title: mRAISE: an alternative algorithmic approach to ligand-based virtual screening.
abstract: Ligand-based virtual screening is a well established method to find new lead molecules in todays drug discovery process. In order to be applicable in day to day practice, such methods have to face multiple challenges. The most important part is the reliability of the results, which can be shown and compared in retrospective studies. Furthermore, in the case of 3D methods, they need to provide biologically relevant molecular alignments of the ligands, that can be further investigated by a medicinal chemist. Last but not least, they have to be able to screen large databases in reasonable time. Many algorithms for ligand-based virtual screening have been proposed in the past, most of them based on pairwise comparisons. Here, a new method is introduced called mRAISE. Based on structural alignments, it uses a descriptor-based bitmap search engine (RAISE) to achieve efficiency. Alignments created on the fly by the search engine get evaluated with an independent shape-based scoring function also used for ranking of compounds. The correct ranking as well as the alignment quality of the method are evaluated and compared to other state of the art methods. On the commonly used Directory of Useful Decoys dataset mRAISE achieves an average area under the ROC curve of 0.76, an average enrichment factor at 1 % of 20.2 and an average hit rate at 1 % of 55.5. With these results, mRAISE is always among the top performing methods with available data for comparison. To access the quality of the alignments calculated by ligand-based virtual screening methods, we introduce a new dataset containing 180 prealigned ligands for 11 diverse targets. Within the top ten ranked conformations, the alignment closest to X-ray structure calculated with mRAISE has a root-mean-square deviation of less than 2.0 Å for 80.8 % of alignment pairs and achieves a median of less than 2.0 Å for eight of the 11 cases. The dataset used to rate the quality of the calculated alignments is freely available at http://www.zbh.uni-hamburg.de/mraise-dataset.html . The table of all PDB codes contained in the ensembles can be found in the supplementary material. The software tool mRAISE is freely available for evaluation purposes and academic use (see http://www.zbh.uni-hamburg.de/raise ).
authors: ZBH - Center for Bioinformatics, University of Hamburg, Bundesstraße 43, 20146, Hamburg, Germany.
authors: Mathias M
authors: MM
authors: von Behren
authors: ZBH - Center for Bioinformatics, University of Hamburg, Bundesstraße 43, 20146, Hamburg, Germany.
authors: Stefan
authors: S
authors: Bietz
authors: ZBH - Center for Bioinformatics, University of Hamburg, Bundesstraße 43, 20146, Hamburg, Germany.
authors: Eva
authors: E
authors: Nittinger
authors: ZBH - Center for Bioinformatics, University of Hamburg, Bundesstraße 43, 20146, Hamburg, Germany. rarey@zbh.uni-hamburg.de.
authors: Matthias
authors: M
authors: Rarey
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D062126:Databases, Chemical; D030562:Databases, Protein; D055808:Drug Discovery / Q000379:methods; D006801:Humans; D008024:Ligands; D008958:Models, Molecular; D011506:Proteins / Q000378:metabolism; D012984:Software
chemical_list: D008024:Ligands; D011506:Proteins
keywords: 3D similarity searching; Lead discovery; Ligand-based; Molecular similarity; Structural alignment; Virtual screening