@inproceedings{00cf4ac0740f40ebb321caa08b4943c5,
title = "Prediction of anti-EGFR drug resistance base on binding free energy and hydrogen bond analysis",
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.",
keywords = "EGFR mutation, Lung cancer, drug resitance, hydrogen bond;binding free energy",
author = "Weiqiang Zhou and Wang, {Debby D.} and Hong Yan and Maria Wong and Victor Lee",
year = "2013",
month = oct,
day = "10",
doi = "10.1109/CIBCB.2013.6595408",
language = "English (US)",
isbn = "9781467358750",
series = "Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013",
pages = "193--197",
booktitle = "Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013",
note = "10th Annual IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 ; Conference date: 16-04-2013 Through 19-04-2013",
}