Pharmacophore modeling and parallel screening for PPAR ligands.
We describe the generation and validation of pharmacophore models for PPARs, as well as a large scale validation of the parallel screening approach by screening PPAR ligands against a large database of structure-based models. A large test set of 357 PPAR ligands was screened against 48 PPAR models to determine the best models for agonists of PPAR-alpha, PPAR-delta, and PPAR-gamma. Afterwards, a parallel screen was performed using the 357 PPAR ligands and 47 structure-based models for PPARs, which were integrated into a 1537 models comprising in-house pharmacophore database, to assess the enrichment of PPAR ligands within the PPAR hypotheses. For these purposes, we categorized the 1537 database models into 181 protein targets and developed a score that ranks the retrieved targets for each ligand. Thus, we tried to find out if the concept of parallel screening is able to predict the correct pharmacological target for a set of compounds. The PPAR target was ranked first more often than any other target. This confirms the ability of parallel screening to forecast the pharmacological active target for a set of compounds.
Markt
Patrick
P
Department of Pharmaceutical Chemistry, Institute of Pharmacy and Center for Molecular Biosciences Innsbruck, University of Innsbruck, Innrain 52c, 6020 Innsbruck, Austria.
Schuster
Daniela
D
Kirchmair
Johannes
J
Laggner
Christian
C
Langer
Thierry
T
D001665:Binding Sites; D003198:Computer Simulation; D016208:Databases, Factual; D015195:Drug Design; D004353:Drug Evaluation, Preclinical; D008024:Ligands; D008958:Models, Molecular; D047492:Peroxisome Proliferator-Activated Receptors / Q000819:agonists* / Q000737:chemistry*
D008024:Ligands; D047492:Peroxisome Proliferator-Activated Receptors