TY - GEN
T1 - Path sampling simulations reveal how the Q61L mutation restricts the dynamics of KRas
AU - Roet, Sander
AU - Hooft, Ferry
AU - Bolhuis, Peter G.
AU - Swenson, David W.H.
AU - Vreede, Jocelyne
PY - 2020/2/28
Y1 - 2020/2/28
N2 - The GTPase KRas is a signaling protein in networks for cell differentiation, growth, and division. KRas mutations can prolong activation of these networks, resulting in tumor formation. When active, KRas tightly binds GTP. Several oncogenic mutations affect the conversion between this rigid state and inactive, more flexible states. Detailed understanding of these transitions may provide valuable insights into how mutations affect KRas. Path sampling simulations, which focus on transitions, show KRas visiting several states, which are the same for wild type and the oncogenic mutant Q61L. Large differences occur when converting between these states, indicating the dramatic effect of the Q61L mutation on KRas dynamics. For Q61L a route to the flexible state is inaccessible, thus shifting the equilibrium to more rigid states. Our methodology presents a novel way to predict dynamical effects of KRas mutations, which may aid in identifying potential therapeutic targets.
AB - The GTPase KRas is a signaling protein in networks for cell differentiation, growth, and division. KRas mutations can prolong activation of these networks, resulting in tumor formation. When active, KRas tightly binds GTP. Several oncogenic mutations affect the conversion between this rigid state and inactive, more flexible states. Detailed understanding of these transitions may provide valuable insights into how mutations affect KRas. Path sampling simulations, which focus on transitions, show KRas visiting several states, which are the same for wild type and the oncogenic mutant Q61L. Large differences occur when converting between these states, indicating the dramatic effect of the Q61L mutation on KRas dynamics. For Q61L a route to the flexible state is inaccessible, thus shifting the equilibrium to more rigid states. Our methodology presents a novel way to predict dynamical effects of KRas mutations, which may aid in identifying potential therapeutic targets.
UR - https://doi.org/10.1101/2020.02.28.969451
U2 - 10.1101/2020.02.28.969451
DO - 10.1101/2020.02.28.969451
M3 - Other contribution
PB - bioRxiv
ER -