The aim of this study is to identify the potential descriptors affecting the inhibitory activity of the peptides inhibiting dipeptidyl peptidase IV (DPP-IV). This study provides important information for assessing the biological activity of the new peptide sequences of food origin or making structural modifications to the current inhibitors to improve their performance. For this purpose, the chemometric method describing the relationship between the structure of food peptides and their biological activity (structure-activity relationship [SAR]) was used to theoretically predict the potential of bioactivity of peptides. Data on the physicochemical properties of amino acids in the dipeptides acting as inhibitors of DPP-IV were collected and analyzed for using these properties as descriptors in further analysis. A total of 252 dipeptide sequences with confirmed DPP-IV inhibitory activity available in the BIOPEP-UWM database were included in the analysis, and 16 descriptors defining individual amino acids (such as molecular weight, polarity, hydropathicity, bulkiness, buried residue, and acceptable and normalized frequency of alpha-helix and beta-sheet) were identified. Based on this information, a data matrix was constructed and used in the chemometric analysis (principal component analysis and multiple linear regression). From the SAR model created, a multiple regression equation was derived to predict the biological activity of the dipeptide DPP-IV inhibitors.

中文翻译：

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通过化学计量学模型研究肽作为二肽基肽酶IV抑制剂的生物活性的构效关系。

这项研究的目的是确定潜在的描述符，以影响抑制二肽基肽酶IV（DPP-IV）的肽的抑制活性。这项研究为评估食品新肽序列的生物学活性或对现有抑制剂进行结构修饰以改善其性能提供了重要信息。为此，描述食品肽结构与其生物学活性之间关系的化学计量方法（结构-活性关系[SAR]）从理论上预测了肽的生物活性潜力。收集有关作为DPP-IV抑制剂的二肽中氨基酸的物理化学性质的数据，并进行分析，以将这些性质用作进一步分析中的描述子。分析中总共包含252条在BIOPEP-UWM数据库中具有已确认的DPP-IV抑制活性的二肽序列，并且16条描述符定义了各个氨基酸（例如分子量，极性，亲水性，蓬松度，掩埋残基和可接受的氨基酸）。并确定了α-螺旋和β-折叠的归一化频率）。基于此信息，构建了一个数据矩阵并将其用于化学计量分析（主要成分分析和多元线性回归）。从创建的SAR模型中，得出了一个多元回归方程来预测二肽DPP-IV抑制剂的生物活性。确定了亲水性，蓬松度，掩埋残留物以及可接受的和标准化的α-螺旋和β-折叠频率。基于此信息，构建了一个数据矩阵并将其用于化学计量分析（主要成分分析和多元线性回归）。从创建的SAR模型中，得出了一个多元回归方程来预测二肽DPP-IV抑制剂的生物活性。确定了亲水性，蓬松度，掩埋残留物以及可接受的和标准化的α-螺旋和β-折叠频率。基于此信息，构建了一个数据矩阵并将其用于化学计量分析（主要成分分析和多元线性回归）。从创建的SAR模型中，得出了一个多元回归方程来预测二肽DPP-IV抑制剂的生物活性。