Prediction of anti-EGFR drug resistance base on binding free energy and hydrogen bond analysis

Weiqiang Zhou, Debby D. Wang, Hong Yan, Maria Wong, Victor Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Mutations in EGFR kinase domain can cause non-small-cell lung cancer, which is one of the most lethal diseases in the world. However, current therapy is limited by the drug resistance effect in different EGFR mutants. There is an urgent demand for developing computational methods to predict drug resisted mutations. In this study, we use quantum mechanics and molecular mechanics models to generate EGFR mutants, and apply molecular dynamic to simulate EGFR-drug interactions. Hydrogen bonds and binding free energy are used to reveal the underlying principle of drug resistance in EGFR. The results show that drug resisted mutants do not establish hydrogen bond between the drug and the protein molecule while having large binding free energy. These properties can be used to predict resistance to anti-EGFR drugs due to protein mutations.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Pages193-197
Number of pages5
DOIs
StatePublished - Oct 10 2013
Externally publishedYes
Event10th Annual IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 - Singapore, Singapore
Duration: Apr 16 2013Apr 19 2013

Publication series

NameProceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

Other

Other10th Annual IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
CountrySingapore
CitySingapore
Period4/16/134/19/13

Keywords

  • EGFR mutation
  • Lung cancer
  • drug resitance
  • hydrogen bond;binding free energy

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Biomedical Engineering

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