Department of Chemical Engineering, Polytechnique Montréal, Centre-Ville Station, P.O. Box 6079, Montreal, QC, H3C 3A7, Canada.
Life Sciences | NRC Human Health Therapeutics Portfolio, Building Montreal-Royalmount, National Research Council Canada, Montreal, QC, H4P 2R2, Canada.
Sci Rep. 2021 Feb 11;11(1):3685. doi: 10.1038/s41598-021-83268-z.
Surface plasmon resonance-based biosensors have been extensively applied to the characterization of the binding kinetics between purified (bio)molecules, thanks to robust data analysis techniques. However, data analysis for solutions containing multiple interactants is still at its infancy. We here present two algorithms for (1) the reliable and accurate determination of the kinetic parameters of N interactants present at different ratios in N mixtures and (2) the estimation of the ratios of each interactant in a given mixture, assuming that their kinetic parameters are known. Both algorithms assume that the interactants compete to bind to an immobilized ligand in a 1:1 fashion and necessitate prior knowledge of the total concentration of all interactants combined. The effectiveness of these two algorithms was experimentally validated with a model system corresponding to mixtures of four small molecular weight drugs binding to an immobilized protein. This approach enables the in-depth characterization of mixtures using SPR, which may be of considerable interest for many drug discovery or development applications, notably for protein glycovariant analysis.
基于表面等离子体共振的生物传感器已经广泛应用于纯化（生物）分子之间结合动力学的特性分析，这要归功于其强大的数据分析技术。然而，对于含有多种反应物的溶液的数据分析仍处于起步阶段。我们在这里提出了两种算法，用于（1）可靠且准确地确定 N 种混合物中不同比例的 N 种反应物的动力学参数，以及（2）在假定其动力学参数已知的情况下，估算给定混合物中各反应物的比例。这两种算法都假设反应物以 1:1 的方式竞争结合固定化配体，并且需要事先知道所有反应物的总浓度。这两种算法的有效性通过对应于四种小分子药物与固定化蛋白质结合的混合物的模型系统进行了实验验证。这种方法可以使用 SPR 对混合物进行深入的特性分析，这对于许多药物发现或开发应用可能具有相当大的兴趣，特别是对于蛋白质糖变体分析。
