OTTER : Omics and Text based Target Enrichment and Ranking

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About OTTER :

It is a common strategy for existing computational target discovery tools, to compare the chemical structure of active compounds with previously reported inhibitors for known target proteins. However, this strategy is not applicable for the identification of target proteins with few or none inhibitors reported. To facilitate the target discovery not applicable to chemical structure comparison, we have developed a new computational tool named OTTER (Omics and Text based Target Enrichment and Ranking). Starting from a list of differentially expressed genes identified by omics data, this tool is able to enrich the most relevant genes for specific pharmacological feature, via exhaustive text mining in all the PubMed abstracts available. In addition to the list of differentially expressed genes, users need to provide a "keyword", which represents the pharmacological feature observed in cells treated with active compounds. The "keyword" can be any word or phrase that might be mentioned in the abstracts of target proteins. For example, the "keyword" can be apoptosis, reactive oxygen species, glioma, breast, etc.

Cite OTTER :

Heng Xu, Hongfang Zhao, Chunyong Ding, Defang Jiang, Zijie Zhao, Yang Li, Xiaoyu Ding, Jing Gao, Hu Zhou, Cheng Luo, Guoqiang Chen, Ao Zhang*, Ying Xu*, and Hao Zhang*.

Celastrol suppresses colorectal cancer via covalent targeting peroxiredoxin 1.

Signal Transduction and Targeted Therapy 2023 Feb 3; 8(1):51.

DOI : 10.1038/s41392-022-01231-4

Contact Dr. Hao Zhang by WeChat :

Correspondence : Dr. Hao Zhang, Chemical Biology Research Center

Shanghai Institute of Materia Medica, Chinese Academy of Sciences