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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.


a and b show the solid angle values at the drug binding site of the first trajectory frame of the mutants delE709_T710insD and delL747_T751, respectively. The dark dashed lines indicate the position of 0. c and d demonstrate the number of convex and concave atoms with different solid angle value thresholds at the drug binding site of the two mutants
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Fig2: a and b show the solid angle values at the drug binding site of the first trajectory frame of the mutants delE709_T710insD and delL747_T751, respectively. The dark dashed lines indicate the position of 0. c and d demonstrate the number of convex and concave atoms with different solid angle value thresholds at the drug binding site of the two mutants

Mentions: We computed the solid angles of all the atoms at the drug binding site, and the values of those who were not at the surface of the drug binding site were set to zero. Figures 2a and b show the solid angle values at the first trajectory frame of the mutants delL747_T751 (RL = 2) and delE709_T710insD (RL = 4). According to the RLs of the two mutants, they are classified to the drug Response and No-response group, respectively. As shown in the two figures, the number of convex atoms of the mutant delE709_T710insD is more than that of delL747_T751. Then we counted the number of convex and concave atoms for all the 200 trajectory frames of the two mutants respectively, and even made a further step to calculate the number of atoms with SA (solid angle value) > 0.5 or SA < − 0.5. Figures 2c and d indicate that the concave indexes of the two mutants are mixed together while the convex ones are clearly separated. Consequently, we only consider the convex-related characteristics of the mutants in the following studies.Fig. 2


Identifying EGFR mutation-induced drug resistance based on alpha shape model analysis of the dynamics
a and b show the solid angle values at the drug binding site of the first trajectory frame of the mutants delE709_T710insD and delL747_T751, respectively. The dark dashed lines indicate the position of 0. c and d demonstrate the number of convex and concave atoms with different solid angle value thresholds at the drug binding site of the two mutants
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig2: a and b show the solid angle values at the drug binding site of the first trajectory frame of the mutants delE709_T710insD and delL747_T751, respectively. The dark dashed lines indicate the position of 0. c and d demonstrate the number of convex and concave atoms with different solid angle value thresholds at the drug binding site of the two mutants
Mentions: We computed the solid angles of all the atoms at the drug binding site, and the values of those who were not at the surface of the drug binding site were set to zero. Figures 2a and b show the solid angle values at the first trajectory frame of the mutants delL747_T751 (RL = 2) and delE709_T710insD (RL = 4). According to the RLs of the two mutants, they are classified to the drug Response and No-response group, respectively. As shown in the two figures, the number of convex atoms of the mutant delE709_T710insD is more than that of delL747_T751. Then we counted the number of convex and concave atoms for all the 200 trajectory frames of the two mutants respectively, and even made a further step to calculate the number of atoms with SA (solid angle value) > 0.5 or SA < − 0.5. Figures 2c and d indicate that the concave indexes of the two mutants are mixed together while the convex ones are clearly separated. Consequently, we only consider the convex-related characteristics of the mutants in the following studies.Fig. 2

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&nbsp;% 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.