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Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, ChinaBiomedical Sciences Institute of Qingdao University (Qingdao Branch of SJTU Bio-X Institutes), Qingdao University, Qingdao 266003, ChinaShanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, ChinaShanghai Key Laboratory of Sleep Disordered Breathing, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, ChinaThe First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, ChinaDepartment of Psychiatry, First Teaching Hospital of Xinjiang Medical University, Urumqi 830046, China
which highlighted that the monkeypox virus had become another global emergency threatening human health under the COVID-19 pandemic. An outbreak of the Monkeypox virus, which was first reported in the United Kingdom in May of 2022 and has since spread to more than 72 territories causing up to 14,533 cases according to the World Health Organization (WHO), as of the 20th of July 2022 (www.who.int/). In response to rising concerns over monkeypox, researchers are focused on acquiring structures of essential monkeypox proteins and have succeeded in producing crystal structures of the A42R Profilin-like protein (PDB: 4QWO), as well as simulating the structure of envelope protein F13, also known as C19L.
The structures of most of the monkeypox virus proteins remain unknown, knowledge of which would significantly enhance our understanding of the molecular mechanisms underlying critical viral processes such as viral entry and replication. AlphaFold2 is a powerful open-source computational approach developed to help predict protein structures,
), yielding a total of 186 highly accurate protein structures (Supplemental Table S1). The mean predicted Local Distance Difference Test (pLDDT) values of 156 of the 186 proteins are above the threshold of 70, which suggests that the predicted structures for these proteins are highly accurate (Fig. 1A). Furthermore, among these proteins, 77 protein structures had mean pLDDT values of between 80 and 90, while 57 protein structures showed mean pLDDT values above 90. To further evaluate the predicted protein structures, we compared the AlphaFold-predicted structure with the experimental crystal structure (PDB: 4QWO) of A42R Profilin-like protein. The resulting Template Modelling (TM), Global Distance Test (GDT)-TS, and the maximal subset (MaxSub) scores between two protein structures are above 0.95 (Fig. 1B). The aligned structure between two proteins has a root means square deviation (RMSD) value of 0.39 (Figs. 1B and 1C), suggesting that the two protein structures are highly similar (Figs. 1B and 1C). Taken together the above suggests that the predicted structures can be considered to be highly accurate.
Previously approved drugs for smallpox, tecovirimat and brincidofovir have been shown to be effective against the monkeypox virus, both in vitro and in animals
; however, given the global emergency, it is necessary to identify alternative drugs that could be used to fight the outbreak. Thus, we endeavored to uncover potential drugs to treat monkeypox based on accurate prediction of the monkeypox protein structures and 5903 approved drugs from the Zinc database
(Supplemental Table S2). We first selected ten target proteins based on their high pLDDT values, essential functions, and potential pharmacophores. The selected proteins were B4R, A42R, PRO132, VITF3L, E8L, I1L, D10L, P28, and G9R. We subsequently calculated the binding energies of all ten proteins with the 5903 drugs (Supplemental Table S3). The top best docking drugs targeting the ten proteins showed low binding energies (Table 1, S3, and FigureS1-S10), suggesting they might have strong interactions.
Table 1Virtual screening of potential drugs targeting the ten proteins. Related to Table S3.
Trypan Blue and Cepharanthine display significant binding affinities to all ten target proteins (Supplemental Table S3). Trypan Blue interacts with the proteins by forming hydrogen bonds, salt bridges and hydrophobic and pi-cation interactions (supplemental materials). Cepharanthine shows high binding affinities to I1L (Fig. 1D1), VITF3L (Fig. 1 D2), A42R (Fig. 1 D3), and E8L (Fig. 1D4) through hydrophobic interactions and hydrogen bond formation. We have generated an extensive drug dataset consisting of 43,800 protein-drug paired data for the monkeypox virus, which could contribute to discovering the potential drugs for fighting monkeypox. Combatting the outbreak would require rapid research in the following: 1. Development of suitable pseudovirus and animal models of the current subtype of monkeypox virus; 2. Clarification of the mechanism of infection, reproduction, and transmission of monkeypox virus; 3. Identify and validate potential drugs that can be used to treat the viral infection.
In conclusion, here we acquired 186 highly accurate protein structures of the monkeypox virus reference proteome using AlphaFold2, which provided the most comprehensive database of monkeypox virus protein structures worldwide. Moreover, we have screened the potential drugs for binding the ten crucial proteins of the monkeypox virus, including B4R, A42R, PRO132, VITF3L, E8L, I1L, D10L, P28, and G9R, and generated a drug dataset containing total 43,800 protein-drug paired data, which could be helpful for drug discovery to the monkeypox virus.
Q.Y. and S.Y. conceived and designed the study. Q.Y. and X.S. analyzed and interpreted the data. Q.Y., A.A.S.S, and S.Y. wrote the first draft. Z.W. provided the softwares.
The detailed methods are described in supplemental Methods. The protein structural files predicted by AlphaFold2 and the interaction analysis results between drugs and proteins were available on Github (https://github.com/lg10is1/monkeypox-virus-protein-structures). The RStudio code used in this study to perform statistical analysis and visualize data are available upon request.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
This work was supported by Shanghai Municipal Science and Technology Major Project (2017SHZDZX01), Natural Science Foundation of China (32070679, U1804284, 81871055), the National Key R&D Program of China (2019YFA0905400, 2017YFC0908105, 2021YFC2702103), Taishan Scholar Program of Shandong Province (tsqn201812153) and Natural Science Foundation of Shandong Province (ZR2019YQ14). The computations in this paper were run on the Siyuan cluster supported by the Center for High-Performance Computing at Shanghai Jiao Tong University.