Duan Huaichuan, Shi Quanshan, Yue Xinru, Zhang Zelan, Liu Ling, Wang Yueteng, Cao Yujie, Ou Zuoxin, Liang Li, Hu Jianping, Shi Hubing
Laboratory of Tumor Targeted and Immune Therapy, Clinical Research Center for Breast, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University and Collaborative Innovation Center for Biotherapy, Chengdu, China.
Key Laboratory of Medicinal and Edible Plants Resources Development of Sichuan Education Department, School of Pharmacy, Chengdu University, Chengdu, China.
PLoS One. 2024 Dec 6;19(12):e0303501. doi: 10.1371/journal.pone.0303501. eCollection 2024.
A new round of monkeypox virus has emerged in the United Kingdom since July 2022 and rapidly swept the world. Currently, despite numerous research groups are studying this virus and seeking effective treatments, the information on the open reading frame, inhibitors, and potential targets of monkeypox has not been updated in time, and the comprehension of monkeypox target ligand interactions remains a key challenge. Here, we first summarized and improved the open reading frame information of monkeypox, constructed the monkeypox inhibitor library and potential targets library by database research as well as literature search, combined with advanced protein modeling technologies (Sequence-based and AI algorithms-based homology modeling). In addition, we build monkeypox virus Docking Server, a web server to predict the binding mode between targets and substrate. The open reading frame information, monkeypox inhibitor library, and monkeypox potential targets library are used as the initial files for server docking, providing free interactive tools for predicting ligand interactions of monkeypox targets, potential drug screening, and potential targets search. In addition, the update of the three databases can also effectively promote the study of monkeypox drug inhibition mechanism and provide theoretical guidance for the development of drugs for monkeypox.
自2022年7月以来,新一轮猴痘病毒在英国出现并迅速席卷全球。目前,尽管众多研究团队正在研究这种病毒并寻求有效的治疗方法,但关于猴痘的开放阅读框、抑制剂和潜在靶点的信息尚未及时更新,对猴痘靶点配体相互作用的理解仍然是一个关键挑战。在此,我们首先总结并完善了猴痘的开放阅读框信息,通过数据库研究以及文献检索,并结合先进的蛋白质建模技术(基于序列和基于人工智能算法的同源建模),构建了猴痘抑制剂库和潜在靶点库。此外,我们搭建了猴痘病毒对接服务器,这是一个用于预测靶点与底物之间结合模式的网络服务器。开放阅读框信息、猴痘抑制剂库和猴痘潜在靶点库用作服务器对接的初始文件,为预测猴痘靶点的配体相互作用、潜在药物筛选和潜在靶点搜索提供免费的交互工具。此外,这三个数据库的更新还可以有效促进猴痘药物抑制机制的研究,为猴痘药物的研发提供理论指导。