pharmdb-logo.png IL PharmDB

3D Pharmacophore Collection

IL PharmDB

3D Pharmacophore Collection

Target Activity and Selectivity Profiling, Toxicity and Metabolism Flagging

Inte:Ligand’s Pharmacophore Database (IL PharmDB) is a premium, meticulously curated collection of 3D-chemical feature-based pharmacophores built on years of expert modeling experience. Manually assembled and rigorously quality-checked, this powerful database serves as an essential engine for parallel virtual screening, compound activity profiling, and drug repurposing. It is uniquely optimized to translate phenotypic screening results into actionable target hypotheses through reverse screening. The IL PharmDB provides researchers with a robust toolkit for translating complex structural data into clear, actionable hypotheses, driving faster and more confident decision-making in compound prioritization and pipeline de-risking.

License the IL PharmDB

Structural Intelligence Repository

Target Prediction and Drug Repurposing

The IL PharmDB provides a premium, manually curated collection of over 9,000 models across 300 clinical targets, uniquely optimized for target searching, selectivity profiling, toxicity prediction and decoding phenotypic screening results.

The tool allows to rapidly and transparently derive ligand profiles from compound structures in a fully automated and convenient way to support key decisions for compound series selection and lead optimization.

pharmacophoredb-heatmap.png

Inte:Ligand’s Pharmacophore Database is a high-quality collection of chemical feature-based 3D pharmacophores. It is based on many years of experience in pharmacophore creation and has been assembled manually and quality checked carefully. The IL PharmDB contains models derived from protein-ligand 3D complex structures as well as from structure data about small bio-active organic molecules and drugs that originate from studies involving major therapeutical classes, such as antiinfectives, cardiovascular, endocrine, gastrointestinal, immunologic, metabolic, neurologic, oncolytic, renal-urologic, and respiratory agents.

The IL Kinase and IL GPCR collections can be licensed separately to drive the critical, risk-mitigating decisions that shape tomorrow's medical breakthroughs.

Customized sub-selections of the IL PharmDB can be assembled into the profiling platform to fit your target product profile needs.

IL PharmDB Toxicity and Metabolism

We offer the IL eToxPlus, and IL CYP450 collections for routine toxicity and metabolism flagging. Both collections were rigorously tested on in house pharmaceutical industry data by eTox Industry consortium partners. Since then the models have been upgraded.

IL eToxPlus

Originally developed within the EU eTOX Consortium framework, and continuously refined over the years, the IL eToxPlus collection represents a highly evolved suite of predictive toxicology models. This optimized portfolio delivers in silico chemical structure safety profiling across critical endpoints—including hERG channel inhibition, drug-induced liver injury (DILI), carcinogenicity, mutagenicity, and phototoxicity—allowing researchers to flag toxicological liabilities with confidence.

Request a License.

IL CYP450 Collection

Streamline your ADME profiling with the IL CYP450 models collection. Engineered to map essential metabolic endpoints, this predictive toolkit identifies potential metabolic liabilities and isoform-specific interactions at the earliest stages of design, ensuring your leads possess the metabolic stability required for clinical success.

Request a License.

IL PharmDB Profiling Subsets

IL Kinase Collection

Built upon meticulously curated 3D-structural data, the IL Kinase collection consists of several thousand models that enables researchers to map cross-reactivity and engineer out off-target liabilities early in design. Clear visualization of the the target ligand profiles with heat maps reflecting scoring to support decisions.

Request a License.

IL GPCR Collection

The IL GPCR collection captures the complex conformational states and pharmacological outcomes necessary to target these membrane proteins effectively, providing the predictive intelligence required to identify novel, highly specific leads for complex signaling pathways.

Request a License.

IL Customized Selection

Beyond our standard packaged collections, we can curate tailored subsets from our extensive collection of 9,000 IL PharmDB models to match the exact target and structural requirements of your specific project to help support your target product profile needs.

Contact us for the next steps!

IL PharmDB Research Services

Let our team of expert scientists accelerate your discovery program by conducting tailored profiling studies using IL PharmDB, delivering high-impact insights across target prediction, selectivity profiling, drug repurposing, and early toxicological flagging.

Find out more about our Services.

Contact us for the next steps!

References

  • Mayr F, Möller G, Garscha U, Fischer J, Rodríguez Castaño P, Inderbinen SG, Temml V, Waltenberger B, Schwaiger S, Hartmann RW, Gege C, Martens S, Odermatt A, Pandey AV, Werz O, Adamski J, Stuppner H, Schuster D. Finding New Molecular Targets of Familiar Natural Products Using In Silico Target Prediction. Int J Mol Sci. 2020 Sep 26;21(19):7102. doi: 10.3390/ijms21197102.
  • Data Mining Using Ligand Profiling and Target Fishing. Bryant, S.D. and Langer, T. (2013). In Data Mining in Drug Discovery pp. 257-270. (eds. R.D. Hoffmann, A. Gohier and P. Pospisil). https://doi.org/10.1002/9783527655984.ch11
  • Parallel Screening: A Novel Concept in Pharmacophore Modelling and Virtual Screening T. M. Steindl, D. Schuster, C. Laggner, T. Langer J. Chem. Inf. Model., 46, 2146-2157 (2006)
    DOI 10.1021/ci6002043
  • High Throughput Structure-based Pharmacophore Modeling as A Basis for Successful Parallel Virtual Screening T. M. Steindl, D. Schuster, G. Wolber, C. Laggner, T. Langer J. Comput. Aided Mol. Des., 20, 703-715 (2006)
    DOI 10.1007/s10822-006-9066-y
  • Pharmacophore Modeling and Parallel Screening for PPAR Ligands P. Markt, D. Schuster, J. Kirchmair, C. Laggner, T. Langer J. Comput. Aided Mol. Des. 21, 575-590 (2007. DOI 10.1007/s10822-007-9140-0
  • Innovative Health Initiative. eTox. https://www.ihi.europa.eu/projects-results/project-factsheets/etox