Lejon T, Strøm M B, Svendsen J S
Department of Chemistry, University of Tromsø, Norway.
J Pept Sci. 2001 Feb;7(2):74-81. doi: 10.1002/psc.295.
Pentadecapeptides based on modified murine lactoferricin (LFM) sequences show varying degrees of antibacterial activity against Escherichia coli and Staphylococcus aureus. By means of projections to latent structures (PLS), a good correlation is obtained if the biological activity is modelled as a function of variables describing peptide properties, e.g. alpha-helicity, hydrophobicity/hydrophilicity and charge. Using variables derived from a principal component analysis (PCA) of all naturally occurring amino acids, it is possible to describe the amino acid content of the peptides using three variables per amino acid position. The resulting descriptor matrix is then used to develop quantitative structure-activity relationships (QSAR). It is shown that the theoretically derived descriptors model the activity of the peptides better than the earlier model, and that properties of the peptides other than antibacterial activity can be predicted.
基于修饰的鼠乳铁蛋白(LFM)序列的十五肽对大肠杆菌和金黄色葡萄球菌表现出不同程度的抗菌活性。通过潜在结构投影(PLS),如果将生物活性建模为描述肽特性的变量(如α-螺旋性、疏水性/亲水性和电荷)的函数,则可获得良好的相关性。使用从所有天然存在的氨基酸的主成分分析(PCA)得出的变量,每个氨基酸位置用三个变量就可以描述肽的氨基酸含量。然后将所得的描述符矩阵用于建立定量构效关系(QSAR)。结果表明,理论推导的描述符比早期模型能更好地模拟肽的活性,并且可以预测肽除抗菌活性以外的其他特性。