Development of Biosensor Technology for Protein Interactions

由于地表粗糙，地表的物理和化学微环境是不均匀的。 因此，在溶液中具有单一类别结合位点的蛋白质一旦与表面化学交联，就可以显示结合性质的分散。 作为一种工具来研究这个合奏的表面网站，我们以前介绍了一种计算方法来确定从实验数据的亲和力和动力学结合位点参数的分布。 我们现在已经扩展了这种方法，将质量输运限制的一阶近似。 它使我们现在，第一次，同时考虑到两个最常见的实验问题的表面结合时，使用生物传感器来表征蛋白质的相互作用，网站的异质性和质量传输的限制，从而模拟实验数据的噪声水平内的数据采集，并充分利用高灵敏度的表面等离子体共振生物传感器的蛋白质相互作用的研究。 我们已经应用这种技术的详细研究流体动力学效应对分析物的表面附近的运输。 在聚合物固定化基质的存在下，数据清楚地显示出显着较小的传质系数相比，从层流模型的理论预测。 额外的限速步骤的起源尚不清楚，但似乎是由于可溶性分析物与固定化聚合物的流体动力学或静电相互作用，导致蛋白质扩散减少，导致聚合物基质对可溶性分析物的渗透性有限。 我们还开始使用这种新的工具，功能性地表征合奏的表面结合位点，研究不同类型的表面，表面附着的策略，和固定的表面密度的影响的性质。 正如预期的那样，第一个结果表明，这些因素可以显着影响表面位点的结合性能。 最近，我们通过引入贝叶斯正则化改进了计算方法，使我们能够引入不同的分布形状的先验期望。 这种方法有助于提高方法的分辨率，并对不同的分布进行详细的比较。

Due to surface rugosity, the physical and chemical microenvironment at the surface is heterogeneous. Therefore, proteins that have a single class of binding sites in solution can show a dispersion in the binding properties, once chemically crosslinked to the surface. As a tool to study this ensemble of surface sites, we previously introduced a computational approach to determine distributions of affinity and kinetic binding site parameters from experimental data. We have now extended this approach to incorporate first-order approximations of mass transport limitation. It allows us now, for the first time, to account simultaneously for the two most commonly encountered experimental problems of surface binding when using biosensors to characterize protein interactions, site heterogeneity and mass transport limitation, and thereby model experimental data to within the level of noise of data acquisition, and fully exploit the high sensitivity of surface plasmon resonance biosensors for the study of protein interactions. We have applied this technique to the detailed study of hydrodynamic effects on analyte transport near the surface. In the presence of a polymeric immobilization matrix, the data clearly show significantly smaller mass transport coefficients as compared to the theoretical predictions from a laminar flow model. The origin of the additional, rate-limiting step is unclear, but appears to be due to hydrodynamic or electrostatic interactions of the soluble analyte with immobilized polymers resulting in reduced protein diffusion, resulting in limited permeability of the polymer matrix for soluble analytes. We have also embarked on using this new tool for functionally characterizing the ensemble of surface binding sites to study the properties of different types of surfaces, strategies for surface attachment, and effect of surface density of immobilization. As expected, first results show that these factors can significantly influence the binding properties of the surface sites. Recently, we have refined the computational approach by introducing Bayesian regularization that enables us to introduce different prior expectations of the shape of the distribution. This approach helps to increase the resolution of the method, and to make detailed comparison of different distributions.