Comparative receptor surface analysis of octopaminergic antagonists for the locust neuronal octopamine receptor

• Published in: Computational biology and chemistry Vol. 27; no. 6; pp. 531 - 540
• Main Authors: Hirashima, Akinori, Kuwano, Eiichi, Eto, Morifusa
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.12.2003
• Subjects: Animals; Antagonist for octopamine receptor; Cerius2; Comparative receptor surface analysis; Computer Graphics; Grasshoppers - chemistry; Grasshoppers - metabolism; Ligands; Locusta migratoria; Models, Theoretical; Molecular Conformation; Molecular Structure; Neurons - chemistry; Neurons - metabolism; Octopamine - agonists; Octopamine - antagonists & inhibitors; Octopamine - chemistry; octopamine receptors; octopaminergic antagonists; Quantitative structure–activity relationship; Receptor surface model; Receptors, Biogenic Amine - agonists; Receptors, Biogenic Amine - antagonists & inhibitors; Receptors, Biogenic Amine - chemistry; Structure-Activity Relationship; Comparative receptor surface analysis; Cerius2; Locusta migratoria; Quantitative structure–activity relationship; Antagonist for octopamine receptor; Receptor surface model
• ISSN: 1476-9271; 1476-928X
• DOI: 10.1016/j.compbiolchem.2003.07.001

In drug discovery, it is common to have measured activity data for a set of compounds acting upon a particular protein but not to have knowledge of the three-dimensional structure of the protein active site. In the absence of such three-dimensional information, one can attempt to build a hypothetical model of the receptor site that can provide insight about receptor site characteristics. Such a model is known as a comparative receptor surface analysis (CoRSA) model, which provides compact and quantitative descriptors which capture three-dimensional information about a putative receptor site. The quantitative structure–activity relationship (QSAR) of a set of 20 antagonists for octopamine (OA) receptor 3 in locust nervous tissue, was analyzed using CoRSA. Three-dimensional energetics descriptors were calculated from receptor surface model (RSM)–ligand interaction and these three-dimensional descriptors were used in QSAR analysis. The predictive character of the QSAR was further assessed using 24 agonists for OA receptor as test molecules. An RSM was generated using some subset of the most active structures and the results provided useful information in the characterization and differentiation of OA receptor.