ArticleJournal of cheminformatics2021
LigTMap: ligand and structure-based target identification and activity prediction for small molecular compounds.
Article in Journal of cheminformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Review
- Synthesis, characterization, and anticancer potency of sulfadiazine salicylaldehyde-based Schiff bases.Scientific reports · 2026Article
- Discovery of Two GSK3β Inhibitors fromCurrent computer-aided drug design · 2026Article
- Network pharmacology and metabolomics reveal mathurameha, a Thai traditional Anti-Diabetic formula, enhances glucose metabolism through PI3K-AKT/AMPK/GLUT4 pathway modulation.Scientific reports · 2025Article
- DerivaPredict: A User-Friendly Tool for Predicting and Evaluating Active Derivatives of Natural Products.Molecules (Basel, Switzerland) · 2025Article
- Computational-aided drug design strategies for drug discovery and development against oral diseases.Frontiers in pharmacology · 2025Review
- Design and predict the potential of imidazole-based organic dyes in dye-sensitized solar cells using fingerprint machine learning and supported by a web application.Scientific reports · 2024Article
- CACTI: an in silico chemical analysis tool through the integration of chemogenomic data and clustering analysis.Journal of cheminformatics · 2024Article
- Exploring the potential of some natural indoles as antiviral agents: quantum chemical analysis, inverse molecular docking, and affinity calculations.Frontiers in chemistry · 2024Article
- Computational studies on searching potential phytochemicals against DNA polymerase activity of the monkeypox virus.Journal of traditional and complementary medicine · 2023Article
- TAIGET: A small-molecule target identification and annotation web server.Frontiers in pharmacology · 2022Article
- Heterogeneous network propagation with forward similarity integration to enhance drug-target association prediction.PeerJ. Computer science · 2022Article
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Authors and funding
4 authors.
Funding
Abstract
Target prediction is a crucial step in modern drug discovery. However, existing experimental approaches to target prediction are time-consuming and costly. Here, we introduce LigTMap, an online server with a fully automated workflow that can identify protein targets of chemical compounds among 17 classes of therapeutic proteins extracted from the PDBbind database. It combines ligand similarity search with docking and binding similarity analysis to predict putative targets. In the validation experiment of 1251 compounds, targets were successfully predicted for more than 70% of the compounds within the top-10 list. The performance of LigTMap is comparable to the current best servers SwissTargetPrediction and SEA. When testing with our newly compiled compounds from recent literature, we get improved top 10 success rate (66% ours vs. 60% SwissTargetPrediction and 64% SEA) and similar top 1 success rate (45% ours vs. 51% SwissTargetPrediction and 41% SEA). LigTMap directly provides ligand docking structures in PDB format, so that the results are ready for further structural studies in computer-aided drug design and drug repurposing projects. The LigTMap web server is freely accessible at https://cbbio.online/LigTMap . The source code is released on GitHub ( https://github.com/ShirleyWISiu/LigTMap ) under the BSD 3-Clause License to encourage re-use and further developments.
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