Dell'orco Daniele, De Benedetti Pier Giuseppe
Department of Chemistry, University of Modena and Reggio Emilia, Via Campi 183, 41100, Modena, Italy.
J Comput Aided Mol Des. 2008 Jun-Jul;22(6-7):469-78. doi: 10.1007/s10822-008-9175-x. Epub 2008 Jan 23.
Correlation analysis was carried out between binding affinity data values from the literature and physicochemical molecular descriptors of two series of single point mutated canonical inhibitors of serine proteases, namely bovine pancreatic trypsin inhibitor (BPTI) and turkey ovomucoid third domain (OMTKY3), toward seven enzymes. Simple quantitative structure-activity relationship (QSAR) models based on either single or double linear regressions (SLR or DLR) were obtained, which highlight the role of hydrophobic and bulk/polarizability features of mutated amino acids of the inhibitors in modulating both affinity and specificity. The utility of the QSAR paradigm applied to the analysis of mutagenesis data was underlined, resulting in a simple tool to quantitatively help deciphering structure-function/activity relationships (SFAR) of different protein systems.
对文献中的结合亲和力数据值与两类丝氨酸蛋白酶单点突变典型抑制剂(即牛胰蛋白酶抑制剂(BPTI)和火鸡卵类粘蛋白第三结构域(OMTKY3))针对七种酶的物理化学分子描述符进行了相关性分析。获得了基于单线性回归或双线性回归(SLR或DLR)的简单定量构效关系(QSAR)模型,这些模型突出了抑制剂突变氨基酸的疏水、体积/极化率特征在调节亲和力和特异性方面的作用。强调了QSAR范式在诱变数据分析中的实用性,从而产生了一个简单工具,用于定量辅助解读不同蛋白质系统的结构-功能/活性关系(SFAR)。