Mapping the distribution and affinities of ligand interaction sites on human serum albumin

绘制人血清白蛋白上配体相互作用位点的分布和亲和力图谱

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Abstract

Ligands in many instances interact with a protein at multiple sites with a range of affinities. In this study, ligand-protein interaction sites on human serum albumin (HSA) are mapped using the site-identification by ligand competitive saturation (SILCS)-Biologics approach in conjunction with hydrogen-deuterium exchange (HDX)-mass spectrometry (MS) experiments. Ligands studied include known HSA binders, ibuprofen and ketoprofen, and compounds arginine, alanine, sucrose, and trehalose, excipients used in therapeutic formulations of protein-based drugs. In addition, the impact of excipient binding to HSA on its stability is investigated through temperature-ramp stability studies monitoring solution viscosity. For the studied ligands, interactions that correspond to known drug-binding sites (DSs) are identified. These include previously identified ibuprofen and ketoprofen interaction sites as well as additional sites and, in the case of the excipients, the ligands are shown to also bind at previously unidentified interaction sites, termed excipient sites (ESs) with 20 or more sites identified for the studied compounds. HDX-MS titrations were used to determine dissociation constants for a subset of the interaction sites for ibuprofen, ketoprofen, arginine, and sucrose, which exhibited K(d) values in the low micromolar to millimolar range in satisfactory agreement with SILCS-Biologics predicted affinities, validating the computational approach to identify both high- and low-affinity interaction sites. The stability studies indicate the excipients offer protection at low excipient/protein ratios up to 66 with destabilization occurring at ratios above 132 with the exception of sucrose at the t(0) time point, indicating that the more favorable affinities of sucrose seen in the SILCS-Biologics and HDX-MS analyses contribute to protein stabilization. These results indicate that ligands can bind to large numbers of interaction sites on proteins, with those interactions having implications for the development of formulations for therapeutic proteins.

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