ArticleThe AAPS journal2013
TargetHunter: an in silico target identification tool for predicting therapeutic potential of small organic molecules based on chemogenomic database.
Article in The AAPS journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.
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Who cites it
99 citing papers in PubMed.
- Review
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- Bioengineering approaches to trained immunity: Physiologic targets and therapeutic strategies.eLife · 2025Review
- Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches.Cancer biology & medicine · 2025Review
- GraphDeep-hERG: Graph Neural Network PharmacoAnalytics for Assessing hERG-Related Cardiotoxicity.Pharmaceutical research · 2025Article
- Fifteen years of ChEMBL and its role in cheminformatics and drug discovery.Journal of cheminformatics · 2025Review
- Virtual screening: hope, hype, and the fine line in between.Expert opinion on drug discovery · 2025Review
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- Network pharmacology-integrated molecular modeling analysis ofIn silico pharmacology · 2025Article
- Enhancing the confidence of potential targets enriched by similarity-centric models: the crucial role of the similarity threshold.Frontiers in pharmacology · 2025Article
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- CACTI: an in silico chemical analysis tool through the integration of chemogenomic data and clustering analysis.Journal of cheminformatics · 2024Article
- Using Generative Modeling to Endow with Potency Initially Inert Compounds with Good Bioavailability and Low Toxicity.Journal of chemical information and modeling · 2024Article
- Predicting drug-target interactions using matrix factorization with self-paced learning and dual similarity information.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
- Frentizole, a Nontoxic Immunosuppressive Drug, and Its Analogs Display Antitumor Activity via Tubulin Inhibition.International journal of molecular sciences · 2023Article
- In Silico Screening of Natural Flavonoids against 3-Chymotrypsin-like Protease of SARS-CoV-2 Using Machine Learning and Molecular Modeling.Molecules (Basel, Switzerland) · 2023Article
- Analgesic Activity of 5-Acetamido-2-Hydroxy Benzoic Acid Derivatives and an In-Vivo and In-Silico Analysis of Their Target Interactions.Pharmaceuticals (Basel, Switzerland) · 2023Article
- ProfhEX: AI-based platform for small molecules liability profiling.Journal of cheminformatics · 2023Article
39 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
Abstract
Target identification of the known bioactive compounds and novel synthetic analogs is a very important research field in medicinal chemistry, biochemistry, and pharmacology. It is also a challenging and costly step towards chemical biology and phenotypic screening. In silico identification of potential biological targets for chemical compounds offers an alternative avenue for the exploration of ligand-target interactions and biochemical mechanisms, as well as for investigation of drug repurposing. Computational target fishing mines biologically annotated chemical databases and then maps compound structures into chemogenomical space in order to predict the biological targets. We summarize the recent advances and applications in computational target fishing, such as chemical similarity searching, data mining/machine learning, panel docking, and the bioactivity spectral analysis for target identification. We then described in detail a new web-based target prediction tool, TargetHunter (http://www.cbligand.org/TargetHunter). This web portal implements a novel in silico target prediction algorithm, the Targets Associated with its MOst SImilar Counterparts, by exploring the largest chemogenomical databases, ChEMBL. Prediction accuracy reached 91.1% from the top 3 guesses on a subset of high-potency compounds from the ChEMBL database, which outperformed a published algorithm, multiple-category models. TargetHunter also features an embedded geography tool, BioassayGeoMap, developed to allow the user easily to search for potential collaborators that can experimentally validate the predicted biological target(s) or off target(s). TargetHunter therefore provides a promising alternative to bridge the knowledge gap between biology and chemistry, and significantly boost the productivity of chemogenomics researchers for in silico drug design and discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.