Computational Models for Prediction of Ligand-Transporter Interaction
Manually curated data for high quality training sets
Cutting edge machine learning algorithms accounting for imbalanced training sets
Traffic light system for results including visualisation of applicability domain assessment
Transmembrane Transport Proteins (TMTs) control nutrient uptake, ion transport, and drug transport across biological membranes. Predicting substrate and inhibition profiles of small molecules towards these transporters helps medicinal chemists to prioritize compounds in an early phase of the drug development process and guide toxicologists in the safety assessment of candidate compounds. Based on our long-lasting experience in the field of transporter informatics we offer a set of high quality computational models for predicting inhibitor profiles of small molecules towards a set of TMTs.
The Phenaris Transporter Models can predict ligand-transporter interaction in 3 easy steps: log-in, upload SDF files, run prediction.
Our model portfolio is constantly updated and expanded. Currently we are offering models for 9 transporter which are involved in drug/drug interactions and hepatoxicity. These include prediction of inhibitors of P-glycoprotein, BCRP, BSEP, MRP3, OATP1B1, OATP1B3, OCT1, OCT2, and MATE1. More transporter to come soon!
To give you a closer insight into the functionalities and design of our Transporter Models we also produced a short demo video. See how you can easily draw and analyse your compounds and get results in a standardised and aggregated form with state of the art data visualisation in just a few minutes:
Webinar Recording: Phenaris Transporter Models V2.0 Release
For a free web-service of our models, please visit livertox.univie.ac.at.