Definitive Metabolite Identification Coupled with Automated Ligand Identification System (ALIS) Technology: A Novel Approach to Uncover Structure–Activity Relationships and Guide Drug Design in a Factor IXa Inhibitor Program

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• 作者：Ting Zhang ; Yong Liu ; Xianshu Yang ; Gary E. Martin ; Huifang Yao ; Jackie Shang ; Randal M. Bugianesi ; Kenneth P. Ellsworth ; Lisa M. Sonatore ; Peter Nizner ; Edward C. Sherer ; Susan E. Hill ; Ian W. Knemeyer ; Wayne M. Geissler ; Peter J. Dandliker ; Roy Helmy ; Harold B. Wood
• 刊名：Journal of Medicinal Chemistry
• 出版年：2016
• 出版时间：March 10, 2016
• 年：2016
• 卷：59
• 期：5
• 页码：1818-1829
• 全文大小：502K
• ISSN：1520-4804

文摘

A potent and selective Factor IXa (FIXa) inhibitor was subjected to a series of liver microsomal incubations, which generated a number of metabolites. Using automated ligand identification system-affinity selection (ALIS-AS) methodology, metabolites in the incubation mixture were prioritized by their binding affinities to the FIXa protein. Microgram quantities of the metabolites of interest were then isolated through microisolation analytical capabilities, and structurally characterized using MicroCryoProbe heteronuclear 2D NMR techniques. The isolated metabolites recovered from the NMR experiments were then submitted directly to an in vitro FIXa enzymatic assay. The order of the metabolites’ binding affinity to the Factor IXa protein from the ALIS assay was completely consistent with the enzymatic assay results. This work showcases an innovative and efficient approach to uncover structure–activity relationships (SARs) and guide drug design via microisolation–structural characterization and ALIS capabilities.