingzhou Li
Xingzhou Li
HLHua Li
Hua Li

5 January 2023 in Molecules
Verified
Journal Article
Open access
PDF file
HJHongshan Jin
Hongshan Jin
CWChengjun Wu
Chengjun Wu
RSRui Su
Rui Su
TSTiemin Sun
Tiemin Sun
XLXingzhou Li
Xingzhou Li
GCGuo Chun
Guo Chun
The dopamine D3 receptor (D3R) is an important central nervous system target for treating various neurological diseases. D3R antagonists modulate the improvement of psychostimulant addiction and relapse, while D3R agonists can enhance the response to dopaminergic stimulation and have potential applications in treating Parkinson’s disease, which highlights the importance of identifying novel D3R ligands. Therefore, we performed auto dock Vina-based virtual screening and D3R-binding-affinity assays to identify human D3R ligands with diverse structures. All molecules in the ChemDiv library (>1,500,000) were narrowed down to a final set of 37 molecules for the binding assays. Twenty-seven compounds exhibited over 50% inhibition of D3R at a concentration of 10 μM, and 23 compounds exhibited over 70% D3R inhibition at a concentration of 10 μM. Thirteen compounds exhibited over 80% inhibition of D3R at a concentration of 10 μM and the IC50 values were measured. The IC50 values of the five compounds with the highest D3R-inhibition rates ranged from 0.97 μM to 1.49 μM. These hit compounds exhibited good structural diversity, which prompted us to investigate their D3R-binding modes. After trial and error, we combined unbiased molecular dynamics simulation (MD) and molecular mechanics generalized Born surface area (MM/GBSA) binding free-energy calculations with the reported protein–ligand-binding pose prediction method using induced-fit docking (IFD) and binding pose metadynamics (BPMD) simulations into a self-consistent and computationally efficient method for predicting and verifying the binding poses of the hit ligands to D3R. Using this IFD-BPMD-MD-MM/GBSA method, we obtained more accurate and reliable D3R–ligand-binding poses than were obtained using the reported IFD-BPMD method. This IFD-BPMD-MD-MM/GBSA method provides a novel paradigm and reference for predicting and validating other protein–ligand binding poses.

2 April 2019 in Organic Chemistry Frontiers
Verified
Journal Article
Closed access
PDF file
DXDongyang Xu
Dongyang Xu
HWHongbo Wei
Hongbo Wei
YZYanxia Zhen
Yanxia Zhen
YGYu-Qi Gao
Yu-Qi Gao
RLRuoxin Li
Ruoxin Li
WXWeiqing Xie
Weiqing Xie
Herein, we disclose that carboxylate phosphabetaine can act as a competent organocatalyst for promoting the intramolecular ring opening of oxetanes, delivering oxazolidin-2-ones in good to excellent yields. 1H NMR studies and DFT calculations revealed that the carboxylate moiety of the phosphabetaine not only acts as a proton shuttle, but also provides crucial hydrogen bonding for the activation of the oxetane ring.