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Yechun Xu

Chinese Academy of Sciences

ORCID: 0000-0002-1581-6155

Publishes on Computational Drug Discovery Methods, SARS-CoV-2 and COVID-19 Research, Cholinesterase and Neurodegenerative Diseases. 182 papers and 11.2k citations.

182Publications
11.2kTotal Citations

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Top publicationsby citations

Structure of Mpro from COVID-19 virus and discovery of its inhibitors
Zhenming Jin, Xiaoyu Du, Yechun Xu et al.|Queensland's institutional digital repository (The University of Queensland)|2020
Cited by 264

A new coronavirus (CoV) identified as COVID-19 virus is the etiological agent responsible for the 2019-2020 viral pneumonia outbreak that commenced in Wuhan. Currently there are no targeted therapeutics and effective treatment options remain very limited. In order to rapidly discover lead compounds for clinical use, we initiated a program of combined structure-assisted drug design, virtual drug screening and high-throughput screening to identify new drug leads that target the COVID-19 virus main protease (M). M is a key CoV enzyme, which plays a pivotal role in mediating viral replication and transcription, making it an attractive drug target for this virus. Here, we identified a mechanism-based inhibitor, N3, by computer-aided drug design and subsequently determined the crystal structure of COVID-19 virus M in complex with this compound. Next, through a combination of structure-based virtual and high-throughput screening, we assayed over 10,000 compounds including approved drugs, drug candidates in clinical trials, and other pharmacologically active compounds as inhibitors of M. Six of these compounds inhibited M with IC values ranging from 0.67 to 21.4 μM. Ebselen also exhibited promising antiviral activity in cell-based assays. Our results demonstrate the efficacy of this screening strategy, which can lead to the rapid discovery of drug leads with clinical potential in response to new infectious diseases for which no specific drugs or vaccines are available.

Conformational transition of amyloid β-peptide
Yechun Xu, Jianhua Shen, Xiaomin Luo et al.|Proceedings of the National Academy of Sciences|2005
Cited by 245

The amyloid beta-peptides (Abetas), containing 39-43 residues, are the key protein components of amyloid deposits in Alzheimer's disease. To structurally characterize the dynamic behavior of Abeta(40), 12 independent long-time molecular dynamics (MD) simulations for a total of 850 ns were performed on both the wide-type peptide and its mutant in both aqueous solution and a biomembrane environment. In aqueous solution, an alpha-helix to beta-sheet conformational transition for Abeta(40) was observed, and an entire unfolding process from helix to coil was traced by MD simulation. Structures with beta-sheet components were observed as intermediates in the unfolding pathway of Abeta(40). Four glycines (G(25), G(29), G(33), and G(37)) are important for Abeta(40) to form beta-sheet in aqueous solution; mutations of these glycines to alanines almost abolished the beta-sheet formation and increased the content of the helix component. In the dipalmitoyl phosphatidylcholine (DPPC) bilayer, the major secondary structure of Abeta(40) is a helix; however, the peptide tends to exit the membrane environment and lie down on the surface of the bilayer. The dynamic feature revealed by our MD simulations rationalized several experimental observations for Abeta(40) aggregation and amyloid fibril formation. The results of MD simulations are beneficial to understanding the mechanism of amyloid formation and designing the compounds for inhibiting the aggregation of Abeta and amyloid fibril formation.