ABSTRACT
In this study, we describe the synthesis and structure-activity relationship (SAR) of a series of isoquinoline chemoattractant receptor-homologous molecule expressed on Th2 cells (CRTH2) antagonists. TASP0376377 (15-20), one of the most potent compounds, showed a potent binding affinity (IC50=19 nM) in addition to the excellent functional antagonist activity (IC50=13 nM). Moreover, the efficacy of this compound in a chemotaxis assay (IC50=23 nM) was in good agreement with its potency as a CRTH2 antagonist. In addition, 15-20 exhibited greater selectivity in binding to CRTH2 than to the DP1 prostanoid receptor (IC50 >1 µM) or the enzymes COX-1 and COX-2 (IC50 >10 µM).
Subject(s)
Drug Design , Isoquinolines/pharmacology , Receptors, Immunologic/antagonists & inhibitors , Receptors, Prostaglandin/antagonists & inhibitors , Dose-Response Relationship, Drug , Humans , Isoquinolines/chemical synthesis , Isoquinolines/chemistry , Models, Molecular , Molecular Structure , Structure-Activity Relationship , Th2 CellsABSTRACT
The concept of drug-likeness, an important characteristic for any compound in a screening library, is nevertheless difficult to pin down. Based on our belief that this concept is implicit within the collective experience of working chemists, we devised a data set to capture an intuitive human understanding of both this characteristic and ease of synthesis, a second key characteristic. Five chemists assigned a pair of scores to each of 3980 diverse compounds, with the component scores of each pair corresponding to drug-likeness and ease of synthesis, respectively. Using this data set, we devised binary classifiers with an artificial neural network and a support vector machine. These models were found to efficiently eliminate compounds that are not drug-like and/or hard-to-synthesize derivatives, demonstrating the suitability of these models for use as compound acquisition filters.
