Computational platform for modelling, analysis, and prediction of anti-EGFR drug resistance for lung cancer
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Pages (from-to) | 40-42 |
| Journal / Publication | Hong Kong medical journal = Xianggang yi xue za zhi |
| Volume | 25 |
| Issue number | 6 (Supplement 9) |
| Publication status | Published - Dec 2019 |
Link(s)
| Document Link | Links
|
|---|---|
| Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85077307970&origin=recordpage |
| Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(a5bb583e-8410-4129-b7ad-c9d5b0d15b1f).html |
Abstract
1. Epidermal growth factor receptor (EGFR) mutation is an important cause of drug resistance in non-small cell lung cancer (NSCLC). We conducted computational modelling of EGFR mutants and analysis of EGFR-drug interaction patterns.
2. Any observed EGFR mutation can be modelled mathematically, and its 3D structure can be predicted computationally. The fundamental cause of drug resistance can be found at the atomic level.
3. Different drugs can be analysed. Based on our computer model, the binding strength between an EGFR mutant and a drug can be calculated.
4. Drug resistance can be evaluated for each mutation and each drug. Thus, a comprehensive database of EGFR mutation and drug effectiveness is established and is available online. The database provides a useful reference to medical doctors.
5. Our computational framework is less expensive than wet-lab experiments. It can also be used to study drug resistance related to other diseases.
2. Any observed EGFR mutation can be modelled mathematically, and its 3D structure can be predicted computationally. The fundamental cause of drug resistance can be found at the atomic level.
3. Different drugs can be analysed. Based on our computer model, the binding strength between an EGFR mutant and a drug can be calculated.
4. Drug resistance can be evaluated for each mutation and each drug. Thus, a comprehensive database of EGFR mutation and drug effectiveness is established and is available online. The database provides a useful reference to medical doctors.
5. Our computational framework is less expensive than wet-lab experiments. It can also be used to study drug resistance related to other diseases.
Research Area(s)
Citation Format(s)
Computational platform for modelling, analysis, and prediction of anti-EGFR drug resistance for lung cancer. / Yan, H; Zhu, GY; Wong, M et al.
In: Hong Kong medical journal = Xianggang yi xue za zhi, Vol. 25, No. 6 (Supplement 9), 12.2019, p. 40-42.
In: Hong Kong medical journal = Xianggang yi xue za zhi, Vol. 25, No. 6 (Supplement 9), 12.2019, p. 40-42.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
