title: Combining pharmacophore fingerprints and PLS-discriminant analysis for virtual screening and SAR elucidation.
abstract: The criterion of success for the initial stages of a ligand-based drug-discovery project is dual. First, a set of suitable lead compounds has to be identified. Second, a level of a preliminary structure-activity relationship (SAR) of the identified ligands has to be established in order to guide the lead optimization toward a final drug candidate. This paper presents a combined approach to solving these two problems of ligand-based virtual screening and elucidation of SAR based on interplay between pharmacophore fingerprints and interpretation of PLS-discriminant analysis (PLS-DA) models. The virtual screening capability of the PLS-DA method is compared to group fusion maximum similarity searching in a test using four graph-based pharmacophore fingerprints over a range of 10 diverse targets. The PLS-DA method was generally found to do better than the Smax method. The GpiDAPH3 and PCH fingerprints proved superior to the TGT and TGD fingerprints. Examples of SAR elucidation based on PLS-DA model interpretation of model coefficients using a reversible pharmacophore fingerprint are given. In addition, we tested the hypothesis that feature combinations coming from the analysis of two-dimensional (2D) pharmacophore fingerprints could be used to elucidate a three-dimensional pharmacophore (Williams, C. Mol. Diversity 2006, 10 (3), 311-332). This test was performed by mapping of pharmacophore triplets found by the PLS-DA model to be important for activity onto relevant ligands aligned by the protein-binding site known from X-ray complexes. The result of this analysis assists in explaining the efficiency of 2D pharmacophore fingerprints as descriptors in virtual screening.
authors.affiliation: Department of Medicinal Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, DK-2100 Copenhagen, Denmark. suap@lundbeck.com
authors.forename: Sune
authors.initials: S
authors.lastname: Askjaer
authors.forename: Morten
authors.initials: M
authors.lastname: Langgård
mesh_terms: D016002:Discriminant Analysis; D008958:Models, Molecular; D004364:Pharmaceutical Preparations; D013329:Structure-Activity Relationship
chemical_list: D004364:Pharmaceutical Preparations