Predicting the conformational variability of oncogenic GTP-bound G12D mutated KRas-4B proteins at zwitterionic model

Huixia Lu1, Jordi Martí2

  • 1School of Pharmacy, Shanghai Jiao Tong University, Shanghai, China. huixia.lu@sjtu.edu.cn.

Nanoscale
|February 10, 2022
PubMed

Insights

This study introduces a computational method to explore KRas protein variations, crucial for cancer drug discovery. The findings reveal how GTP binding influences KRas conformations, potentially enabling new therapeutic strategies.

Area of Science:

  • Computational biology
  • Biophysics
  • Molecular modeling

Background:

  • KRas proteins are key drivers in various cancers, making them important drug targets.
  • Understanding KRas conformational variability is essential for developing effective small-molecule inhibitors.
  • Existing methods struggle to fully capture the dynamic nature of Ras proteins.

Purpose of the Study:

  • To develop and validate a computational framework for accurately accessing KRas protein conformational variants.
  • To investigate the conformational landscape of oncogenic KRas-4B bound to GTP and an anionic membrane.
  • To identify potential druggable states and pathways for KRas-4B.

Main Methods:

  • Combined all-atom Molecular Dynamics (MD) and Metadynamics simulations.
  • Utilized a G12D mutated GTP-bound KRas-4B protein model interacting with a lipid membrane.
  • Employed torsional angles as reaction coordinates to generate free-energy landscapes.

Main Results:

  • Identified two primary orientations of KRas-4B at the anionic membrane.
  • Generated free-energy landscapes revealing stable and transition states between orientations.
  • Observed that GTP binding stabilizes KRas-4B and can open Switch I/II pockets.

Conclusions:

  • The computational framework accurately captures KRas conformational dynamics.
  • GTP binding significantly influences KRas stability and conformation, potentially revealing new drug targets.
  • This work offers insights into targeting KRas meta-stable states for novel cancer therapies.