Christian Laggner

TL;DR: The results show that the tested algorithms implemented within Catalyst are able to produce high quality conformers, which in most of the cases are well suited for in silico drug research.

TL;DR: This proof of principle study presents a model work for the application of parallel pharmacophore-based virtual screening on a set of 50 structure-based pharmacophores built for various viral targets and 100 antiviral compounds, and demonstrates that the desired enrichment was achieved for approximately 90% of all input molecules.

TL;DR: This study analyzes chemical features common to P450 19 inhibitors to develop ligand-based, selective pharmacophore models for this enzyme, and uses them as database search queries to identify active compounds from the NCI database.

TL;DR: The results prove that high enrichment rates are not necessarily in conflict with efficient vHTS settings: in most of the experiments, the highest yield of actives in the hit list when parameter sets for the fastest search algorithm were used.

TL;DR: An early application example employing a Pipeline Pilot-based screening platform for automatic large-scale virtual activity profiling using an extensive set of HIV protease inhibitor pharmacophore models to screen a selection of active and inactive compounds is presented.