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Mechanisms of membrane interaction and dimerization of K-Ras4B

Wednesday, September 16, 2015 — Poster Session I

3:30 p.m. – 5:00 p.m.
FAES Terrace
NCI
COMPBIO-11

Authors

  • H Jang
  • L Shaoyong
  • R Nussinov

Abstract

Ras is a small GTPase, controlling signal transduction pathways and promoting cell proliferation and survival. KRAS is frequently mutated in cancer. Ras consists of highly homologous catalytic domains and flexible C-terminal hypervariable regions (HVRs) that differ significantly across Ras isoforms. Recent NMR and MD simulations discovered that the HVR of K-Ras4B-GDP extensively interacts with the catalytic domain. However, it weakly interacts with the catalytic domain in the GTP-bound state. Here, using MD simulations we modeled K-Ras4B membrane interaction and dimerization. On the membrane, the catalytic domain takes on multiple orientations, including perpendicular and parallel alignments of the allosteric helices with respect to the membrane normal. In the autoinhibited state, the HVR is sandwiched between the effector lobe and the membrane; in the active state, with the farnesyl anchored into the membrane and the HVR unrestrained, the catalytic domain fluctuates reinlessly, exposing its effector binding site. Notably, we also observe HVR-autoinhibited K-Ras4B-GTP states that display GDP-bound-like orientations of the helices. We thus propose that GDP/GTP nucleotide exchange may not be sufficient for K-Ras4B activation; composite mechanisms including HVR sequestration, farnesyl insertion, and orientation/localization of the catalytic domain on the membrane can determine the functional state of K-Ras4B. Remarkably, K-Ras4B-GTP, but not GDP-bound, is able to form stable homodimers with different dimer interfaces, suggesting that the nucleotide-dependent dimerization with various dimer interfaces can resolve nanoclustering and cluster reorganization accomplishment with Raf’s activation. Dimerization and clustering could rein the fluctuations producing more productive pre-organized conformations.

Category: Computational Biology