New strategy for receptor-based pharmacophore query construction: a case study for 5-HT₇ receptor ligands.
In this paper, a new approach for generating receptor-based 3D pharmacophore models for rapid in silico virtual screening is presented. The method combines information from docking poses of known ligands of different structures and further ligand-receptor complexes analyses using structural interaction fingerprints (SIFts). Next, the best linear combination of three-, four-, and five-feature pharmacophores in terms of selected performance parameter (i.e., recall, F-score, and MCC) is constructed. The resultant queries showed significantly better VS performance and new scaffold recognition when compared with the known ligand- and receptor-based pharmacophore models. The approach was developed and validated on 5-HT₇ receptor homology models created on available crystal structure templates. The efficiency of the obtained linear combinations exhibited only a minor dependence on the template selection.
Department of Medicinal Chemistry, Institute of Pharmacology Polish Academy of Sciences , 12 Smętna Street, Kraków, 31-343, Poland.
Rafał
R
Kurczab
Andrzej J
AJ
Bojarski
D000595:Amino Acid Sequence; D020134:Catalytic Domain; D062126:Databases, Chemical; D030562:Databases, Protein; D055808:Drug Discovery; D057166:High-Throughput Screening Assays; D006801:Humans; D008024:Ligands; D062105:Molecular Docking Simulation; D008969:Molecular Sequence Data; D011485:Protein Binding; D011985:Receptors, Serotonin / Q000737:chemistry*; D016415:Sequence Alignment; D017366:Serotonin Receptor Agonists / Q000737:chemistry*; D054852:Small Molecule Libraries / Q000737:chemistry*; D040681:Structural Homology, Protein; D013329:Structure-Activity Relationship; D014584:User-Computer Interface
D008024:Ligands; D011985:Receptors, Serotonin; D017366:Serotonin Receptor Agonists; D054852:Small Molecule Libraries; C104425:serotonin 7 receptor