title: LASSO-ligand activity by surface similarity order: a new tool for ligand based virtual screening.
abstract: Virtual Ligand Screening (VLS) has become an integral part of the drug discovery process for many pharmaceutical companies. Ligand similarity searches provide a very powerful method of screening large databases of ligands to identify possible hits. If these hits belong to new chemotypes the method is deemed even more successful. eHiTS LASSO uses a new interacting surface point types (ISPT) molecular descriptor that is generated from the 3D structure of the ligand, but unlike most 3D descriptors it is conformation independent. Combined with a neural network machine learning technique, LASSO screens molecular databases at an ultra fast speed of 1 million structures in under 1 min on a standard PC. The results obtained from eHiTS LASSO trained on relatively small training sets of just 2, 4 or 8 actives are presented using the diverse directory of useful decoys (DUD) dataset. It is shown that over a wide range of receptor families, eHiTS LASSO is consistently able to enrich screened databases and provides scaffold hopping ability.
authors.affiliation: SimBioSys Inc., 135 Queen's Plate Drive, Suite 520, Toronto, ON, Canada, M9W 6V1.
authors.forename: Darryl
authors.initials: D
authors.lastname: Reid
authors.forename: Bashir S
authors.initials: BS
authors.lastname: Sadjad
authors.forename: Zsolt
authors.initials: Z
authors.lastname: Zsoldos
authors.forename: Aniko
authors.initials: A
authors.lastname: Simon
mesh_terms: D015195:Drug Design; D008024:Ligands; D015394:Molecular Structure; D013499:Surface Properties
chemical_list: D008024:Ligands