基于偏最小二乘法的抗类风湿性免疫活性肽定量构效建模研究

Quantitative Structure-activity Relationship Model of Anti-rheumatoid Immune-active Peptides Based on Partial Least Square Method

摘要:

本研究采用偏最小二乘法（PLS）建立了抗类风湿性免疫活性肽的QSAR模型。首先从常见氨基酸各原子间静电、立体和疏水等与生物活性直接相关的非键作用方式，筛选出适合于免疫活性肽定量-构效建模的氨基酸描述符，再采用此描述符对47个肽数据集进行定量构效关系建模。结果表明，Z-scales氨基酸描述符实现了对氨基酸残基的多位置、多变量的定量结构描述，最适合用于描述免疫活性肽的物化性质。根据Z-scales描述符，经主成分分析和偏最小二乘法建立的模型有良好的可靠性和预测能力，模型的复相关系数R2=0.986，均方根误差RMSE=0.253，留一交叉验证相关系数Q2LOO=0.893，外部验证相关系数Q2ext=0.971。通过对免疫活性肽构效关系的研究为类风湿性关节炎新耐受原的筛选、设计开辟了广阔空间，同时也为功能食品的开发和创新提供了新手段。

Abstract:

In this study, partial least squares (PLS) method was used to build a quantitative structure-activity relationship (QSAR) model for anti-rheumatoid immune activity of peptides. First, based on the bioactivity-related non-bonding effects (such as electrostatic, steric, and hydrophobic interactions) of each atom, the amino acids descriptor best suited for QSAR model of immune activity of peptides was selected to construct a QSAR model for a 47-peptide data set. The results showed that Z-scales amino descriptor achieved multiple-position and multivariate quantitative structure description for amino acid residues and was the most suitable for describing physicochemical properties of anti-rheumatoid immune-active peptides. Using the Z-scales descriptor, the model built on principle component analysis and PLS showed good reliability and predictive ability, with multiple correlation coefficient of 0.986, root mean square error (RMSE) of 0.253, leave-one-out cross-validation correlation coefficient of 0.893, and external validation coefficient of 0.971. Based on the structure-activity relationship of immune-active peptides, this study provides new opportunities for screening and design of new tolerogens for rheumatoid arthritis, thus providing a new approach for the development innovative functional food products.