Development of knowledge-based system for predicting the stability of proteins upon point mutations

Liang Tsung Huang, Lien-Fu Lai, Chao-Chin Wu, M. Michael Gromiha

研究成果: Article

3 引文 (Scopus)

摘要

Prediction of protein stability upon amino acid substitution is an important problem in designing stable proteins. We have developed a classification rule generator for integrating the knowledge of amino acid sequence and experimental stability change upon single mutation. These rules are human readable and hence the method enhances the synergy between expert knowledge and computational system. Utilizing the information about wild type, mutant, three neighboring residues and experimentally observed stability data, we have developed a method based on decision tree for discriminating the stabilizing and destabilizing mutants and predicting the protein stability changes upon single point mutations, which showed an accuracy of 82% and a correlation of 0.70, respectively. In addition, we have developed a fuzzy query method to predict protein stability with partial information. We have developed a web server for predicting the protein stability changes upon single mutations by using fuzzy query mechanism and it is available at http://bioinformatics.myweb.hinet.net/fqstab.htm.

原文English
頁(從 - 到)2293-2299
頁數7
期刊Neurocomputing
73
發行號13-15
DOIs
出版狀態Published - 2010 八月 1

指紋

Protein Stability
Knowledge based systems
Point Mutation
Proteins
Decision Trees
Mutation
Amino acids
Mutant Proteins
Amino Acid Substitution
Computational Biology
Amino Acid Sequence
Bioinformatics
Decision trees
Substitution reactions
Servers

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

引用此文

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Development of knowledge-based system for predicting the stability of proteins upon point mutations. / Huang, Liang Tsung; Lai, Lien-Fu; Wu, Chao-Chin; Michael Gromiha, M.

於: Neurocomputing, 卷 73, 編號 13-15, 01.08.2010, p. 2293-2299.

研究成果: Article

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