Insight into Molecular Basis and Dynamics of Full-length CRaf Kinase in Cellular Signaling Mechanism

Ngo, Van A. | Oak Ridge National Laboratory

Overview

Description

This study presents the first large-scale simulation using an initial structure predicted by AI/ML algorithms for the 648-amino-acid CRaf kinase, which plays a key role in cellular signaling. Simulation results show the evolution of the predicted structure into much more compact structures with inter-domain interactions that shed insights into auto-inhibition mechanism, paradoxical effect, activation, and recruitment pathways in the CRaf kinase. Newly identified epitopes in the CRaf may suggest additional drug targets. The results were published in Biophysical Journal, DOI:10.1016/j.bpj.2024.06.028.

Funding resources

DOE contract number

ASCR ERKJZN1

Originating research organization

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring organization

Office of Science (SC);Office of Scienc (SC), Advanced Scientific Computing Research (ASCR) (SC-21)

Related resources

IsSupplementTo (DOI): https://doi.org/10.1016/j.bpj.2024.06.028

Details

DOI

10.13139/OLCF/2396898

Release date

July 26, 2024

Dataset

Dataset type

ND Numeric Data

Software

VMD, Python

Acknowledgements

Users should acknowledge the OLCF in all publications and presentations that speak to work performed on OLCF resources:

This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725.

Keywords

Biophysics,
Cellular Signaling,
Molecular Dynamics Simulations,
Signalosome