Mandell A J, Selz K A, Shlesinger M F
The Cielo Institute, 486 Sunset Drive, Asheville, NC 28804, USA.
Proc Natl Acad Sci U S A. 1997 Dec 9;94(25):13576-81. doi: 10.1073/pnas.94.25.13576.
Patterns in sequences of amino acid hydrophobic free energies predict secondary structures in proteins. In protein folding, matches in hydrophobic free energy statistical wavelengths appear to contribute to selective aggregation of secondary structures in "hydrophobic zippers." In a similar setting, the use of Fourier analysis to characterize the dominant statistical wavelengths of peptide ligands' and receptor proteins' hydrophobic modes to predict such matches has been limited by the aliasing and end effects of short peptide lengths, as well as the broad-band, mode multiplicity of many of their frequency (power) spectra. In addition, the sequence locations of the matching modes are lost in this transformation. We make new use of three techniques to address these difficulties: (i) eigenfunction construction from the linear decomposition of the lagged covariance matrices of the ligands and receptors as hydrophobic free energy sequences; (ii) maximum entropy, complex poles power spectra, which select the dominant modes of the hydrophobic free energy sequences or their eigenfunctions; and (iii) discrete, best bases, trigonometric wavelet transformations, which confirm the dominant spectral frequencies of the eigenfunctions and locate them as (absolute valued) moduli in the peptide or receptor sequence. The leading eigenfunction of the covariance matrix of a transmembrane receptor sequence locates the same transmembrane segments seen in n-block-averaged hydropathy plots while leaving the remaining hydrophobic modes unsmoothed and available for further analyses as secondary eigenfunctions. In these receptor eigenfunctions, we find a set of statistical wavelength matches between peptide ligands and their G-protein and tyrosine kinase coupled receptors, ranging across examples from 13.10 amino acids in acid fibroblast growth factor to 2.18 residues in corticotropin releasing factor. We find that the wavelet-located receptor modes in the extracellular loops are compatible with studies of receptor chimeric exchanges and point mutations. A nonbinding corticotropin-releasing factor receptor mutant is shown to have lost the signatory mode common to the normal receptor and its ligand. Hydrophobic free energy eigenfunctions and their transformations offer new quantitative physical homologies in database searches for peptide-receptor matches.
氨基酸疏水自由能序列中的模式可预测蛋白质的二级结构。在蛋白质折叠过程中,疏水自由能统计波长的匹配似乎有助于“疏水拉链”中二级结构的选择性聚集。在类似的情况下,使用傅里叶分析来表征肽配体和受体蛋白疏水模式的主要统计波长以预测此类匹配,受到短肽长度的混叠和末端效应的限制,以及它们许多频率(功率)谱的宽带、模式多样性的限制。此外,匹配模式的序列位置在这种转换中丢失了。我们新采用了三种技术来解决这些困难:(i)从配体和受体的滞后协方差矩阵的线性分解构建本征函数,将其作为疏水自由能序列;(ii)最大熵、复极点功率谱,它选择疏水自由能序列或其本征函数的主要模式;(iii)离散、最佳基、三角小波变换,它确认本征函数的主要光谱频率并将它们定位为肽或受体序列中的(绝对值)模量。跨膜受体序列协方差矩阵的主导本征函数定位出现在n块平均亲水性图中的相同跨膜片段,同时使其余疏水模式不被平滑处理,并作为二级本征函数可供进一步分析。在这些受体本征函数中,我们发现了一组肽配体与其G蛋白和酪氨酸激酶偶联受体之间的统计波长匹配,范围从酸性成纤维细胞生长因子中的13.10个氨基酸到促肾上腺皮质激素释放因子中的2.18个残基。我们发现细胞外环中的小波定位受体模式与受体嵌合交换和点突变的研究结果一致。一个无结合能力的促肾上腺皮质激素释放因子受体突变体被证明失去了正常受体及其配体共有的标志性模式。疏水自由能本征函数及其变换在数据库搜索肽 - 受体匹配中提供了新的定量物理同源性。