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Identifying EGFR mutation-induced drug resistance based on alpha shape model analysis of the dynamics

View Article: PubMed Central - PubMed

ABSTRACT

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.

No MeSH data available.


The relationship of knob level and drug response level of the 30 mutants, with the solid angle value threshold setting to 0, 0.01 and 0.02, respectively. a to c show the scatter plots of the mutants for each drug response level. d to f are the corresponding box plots of (a) to (c)
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Fig4: The relationship of knob level and drug response level of the 30 mutants, with the solid angle value threshold setting to 0, 0.01 and 0.02, respectively. a to c show the scatter plots of the mutants for each drug response level. d to f are the corresponding box plots of (a) to (c)

Mentions: Then we defined knob level, the mean of the average convex degrees for the 200 trajectory frames, to characterize the drug binding site of each mutant. The solid angle values of some atoms are very close to zero (Figs. 2a and b), making a large difference on the average convex degree of each trajectory frame. Therefore, we set a solid angle value threshold to avoid their influence. Afterwards, we explored the relationship between knob level and drug response level of the 30 mutants. The results are shown in Fig. 4, with solid angle value threshold setting to 0, 0.01 and 0.02 respectively. Figures 4a to c are the scatter plots of the mutants. When the threshold equals to 0.01, the mutants of the Response and No-response groups can be separated with only 3 errors (3 mutants belonging to RL = 2 are wrongly categorized). Figures 4d to f shows the corresponding box plots of Figs. 4a to c, respectively. As shown in these figures, the median knob level values (bands inside the boxes) of the four drug response level groups are clearly separated. In addition, the main bodies (boxes) of the two groups (Response and No-response) of mutants are at different knob levels, when the threshold equals to 0.01 or 0.02.Fig. 4


Identifying EGFR mutation-induced drug resistance based on alpha shape model analysis of the dynamics
The relationship of knob level and drug response level of the 30 mutants, with the solid angle value threshold setting to 0, 0.01 and 0.02, respectively. a to c show the scatter plots of the mutants for each drug response level. d to f are the corresponding box plots of (a) to (c)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5015241&req=5

Fig4: The relationship of knob level and drug response level of the 30 mutants, with the solid angle value threshold setting to 0, 0.01 and 0.02, respectively. a to c show the scatter plots of the mutants for each drug response level. d to f are the corresponding box plots of (a) to (c)
Mentions: Then we defined knob level, the mean of the average convex degrees for the 200 trajectory frames, to characterize the drug binding site of each mutant. The solid angle values of some atoms are very close to zero (Figs. 2a and b), making a large difference on the average convex degree of each trajectory frame. Therefore, we set a solid angle value threshold to avoid their influence. Afterwards, we explored the relationship between knob level and drug response level of the 30 mutants. The results are shown in Fig. 4, with solid angle value threshold setting to 0, 0.01 and 0.02 respectively. Figures 4a to c are the scatter plots of the mutants. When the threshold equals to 0.01, the mutants of the Response and No-response groups can be separated with only 3 errors (3 mutants belonging to RL = 2 are wrongly categorized). Figures 4d to f shows the corresponding box plots of Figs. 4a to c, respectively. As shown in these figures, the median knob level values (bands inside the boxes) of the four drug response level groups are clearly separated. In addition, the main bodies (boxes) of the two groups (Response and No-response) of mutants are at different knob levels, when the threshold equals to 0.01 or 0.02.Fig. 4

View Article: PubMed Central - PubMed

ABSTRACT

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.

No MeSH data available.