Dynamics and lipid membrane coupling of the RAS-RAF complex revealed via multiscale simulations.

Journal: Biophysical journal
Published Date: Aug 22, 2025

Abstract

To gain molecular and mechanistic insights into initiation of the RAS-RAF signaling cascade, we developed and used a combination of multiscale simulation and experimental approaches. The influence and impact of the membrane on RAS and RAF proteins is a factor we are just beginning to understand and appreciate in more detail. Molecular simulation is an ideal methodology to further study this complicated relationship between the membrane and associated proteins. Our previous work using Multiscale Machine-learned Modeling Infrastructure investigated different lipid compositions solely around the KRAS4b protein and the interplay between protein behavior and these membrane environments. Multiscale Machine-learned Modeling Infrastructure uses machine learning to couple adjacent simulation scales and has been efficiently scaled across some of the world's largest high-performance computers. Recently, we have expanded this multiresolution framework to include the all-atom simulation scale and to incorporate the RAF RBDCRD domains. Here, we present the overall analysis results from this new simulation campaign comprising a mixture of RAS and RAF RBDCRD proteins. Approximately 35,000 coarse-grained and 10,000 all-atom molecular dynamics simulations were completed, sampled from a variety of protein/lipid composition configurations that were generated from a micron-scale continuum simulation containing hundreds of copies of the proteins. Our studies suggest that orientations of the RAS-RBDCRD complex on the membrane occupy distinct configurational states, and the spatial patterns of lipid arrangements around these different protein states are unique to each state. The extent and size of lipid "fingerprints" imposed on the membrane by the RAS-RBDCRD protein complex are significantly larger than observed for just the RAS protein on its own. These protein complexes strongly associate, but we do not observe statistically significant preferred protein-protein orientations. These observations indicate that spatial colocalization of RAS-RBDCRD proteins in the same vicinity may be assisted by specific membrane environments, acting to increase the probability of signaling complex formation.

Authors

  • Timothy S Carpenter
    Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Fikret Aydin
    Quantum Simulation Group, Lawrence Livermore National Laboratory, Livermore, California 94550, USA.
  • Chris Neale
    Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545.
  • Que N Van
    RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory, Frederick, MD 21701.
  • Xiaohua Zhang
    Department of Urology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, P. R. China.
  • Harsh Bhatia
    Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Jason W Sidabras
    Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI 53226.
  • Peter H Frank
    NCI RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory(,) Frederick(,) MD 21701(.).
  • Konstantia Georgouli
    Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States.
  • Jeremy O B Tempkin
    Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, California 94550, United States.
  • Violeta Burns Casamayor
    Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545.
  • Gulcin Gulten
    RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory, Frederick, MD 21701.
  • Rebika Shrestha
    RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory, Frederick, MD 21701.
  • Debanjan Goswami
    RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory, Frederick, MD 21701.
  • Francesco Di Natale
    Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Joseph R Chavez
    Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Adam Moody
    Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Joseph Y Moon
    Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Tomas Oppelstrup
    Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • James N Glosli
    Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Gautham Dharuman
    Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Sergio Wong
    Physical and Life Sciences (PLS) Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Shusen Liu
    Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Nicolas W Hengartner
    Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545.
  • Cesar A Löpez
  • Kien Nguyen
    The Speech, Audio, Image and Video Technologies (SAIVT) research group, School of Electrical Engineering & Computer Science, Queensland University of Technology, Australia.
  • Christopher B Stanley
    Computational Sciences and Engineering Division, Oak Ridge National Laboratory(,) Oak Ridge(,) TN 37830(.).
  • Liam G Stanton
    Department of Mathematics and Statistics, San José State University, San José, CA 95192.
  • Lara Patel
    Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545.
  • Tyler Reddy
    Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM 87545.
  • Thomas J Turbyville
    NCI RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory(,) Frederick(,) MD 21701(.).
  • Brian Van Essen
    Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Peer-Timo Bremer
    Computing Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
  • Felice C Lightstone
    Biochemical and Biophysical Systems Group, Biosciences and Biotechnology Division, Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California 94550, United States.
  • Andrew G Stephen
    RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory, Frederick, MD 21701.
  • Sandrasegaram Gnanakaran
    Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos, New Mexico 87545, United States.
  • Frank McCormick
    RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory, Frederick, MD 21701; [email protected] [email protected] [email protected].
  • Dwight V Nissley
    RAS Initiative, The Cancer Research Technology Program, Frederick National Laboratory, Frederick, MD 21701; [email protected] [email protected] [email protected].
  • Frederick H Streitz
    Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550; [email protected] [email protected] [email protected].
  • Helgi I Ingólfsson
    Biochemical and Biophysical Systems Group, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, United States.

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