Wang Fan, Wu Feng-Xu, Li Cheng-Zhang, Jia Chen-Yang, Su Sun-Wen, Hao Ge-Fei, Yang Guang-Fu
Key Laboratory of Pesticide & Chemical Biology, Ministry of Education, College of Chemistry, Central China Normal University, Wuhan, 430079, People's Republic of China.
International Joint Research Center for Intelligent Biosensor Technology and Health, Central China Normal University, Wuhan, 430079, China.
J Cheminform. 2019 Nov 27;11(1):73. doi: 10.1186/s13321-019-0394-z.
Drug repurposing offers a promising alternative to dramatically shorten the process of traditional de novo development of a drug. These efforts leverage the fact that a single molecule can act on multiple targets and could be beneficial to indications where the additional targets are relevant. Hence, extensive research efforts have been directed toward developing drug based computational approaches. However, many drug based approaches are known to incur low successful rates, due to incomplete modeling of drug-target interactions. There are also many technical limitations to transform theoretical computational models into practical use. Drug based approaches may, thus, still face challenges for drug repurposing task. Upon this challenge, we developed a consensus inverse docking (CID) workflow, which has a ~ 10% enhancement in success rate compared with current best method. Besides, an easily accessible web server named auto in silico consensus inverse docking (ACID) was designed based on this workflow (http://chemyang.ccnu.edu.cn/ccb/server/ACID).
药物重新利用提供了一种很有前景的替代方法，可以显著缩短药物传统从头研发的过程。这些努力利用了单个分子可以作用于多个靶点这一事实，并且可能对额外靶点相关的适应症有益。因此，大量的研究工作都致力于开发基于药物的计算方法。然而，由于药物-靶点相互作用的建模不完整，许多基于药物的方法成功率较低。将理论计算模型转化为实际应用也存在许多技术限制。因此，基于药物的方法在药物重新利用任务中可能仍然面临挑战。面对这一挑战，我们开发了一种共识反向对接（CID）工作流程，与当前最佳方法相比，成功率提高了约10%。此外，基于此工作流程设计了一个名为自动计算机模拟共识反向对接（ACID）的易于访问的网络服务器（http://chemyang.ccnu.edu.cn/ccb/server/ACID）。
