A binary logistic regression model for discriminating real protein-protein interface

被引：0

作者：

LIN Wei SUN Ping and LIU XiangjunBioinformatics Laboratory School of Medicine Tsinghua University Beijing China ^{[100084
]}

机构：

来源：

ProgressinNaturalScience | 2003年 / 06期

关键词：

protein-protein recognition; binary logistic regression; interfacial descriptive variable;

D O I：

暂无

中图分类号：

Q51 [蛋白质];

学科分类号：

071010 ; 081704 ;

摘要：

<正> The selection and study of descriptive variables of protein-protein complex interface is a major question that many biologists come across when the research of protein-protein recognition is concerned. Several variables have been proposed to understand the structural or energetic features of complex interfaces. Here a systematic study of some of these "traditional" variables, as well as a few new ones, is introduced. With the values of these variables extracted from 42 PDB samples with real or false complex interfaces, a binary logistic regression analysis is performed, which results in an effective empirical model for the evaluation of binding probabilities of protein-protein interfaces. The model is validated with 12 samples, and satisfactory results are obtained for both the training and validation sets. Meanwhile, three potential dimeric interfaces of staphylokinase have been investigated and one with the best suitability to our model is proposed .

引用

页码：14 / 20

页数：7

共 14 条

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