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

  • Ngo, Van A. | Oak Ridge National Laboratory
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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

Details

DOI

10.13139/OLCF/2396898

Release date

July 26, 2024

Dataset

Dataset type

ND Numeric Data

Software

VMD, Python

Acknowledgements

Papers using this dataset are requested to include the following text in their acknowledgements:

*Support for 10.13139/OLCF/2396898 is provided by the U.S. Department of Energy, project STF006 under Contract ASCR ERKJZN1. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.

Category

  • 59 BASIC BIOLOGICAL SCIENCES

Keywords

  • Biophysics,
  • Cellular Signaling,
  • Molecular Dynamics Simulations,
  • Signalosome