TAIGET: A small-molecule target identification and annotation web server - Wei, Xuxu; Yang, Jiarui; Li, Simin; Li, Boyuan; Chen, Mengzhen; Lu, Yukang; Wu, Xiang; Cheng, Zeyu; Zhang, Xiaoyu; Chen, Zhao; Wang, Chunxia; Wang, Edwin; et al. (Frontiers in Pharmacology, 2022)
Background: Accurate target identification of small molecules and downstream target annotation are important in pharmaceutical research and drug development. Methods: We present TAIGET, a friendly and easy to operate graphical web interface, which consists of a docking module based on Autodock vina and LeDock, a target screen module based on a Bayesian Gaussian Mixture Model (BGMM), and a target annotation module derived from >14,000 cancer-related literatures. Results: TAIGET produces binding poses by selecting ≤5 proteins at a time from the UniProt ID-PDB network, and submitting ≤ 3 ligands at a time with the SMILES format. Once the identification process of binding poses is complete, TAIGET then screens potential targets based on the BGMM. In addition, three medical experts and ten medical students curated associations among drugs, genes, gene regulation, cancer outcome phenotype, 2170 cancer-cell types, 73 cancer types from the PubMed literatures, with the aim to construct a target annotation module. Target-related PPI network can be visualized by an interactive interface. Conclusions: This online tool significantly lowers the entry barrier of virtual identification of targets for users who are not experts in the technical aspects of virtual drug discovery. The webserver is freely available at http://www.taiget.cn/.