Machine learning-driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins
Helgi I Ingólfsson1, Chris Neale2, Timothy S Carpenter1
1Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory, Livermore, CA 94550.
Summary
RAS proteins, mutated in many cancers, may be regulated by cell membrane dynamics. New multiscale simulations reveal lipid patterns influencing RAS signaling and potential cancer drug targets.
Area of Science:
- Computational biology
- Biophysics
- Molecular dynamics
Background:
- RAS proteins are key regulators of cell signaling, frequently mutated in human cancers.
- Cell membrane heterogeneity is hypothesized to regulate RAS signaling dynamics.
- Conventional methods lack the scale to investigate RAS-membrane interactions.
Purpose of the Study:
- To develop and utilize a multiscale simulation infrastructure for studying RAS-membrane interactions.
- To characterize the relationship between lipid composition and RAS protein behavior.
- To identify potential mechanisms regulating RAS signaling.
Main Methods:
- Developed a multiscale simulation infrastructure integrating machine learning for scale-bridging.
- Executed over 100,000 simulations of active wild-type KRAS on a complex membrane.
- Initialized and validated simulations with experimental data, including a novel KRAS structure.
Main Results:
- Identified distinctive local lipid composition patterns correlated with RAS multimerization.
- Demonstrated coupling between lipid fingerprints and RAS protein dynamics.
- Predicted that these lipid-mediated effects influence RAS effector binding.
Conclusions:
- RAS-membrane interactions are influenced by specific lipid microenvironments.
- Lipid composition patterns act as 'fingerprints' regulating RAS dynamics and signaling.
- This provides a novel mechanism for controlling cell signaling cascades and offers potential therapeutic targets.
Keywords:
RAS dynamicsRAS-membrane biologymassive parallel simulationsmultiscale infrastructuremultiscale modelingMore Related Videos
Related Concept Videos
02:38The Ras Gene
6.5K
The Ras-gene-encoded proteins are regulators of signaling pathways controlling cell proliferation, differentiation, or cell survival. The Ras-gene family in humans constitutes three primary members—the HRas, NRas, and KRas. These genes code for four functionally distinct yet closely related proteins—the HRas, NRas, KRas4A, and KRas4B. The involvement of mutant Ras genes in human cancer was first discovered in 1982 and is among the most common causes of human tumorigenesis.
Ras is a...
Ras is a...
6.5K
01:24Small GTPases - Ras and Rho
4.3K
Ras and Rho are small monomeric GTPases that act downstream of receptor tyrosine kinase (RTK) and regulate various cellular processes. These GTPases switch between active and inactive states by binding to guanine nucleotides.
Three regulatory proteins control their activity:
Three regulatory proteins control their activity:
4.3K
01:07MAPK Signaling Cascades
6.4K
Mitogen-activated protein kinase, or MAPK pathway, activates three sequential kinases to regulate cellular responses such as proliferation, differentiation, survival, and apoptosis. The canonical MAPK pathway starts with a mitogen or growth factor binding to an RTK. The activated RTKs stimulate Ras, which recruits Raf or MAP3 Kinase (MAPKKK), the first kinase of the MAPK signaling cascade. Raf further phosphorylates and activates MEK or MAP2 Kinases (MAPKK), which in turn phosphorylates MAP...
6.4K
01:30Assembly of Signaling Complexes
6.0K
Multiprotein signaling complexes are formed in a dynamic process involving protein-protein interactions at the cytoplasmic domain of transmembrane receptors or enzymatic and non-enzymatic proteins associated with the receptor. These complexes ensure the activation and propagation of intracellular signals that regulate cell functions.
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
Interaction domains in cell signaling
Interaction domains recognize exposed features of their binding partners containing post-translationally modified sequences,...
6.0K
01:19Interactions Between Signaling Pathways
6.6K
Signaling cascades usually lack linearity. Multiple pathways interact and regulate one another, allowing cells to integrate and respond to diverse environmental stimuli.
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
Convergence and divergence, and cross-talk between signaling pathways
Two distinct signaling pathways can converge on a single functional unit, which may either be a single protein or a complex of proteins. The response is either functionally distinct or synergistic between the two pathways but different from the response...
6.6K
01:19Fluid Mosaic Model
13.6K
Scientists identified the plasma membrane in the 1890s and its principal chemical components (lipids and proteins) by 1915. The model for plasma membrane structure, proposed in 1935 by Hugh Davson and James Danielli, was the first model to be widely accepted in the scientific community. The model was based on the plasma membrane's "railroad track" appearance in early electron micrographs. Davson and Danielli theorized that the plasma membrane's structure resembled a sandwich...
13.6K