標題: Sequence analysis and rule development of predicting protein stability change upon mutation using decision tree model
作者: Huang, Liang-Tsung
Gromiha, M. Michael
Ho, Shinn-Ying
生物科技學系
生物資訊及系統生物研究所
Department of Biological Science and Technology
Institude of Bioinformatics and Systems Biology
關鍵字: bioinformatics;data mining;decision trees;prediction;protein stability
公開日期: 1-八月-2007
摘要: Understanding the mechanism of the protein stability change is one of the most challenging tasks. Recently, the prediction of protein stability change affected by single point mutations has become an interesting topic in molecular biology. However, it is desirable to further acquire knowledge from large databases to provide new insights into the nature of them. This paper presents an interpretable prediction tree method (named iPTREE-2) that can accurately predict changes of protein stability upon mutations from sequence based information and analyze sequence characteristics from the viewpoint of composition and order. Therefore, iPTREE-2 based on a regression tree algorithm exhibits the ability of finding important factors and developing rules for the purpose of data mining. On a dataset of 1859 different single point mutations from thermodynamic database, ProTherm, iPTREE-2 yields a correlation coefficient of 0.70 between predicted and experimental values. In the task of data mining, detailed analysis of sequences reveals the possibility of the compositional specificity of residues in different ranges of stability change and implies the existence of certain patterns. As building rules, we found that the mutation residues in wild type and in mutant protein play an important role. The present study demonstrates that iPTREE-2 can serve the purpose of predicting protein stability change, especially when one requires more understandable knowledge.
URI: http://dx.doi.org/10.1007/s00894-007-0197-4
http://hdl.handle.net/11536/10510
ISSN: 1610-2940
DOI: 10.1007/s00894-007-0197-4
期刊: JOURNAL OF MOLECULAR MODELING
Volume: 13
Issue: 8
起始頁: 879
結束頁: 890
顯示於類別:期刊論文


文件中的檔案:

  1. 000247428800002.pdf