Identifying EGFR mutation-induced drug resistance based on alpha shape model analysis of the dynamics.
BACKGROUND
Epidermal growth factor receptor (EGFR) mutation-induced drug resistance is a difficult problem in lung cancer treatment. Studying the molecular mechanisms of drug resistance can help to develop corresponding treatment strategies and benefit new drug design.


METHODS
In this study, Rosetta was employed to model the EGFR mutant structures. Then Amber was carried out to conduct molecular dynamics (MD) simulation. Afterwards, we used Computational Geometry Algorithms Library (CGAL) to compute the alpha shape model of the mutants.


RESULTS
We analyzed the EGFR mutation-induced drug resistance based on the motion trajectories obtained from MD simulation. We computed alpha shape model of all the trajectory frames for each mutation type. Solid angle was used to characterize the curvature of the atoms at the drug binding site. We measured the knob level of the drug binding pocket of each mutant from two ways and analyzed its relationship with the drug response level. Results show that 90 % of the mutants can be grouped correctly by setting a certain knob level threshold.


CONCLUSIONS
There is a strong correlation between the geometric properties of the drug binding pocket of the EGFR mutants and the corresponding drug responses, which can be used to predict the response of a new EGFR mutant to a drug molecule.
Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong.
Lichun
L
Ma
Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong.
Bin
B
Zou
Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong.
Hong
H
Yan
Alpha shape modeling; Drug binding site; Epidermal growth factor receptor (EGFR); Gefitinib; Molecular dynamics; Non-small-cell lung cancer (NSCLC); Solid angle