In silico quantitative prediction of peptides binding affinity to human MHC molecule: an intuitive quantitative structure–activity relationship approach
In silico quantitative prediction of peptides binding affinity to human MHC molecule: an intuitive quantitative structure–activity relationship approach
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肽与人类 MHC 分子结合亲和力的计算机定量预测：一种直观的定量结构-活性关系方法
DOI：
10.1007/s00726-008-0116-8
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发表时间：
2009-03
期刊：
影响因子：
3.5
通讯作者：
中科院分区：
文献类型：
--
作者：
本文从数千个氨基酸的结构和性质参数中精选出23种电子性质、37种空间性质、54种疏水性质和5种氢键性质。对这些参数进行主成分分析(PCA)，得到了涉及20个编码氨基酸显著非键性质的10个分数向量，称为氨基酸的划分物理化学性质分数(DPPS)。然后用DPPS描述符描述了152个HLA-A*0201限制性CTL表位的结构，并用遗传算法选择了影响结合亲和力的重要变量，用偏最小二乘法建立了定量构效关系(QSAR)模型来预测多肽与HLA-A*0201分子的相互作用。对得到的基于DPPS的QSAR模型进行了统计分析，结果与实验结果和分子图形显示结果吻合较好。结合多肽中不同残基的不同性质可能对HLA-A*0201分子与其多肽配体的相互作用有显著影响。特别是，多肽锚定残基的疏水性和氢键可能对相互作用有重要贡献。结果表明，DPPS能很好地反映抗原肽的结构特征，是一种有效、直观的预测抗原肽与人类白细胞抗原A*0201结合的亲和力的方法。我们希望这种基于物理原理的方法也可以应用于其他蛋白质-多肽相互作用。
In this paper, we have handpicked 23 kinds of electronic properties, 37 kinds of steric properties, 54 kinds of hydrophobic properties and 5 kinds of hydrogen bond properties from thousands of amino acid structural and property parameters. Principal component analysis (PCA) was applied on these parameters and thus ten score vectors involving significant nonbonding properties of 20 coded amino acids were yielded, called the divided physicochemical property scores (DPPS) of amino acids. The DPPS descriptor was then used to characterize the structures of 152 HLA-A*0201-restricted CTL epitopes, and significant variables being responsible for the binding affinities were selected by genetic algorithm, and a quantitative structure–activity relationship (QSAR) model by partial least square was established to predict the peptide-HLA-A*0201 molecule interactions. Statistical analysis on the resulted DPPS-based QSAR models were consistent well with experimental exhibits and molecular graphics display. Diversified properties of the different residues in binding peptides may contribute remarkable effect to the interactions between the HLA-A*0201 molecule and its peptide ligands. Particularly, hydrophobicity and hydrogen bond of anchor residues of peptides may have a significant contribution to the interactions. The results showed that DPPS can well represent the structural characteristics of the antigenic peptides and is a promising approach to predict the affinities of peptide binding to HLA-A*0201 in a efficient and intuitive way. We expect that this physical-principle based method can be applied to other protein–peptide interactions as well.
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影响因子：
2
作者：
Xuan Xiao;Shihuang Shao;Yongsheng Ding;Zheng-De Huang;Xiaojing Chen;K. Chou
通讯作者：
Xuan Xiao;Shihuang Shao;Yongsheng Ding;Zheng-De Huang;Xiaojing Chen;K. Chou
影响因子：
56.9
作者：
A. Sette
通讯作者：
A. Sette
DOI：
10.1021/ci950183m
发表时间：
1996
期刊：
J. Chem. Inf. Comput. Sci.
影响因子：
--
作者：
M. Soskic;D. Plavsic;N. Trinajstic
通讯作者：
M. Soskic;D. Plavsic;N. Trinajstic
DOI：
10.1089/cmb.2004.11.683
发表时间：
2004
期刊：
J. Comput. Biol.
影响因子：
--
作者：
Zhihua Lin;Yuzhang Wu;Bo Zhu;B. Ni;Li Wang
通讯作者：
Zhihua Lin;Yuzhang Wu;Bo Zhu;B. Ni;Li Wang
影响因子：
4.4
作者：
M. D. Guercio;J. Sidney;Gary G. Hermanson;Cynthia Perez;Howard M. Grey;Ralph T. Kubo;Alessandro Sette
通讯作者：
M. D. Guercio;J. Sidney;Gary G. Hermanson;Cynthia Perez;Howard M. Grey;Ralph T. Kubo;Alessandro Sette