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

doi:10.1109/CIBCB.2013.6595408

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 proceeding › Conference contribution › peer-review

9 Citations (Scopus)

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 language	English
Title of host publication	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
Number of pages	5
DOIs	https://doi.org/10.1109/CIBCB.2013.6595408
Publication status	Published - 2013
Externally published	Yes
Event	10th 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: 16 Apr 2013 → 19 Apr 2013

Publication series

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

Conference

Conference	10th Annual IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Country/Territory	Singapore
City	Singapore
Period	16/04/13 → 19/04/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

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

Access to Document

10.1109/CIBCB.2013.6595408

Cite this

Zhou, W., Wang, D. D., Yan, H., Wong, M., & Lee, V. (2013). Prediction of anti-EGFR drug resistance base on binding free energy and hydrogen bond analysis. In Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 (pp. 193-197). Article 6595408 (Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013). https://doi.org/10.1109/CIBCB.2013.6595408

Zhou, Weiqiang ; Wang, Debby D. ; Yan, Hong et al. / Prediction of anti-EGFR drug resistance base on binding free energy and hydrogen bond analysis. Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. 2013. pp. 193-197 (Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013).

@inproceedings{4a72b396420247338605f5882abb6038,

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",

doi = "10.1109/CIBCB.2013.6595408",

language = "English",

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",

}

Zhou, W, Wang, DD, Yan, H, Wong, M & Lee, V 2013, Prediction of anti-EGFR drug resistance base on binding free energy and hydrogen bond analysis. in Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013., 6595408, Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, pp. 193-197, 10th Annual IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, Singapore, Singapore, 16/04/13. https://doi.org/10.1109/CIBCB.2013.6595408

Prediction of anti-EGFR drug resistance base on binding free energy and hydrogen bond analysis. / Zhou, Weiqiang; Wang, Debby D.; Yan, Hong et al.
Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. 2013. p. 193-197 6595408 (Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Prediction of anti-EGFR drug resistance base on binding free energy and hydrogen bond analysis

AU - Zhou, Weiqiang

AU - Wang, Debby D.

AU - Yan, Hong

AU - Wong, Maria

AU - Lee, Victor

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

KW - EGFR mutation

KW - Lung cancer

KW - drug resitance

KW - hydrogen bond;binding free energy

UR - https://www.scopus.com/pages/publications/84885077721

U2 - 10.1109/CIBCB.2013.6595408

DO - 10.1109/CIBCB.2013.6595408

M3 - Conference contribution

AN - SCOPUS:84885077721

SN - 9781467358750

T3 - Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

SP - 193

EP - 197

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

T2 - 10th Annual IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

Y2 - 16 April 2013 through 19 April 2013

ER -

Zhou W, Wang DD, Yan H, Wong M, Lee V. Prediction of anti-EGFR drug resistance base on binding free energy and hydrogen bond analysis. In Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. 2013. p. 193-197. 6595408. (Proceedings of the IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013). doi: 10.1109/CIBCB.2013.6595408

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

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this