Jiang Wang

Dr. Jiang Wang

State Key Laboratory of Drug Research, Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zu Chong Zhi Road, Shanghai 201203, China
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

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

Representative Publications

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19 June 2020 in Science
Verified
Journal Article
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WDWenhao Dai
Wenhao Dai
BZBing Zhang
Bing Zhang
XJXia-Ming Jiang
Xia-Ming Jiang
HSHaixia Su
Haixia Su
JLJian Li
Jian Li
Hong LiuHong Liu
Hong Liu
Promising antiviral protease inhibitors: With no vaccine or proven effective drug against the virus that causes coronavirus disease 2019 (COVID-19), scientists are racing to find clinical antiviral treatments. A promising drug target is the viral main protease M pro , which plays a key role in viral replication and transcription. Dai et al. designed two inhibitors, 11a and 11b, based on analyzing the structure of the M pro active site. Both strongly inhibited the activity of M pro and showed good antiviral activity in cell culture. Compound 11a had better pharmacokinetic properties and low toxicity when tested in mice and dogs, suggesting that this compound is a promising drug candidate. Science , this issue p. 1331

3 February 2020 in Organic Letters
Verified
Journal Article
Closed access
JPJingjing Peng
Jingjing Peng
CLChunpu Li
Chunpu Li
MKMirzadavlat Khamrakulov
Mirzadavlat Khamrakulov
Jiang WangJiang Wang
Jiang Wang
Hong LiuHong Liu
Hong Liu

6 July 2020 in Organic Chemistry Frontiers
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Journal Article
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ZFZunyun Fu
Zunyun Fu
XLXutong Li
Xutong Li
ZWZhaohui Wang
Zhaohui Wang
ZLZhaojun Li
Zhaojun Li
XLXiaohong Liu
Xiaohong Liu
MZMingyue Zheng
Mingyue Zheng
Here we report a feasibility study of a deep learning model for exploring the optimal reaction conditions for given chemical reactions. The model was trained to learn the relationships between the chemical contexts, reaction conditions and product yields based on high-quality existing experimental data, and then extrapolate reasonably to unseen reactions by in silico exploration of accessible reaction space. This strategy was applied to the Suzuki–Miyaura cross-coupling reaction to find the best catalysts for given reactants and at the same time to discover the optimum combination of the reaction conditions. We demonstrated that the trained model was able to determine the productive catalysts as well as the most favorable catalyst loading and reaction temperature for both modeled reactions and external unseen reactions. This work aims to provide an insight into the feasibility of introducing a deep learning method in the optimization of chemical reaction conditions.

11 January 2022 in Nature Communications
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Journal Article
Open access
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YCYaqiong Chen
Yaqiong Chen
Jiang WangJiang Wang
Jiang Wang
YWYibing Wang
Yibing Wang
PWPengfei Wang
Pengfei Wang
ZZZan Zhou
Zan Zhou
YLYi Liu
Yi Liu
The molecular targets and mechanisms of propolis ameliorating metabolic syndrome are not fully understood. Here, we report that Brazilian green propolis reduces fasting blood glucose levels in obese mice by disrupting the formation of CREB/CRTC2 transcriptional complex, a key regulator of hepatic gluconeogenesis. Using a mammalian two-hybrid system based on CREB-CRTC2, we identify artepillin C (APC) from propolis as an inhibitor of CREB-CRTC2 interaction. Without apparent toxicity, APC protects mice from high fat diet-induced obesity, decreases fasting glucose levels, enhances insulin sensitivity and reduces lipid levels in the serum and liver by suppressing CREB/CRTC2-mediated both gluconeogenic and SREBP transcriptions. To develop more potential drugs from APC, we designed and found a novel compound, A57 that exhibits higher inhibitory activity on CREB-CRTC2 association and better capability of improving insulin sensitivity in obese animals, as compared with APC. In this work, our results indicate that CREB/CRTC2 is a suitable target for developing anti-metabolic syndrome drugs.

16 July 2019 in The Journal of Organic Chemistry
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Journal Article
Closed access
HLHuihui Li
Huihui Li
CWChenglin Wu
Chenglin Wu
Hong LiuHong Liu
Hong Liu
Jiang WangJiang Wang
Jiang Wang

1 February 2014 in Nanomedicine: Nanotechnology, Biology and Medicine
Verified
Journal Article
Open access
YMYicheng Mao
Yicheng Mao
Jiang WangJiang Wang
Jiang Wang
YZYuan Zhao
Yuan Zhao
YWYun Wu
Yun Wu
KKKwang Joo Kwak
Kwang Joo Kwak
NMNatarajan Muthusamy
Natarajan Muthusamy
We describe here the development and characterization of the physicochemical and pharmacokinetic properties of a novel liposomal formulation for FTY720 delivery, LP-FTY720. The mean diameter of LP-FTY720 was ~157 nm, and the FTY720 entrapment efficiency was ~85%. The liposomal formulation protected FTY720 from degradation in aqueous buffer and showed toxicity in CLL patient B cells comparable to that of free FTY720. Following intravenous injection in ICR mice, LP-FTY720 had an increased elimination phase half-life (~28 vs. ~19 hr) and decreased clearance (235 vs. 778 mL/h/kg) compared to the free drug. Antibodies against CD19, CD20 and CD37 were incorporated into LP-FTY720, which provided targeted delivery to CLL patient B cells and thus achieved higher killing efficacy. The novel liposomal carrier of FTY720 demonstrated improved pharmacokinetic properties, comparable activity, and a potential platform for targeted delivery to CLL by overcoming the limited application of free FTY720 to B malignancy treatment. This team reports on a novel liposomal formulation for FTY720 delivery, demonstrating improved pharmacokinetic properties, comparable activity, and a potential platform for targeted delivery to CLL using antibodies incorporated in the liposomes. The method expected to overcome the limited application of free FTY720 to B malignancy treatment.