title: Discovery of high affinity ligands for β2-adrenergic receptor through pharmacophore-based high-throughput virtual screening and docking.
abstract: Novel high affinity compounds for human β2-adrenergic receptor (β2-AR) were searched among the clean drug-like subset of ZINC database consisting of 9,928,465 molecules that satisfy the Lipinski's rule of five. The screening protocol consisted of a high-throughput pharmacophore screening followed by an extensive amount of docking and rescoring. The pharmacophore model was composed of key features shared by all five inactive states of β2-AR in complex with inverse agonists and antagonists. To test the discriminatory power of the pharmacophore model, a small-scale screening was initially performed on a database consisting of 117 compounds of which 53 antagonists were taken as active inhibitors and 64 agonists as inactive inhibitors. Accordingly, 7.3% of the ZINC database subset (729,413 compounds) satisfied the pharmacophore requirements, along with 44 antagonists and 17 agonists. Afterwards, all these hit compounds were docked to the inactive apo form of the receptor using various docking and scoring protocols. Following each docking experiment, the best pose was further evaluated based on the existence of key residues for antagonist binding in its vicinity. After final evaluations based on the human intestinal absorption (HIA) and the blood brain barrier (BBB) penetration properties, 62 hit compounds have been clustered based on their structural similarity and as a result four scaffolds were revealed. Two of these scaffolds were also observed in three high affinity compounds with experimentally known Ki values. Moreover, novel chemical compounds with distinct structures have been determined as potential β2-AR drug candidates.
authors.affiliation: Graduate School of Computational Biology and Bioinformatics, Kadir Has University, Cibali, 34083 Istanbul, Turkey.
authors.forename: Ruya
authors.initials: R
authors.lastname: Yakar
authors.affiliation: Department of Bioinformatics and Genetics, Faculty of Engineering and Natural Sciences, Kadir Has University, Cibali, 34083 Istanbul, Turkey. Electronic address: demet.akten@khas.edu.tr.
authors.forename: Ebru Demet
authors.initials: ED
authors.lastname: Akten
mesh_terms: D058672:Adrenergic beta-2 Receptor Antagonists / Q000737:chemistry*; D001665:Binding Sites; D055808:Drug Discovery; D057166:High-Throughput Screening Assays; D006801:Humans; D062105:Molecular Docking Simulation; D011485:Protein Binding; D017434:Protein Structure, Tertiary; D018343:Receptors, Adrenergic, beta-2 / Q000737:chemistry*; D054852:Small Molecule Libraries
chemical_list: D058672:Adrenergic beta-2 Receptor Antagonists; D018343:Receptors, Adrenergic, beta-2; D054852:Small Molecule Libraries
keywords: Docking; Pharmacophore modeling; Scoring; Virtual screening; β(2)-Adrenergic receptor