Shuguang Yuan

Prof. Dr. Shuguang Yuan

Research Center for Computer-Aided Drug Discovery, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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5 January 2017 in WIREs Computational Molecular Science
Verified
Journal Article
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SYShuguang Yuan
Shuguang Yuan
HCH.C. Stephen Chan
H.C. Stephen Chan
ZHZhenquan Hu
Zhenquan Hu

1 August 2019 in Trends in Pharmacological Sciences
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Journal Article
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HCH.C. Stephen Chan
H.C. Stephen Chan
HSHanbin Shan
Hanbin Shan
TDThamani Dahoun
Thamani Dahoun
HVHorst Vogel
Horst Vogel
SYShuguang Yuan
Shuguang Yuan

1 March 2012 in Current Medicinal Chemistry
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Journal Article
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Bartosz TrzaskowskiBartosz Trzaskowski
Bartosz Trzaskowski
DLD. Latek
D. Latek
SYShuguang Yuan
Shuguang Yuan
UGU. Ghoshdastider
U. Ghoshdastider
ADA. Debinski
A. Debinski
Sławomir FilipekSławomir Filipek
Sławomir Filipek
G protein coupled receptors (GPCRs), also called 7TM receptors, form a huge superfamily of membrane proteins that, upon activation by extracellular agonists, pass the signal to the cell interior. Ligands can bind either to extracellular N-terminus and loops (e.g. glutamate receptors) or to the binding site within transmembrane helices (Rhodopsin-like family). They are all activated by agonists although a spontaneous auto-activation of an empty receptor can also be observed. Biochemical and crystallographic methods together with molecular dynamics simulations and other theoretical techniques provided models of the receptor activation based on the action of so-called “molecular switches” buried in the receptor structure. They are changed by agonists but also by inverse agonists evoking an ensemble of activation states leading toward different activation pathways. Switches discovered so far include the ionic lock switch, the 3-7 lock switch, the tyrosine toggle switch linked with the nPxxy motif in TM7, and the transmission switch. The latter one was proposed instead of the tryptophan rotamer toggle switch because no change of the rotamer was observed in structures of activated receptors. The global toggle switch suggested earlier consisting of a vertical rigid motion of TM6, seems also to be implausible based on the recent crystal structures of GPCRs with agonists. Theoretical and experimental methods (crystallography, NMR, specific spectroscopic methods like FRET/BRET but also single-molecule-force-spectroscopy) are currently used to study the effect of ligands on the receptor structure, location of stable structural segments/domains of GPCRs, and to answer the still open question on how ligands are binding: either via ensemble of conformational receptor states or rather via induced fit mechanisms. On the other hand the structural investigations of homoand heterodimers and higher oligomers revealed the mechanism of allosteric signal transmission and receptor activation that could lead to design highly effective and selective allosteric or ago-allosteric drugs.

1 February 2020 in Cell
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Journal Article
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THTian Hua
Tian Hua
XLXiaoting Li
Xiaoting Li
LWLijie Wu
Lijie Wu
CIChristos Iliopoulos-Tsoutsouvas
Christos Iliopoulos-Tsoutsouvas
YWYuxia Wang
Yuxia Wang
ZLZhi-Jie Liu
Zhi-Jie Liu

20 May 2020 in Frontiers in Pharmacology
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WCWenqiang Cui
Wenqiang Cui
AAAdnane Aouidate
Adnane Aouidate
SWShouguo Wang
Shouguo Wang
QYQiuliyang Yu
Qiuliyang Yu
YLYanhua Li
Yanhua Li
SYShuguang Yuan
Shuguang Yuan
New drug discovery has been acknowledged as a complicated, expensive, time-consuming, and challenging project. It has been estimated that around 12 years and 2.7 billion USD, on average, are demanded for a new drug discovery via traditional drug development pipeline. How to reduce the research cost and speed up the development process of new drug discovery has become a challenging, urgent question for the pharmaceutical industry. Computer-aided drug discovery (CADD) has emerged as a powerful, and promising technology for faster, cheaper, and more effective drug design. Recently, the rapid growth of computational tools for drug discovery, including anticancer therapies, has exhibited a significant and outstanding impact on anticancer drug design, and has also provided fruitful insights into the area of cancer therapy. In this work, we discussed the different subareas of the computer-aided drug discovery process with a focus on anticancer drugs.

11 July 2018 in Nature
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Journal Article
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YYYan Yan
Yan Yan
QLQikun Liu
Qikun Liu
XZXin Zang
Xin Zang
SYShuguang Yuan
Shuguang Yuan
UBUndramaa Bat-Erdene
Undramaa Bat-Erdene
YTYi Tang
Yi Tang