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A soft-modeling approach to interpret thermodynamic and conformational transitions of polynucleotides.

机译:一种软建模方法用于解释多核苷酸的热力学和构象转变。

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摘要

Multivariate outputs from the experimental monitoring of biochemical processes are usually difficult to interpret applying methods based on a priori chemical models. Curve resolution methods are model-free procedures, generally known as soft-modeling methods, which obtain the concentration profiles and instrumental responses of each individual species involved in a multivariate monitored process without making any kind of external assumption. Of the curve resolution methods available, the alternating least squares (ALS) is proposed here because of its ability to operate on one or on several matrices. Furthermore, ALS allows the introduction of information related to the internal data structure and to the general features of the concentration profiles and instrumental responses through the input of suitable constraints in the iterative resolution procedure. The ALS potential is tested on several data sets coming from the multivariate spectrometric monitoring of polyuridylic (polyU), polycytidylic (polyC), and polyadenylic (polyA) protonation equilibria in dioxane/water 30% (v/v). Information concerning the evolution of the concentration profiles and the spectra of each individual species involved in the acid-base equilibria, the presence and pattern of polyelectrolyte effects, and the presence of conformational transitions associated or not with the proton uptake process is presented.
机译:来自生化过程的实验监控的多变量输出通常难以解释基于先验化学模型的应用方法。曲线解析方法是无模型程序,通常称为软建模方法,无需进行任何外部假设即可获取参与多变量监测过程的每个物种的浓度曲线和仪器响应。在可用的曲线分辨率方法中,这里提出了交替最小二乘(ALS),因为它可以在一个或多个矩阵上进行运算。此外,通过在迭代解析程序中输入适当的约束条件,ALS允许引入与内部数据结构以及浓度曲线和仪器响应的一般特征有关的信息。在来自30%二恶烷/水中(v / v)的多尿酸(polyU),多胞苷(polyC)和多腺苷酸(polyA)质子化平衡的多光谱监测的几个数据集上测试了ALS的潜力。提出了有关浓度分布演变和涉及酸碱平衡的每个单独物种的光谱,聚电解质效应的存在和模式以及与质子吸收过程相关或不相关的构象转变的信息。

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