title: Probing Small-Molecule Binding to the Liver-X Receptor: A Mixed-Model QSAR Study.
abstract: The LXR model has been added in the VirtualToxLab, a fully automated technology that allows for the identification of the endocrine-disrupting potential of drugs, chemicals and natural products. This protocol has then been applied to screen a series of 161 natural compounds probing their binding to the LXR. The results of the simulation were compared with experimental data (where available) and suggest that the LXR model can be applied to predict the binding affinity of existing or hypothetical compounds for screening purposes. The binding of 52 ligands towards the liver X receptors (LXRs) was identified trough docking to the three-dimensional protein structure and quantified by multidimensional QSAR (mQSAR), an approach referred to as 'mixed-model QSAR'. The model was validated by the prediction of 17 external compounds (oxysterols) present neither in the training nor in the test set. The robustness of the model was verified by consensus scoring using a conceptually different methodology, and chance correlation was ruled out by a series of scramble tests.
authors.affiliation: Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel (Switzerland).
authors.forename: Morena
authors.initials: M
authors.lastname: Spreafico
authors.affiliation: Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel (Switzerland).
authors.forename: Martin
authors.initials: M
authors.lastname: Smiesko
authors.affiliation: Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel (Switzerland).
authors.forename: Ourania
authors.initials: O
authors.lastname: Peristera
authors.affiliation: Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel (Switzerland).
authors.forename: Gianluca
authors.initials: G
authors.lastname: Rossato
authors.affiliation: Department of Pharmaceutical Sciences, University of Basel, Klingelbergstrasse 50, 4056 Basel (Switzerland). angelo.vedani@unibas.ch.
authors.forename: Angelo
authors.initials: A
authors.lastname: Vedani
keywords: Bioinformatics; Consensus scoring; Drug design; Flexible docking; Liver X receptor; Multidimensional QSAR