Random screening of compounds in an ETA receptor binding assay led to the discovery of a class of benzenesulfonamide ligands. Optimization led to the development of 5-amino-N-(3,4-dimethyl-5-isoxazolyl)-1-naphthalenesulfonamides which were functional antagonists. Structural features which were important to activity included a 1,5-substitution pattern on the naphthalene ring; a sulfonamide NH with a pK value < 7; an amine, preferably with alkyl substituents, at the 5-position; and methyl groups on both the 3- and 4-positions of the isoxazole.

Bioassay-guided fractionation of the marine alga Dictyochloris fragrans led to the isolation and identification of sulfonoquinovosyl dipalmitoyl glyceride (1). The structure of 1 was determined by a combination of spectroscopic methods. On the basis of P-selectin inhibition assays (i.e., P-selectin-IgG ELISA, cell binding assay of receptor globulin, and platelet:HL60 adhesion, it was demonstrated that 1 selectively blocks the P-selectin-ligand interaction in vitro and could be considered a lead compound for synthetic modification in order to design more potent inhibitors of cell adhesion processes that play important roles in development of inflammatory-mediated disease states.

No abstract

Among the several goals of a high-throughput screening campaign is the identification of as many active chemotypes as possible for further evaluation. Often, however, the number of concentration response curves (e.g., IC(50)s or K(i)s) that can be collected following a primary screen is limited by practical constraints such as protein supply, screening workload, and so forth. One possible approach to this dilemma is to cluster the hits from the primary screen and sample only a few compounds from each cluster. This introduces the question as to how many compounds must be selected from a cluster to ensure that an active compound is identified, if it exists at all. This article seeks to address this question using a Monte Carlo simulation in which the dependence of the success of sampling is directly linked to screening data variability. Furthermore, the authors demonstrate that the use of replicated compounds in the screening collection can easily assess this variability and provide a priori guidance to the screener and chemist as to the extent of sampling required to maximize chemotype identification during the triage process. The individual steps of the Monte Carlo simulation provide insight into the correspondence between the percentage inhibition and eventual IC(50) curves.