metaTarFisher tries to fish the credible target of a compound. Target finding is one of the most important challenges in drug discovery. Some good methods and tools have been established to obtain the possible targets of a compound. However, usually only part of the information can be captured. Here, we develop metaTarFisher that tries to grasp comprehensive information of the target by integrating state-of-art target searching tools. We hope metaTarFisher can be used as a meta target searching tool.Read more
How to Use
It is very simple to use metaTarFisher, users only need to input a SMILES of the compound.(Example: search for Ibuprofen, just input CC(C)CC1=CC=C(C=C1)C(C)C(O)=O) then click the button to submit the task. After the states of all the tasks become 'SUCCESS', click the submit button of step 2, then you will get the final results and diagrams.Read more
News & Updates
New version v1.0.2 just lunched!2019.07.24
Models from ChEMBL just temporarily offline. Waiting for fixing the issue.2019.06.24
Added the TargetHunter resources.2019.06.20
Added the PPB2 resources.2019.06.15
Find the Web server ChemMapper needs to be upgraded. Overdue2019.06.12
New version v1.0.1 just lunched!2019.06.01
Nucleic Acids Research
metaTarFisher: a powerful web-based platform for credible target searching based on integrated tools and methods.
December 5, 2019 / Submitted
- Yao Z J, Dong J, Che Y J, et al. TargetNet: a web service for predicting potential drug–target interaction profiling via multi-target SAR models[J]. Journal of Computer-Aided Molecular Design, 2016, 30(5): 413-424
- Cao D S, Liang Y Z, Deng Z, et al. Genome-scale screening of drug-target associations relevant to Ki using a chemogenomics approach[J]. PloS one, 2013, 8(4): e57680.
- Cao D S, Zhang L X, Tan G S, et al. Computational Prediction of Drug-Target Interactions Using Chemical, Biological, and Network Features[J]. Molecular informatics, 2014, 33(10): 669-681.
- Cao D S, Zhou G H, Liu S, et al. Large-scale prediction of human kinase–inhibitor interactions using protein sequences and molecular topological structures[J]. Analytica chimica acta, 2013, 792: 10-18.
- Deng Y H, Wang N N, Zou Z X, et al. Multi-target screening and experimental validation of natural products from selaginella plants against Alzheimer's disease[J]. Frontiers in Pharmacology, 2017, 8: 539.
- Cao D S, Liu S, Xu Q S, et al. Large-scale prediction of drug–target interactions using protein sequences and drug topological structures[J]. Analytica chimica acta, 2012, 752: 1-10.