Comparative 3D QSAR study on β1-, β2-, and β3-adrenoceptor agonists

A quantitative structure–activity relationship study of tryptamine-based derivatives of β1-, β2-, and β3-adrenoceptor agonists was conducted using comparative molecular field analysis (CoMFA). Correlation coefficients (cross-validated r2) of 0.578, 0.595, and 0.558 were obtained for the three subtypes, respectively, in three different CoMFA models. All three CoMFA models have different steric and electrostatic contributions, implying different requirements inside the binding cavity. The CoMFA coefficient contour plots of the three models and comparisons among these plots provide clues regarding the main chemical features responsible for the biological activity variations and also result in predictions which correlate very well with the observed biological activity. Based on the analysis, a summary regeospecific description of the requirements for improving β-adrenoceptor subtype selectivity is given

Application of 3D Zernike descriptors to shape-based ligand similarity searching

Background: The identification of promising drug leads from a large database of compounds is an important step in the preliminary stages of drug design. Although shape is known to play a key role in the molecular recognition process, its application to virtual screening poses significant hurdles both in terms of the encoding scheme and speed. Results: In this study, we have examined the efficacy of the alignment independent three-dimensional Zernike descriptor (3DZD) for fast shape based similarity searching. Performance of this approach was compared with several other methods including the statistical moments based ultrafast shape recognition scheme (USR) and SIMCOMP, a graph matching algorithm that compares atom environments. Three benchmark datasets are used to thoroughly test the methods in terms of their ability for molecular classification, retrieval rate, and performance under the situation that simulates actual virtual screening tasks over a large pharmaceutical database. The 3DZD performed better than or comparable to the other methods examined, depending on the datasets and evaluation metrics used. Reasons for the success and the failure of the shape based methods for specific cases are investigated. Based on the results for the three datasets, general conclusions are drawn with regard to their efficiency and applicability