FLIM-FRET Protein-Protein Interaction Assay.

Fluorescence lifetime imaging performed under FRET conditions between two interacting molecules is a sensitive and robust way to quantify intermolecular interactions in cells. The fluorescence lifetime, an inherent property of the fluorophore, remains unaffected by factors such as concentration, laser intensity, and other photophysical artifacts. In the context of FLIM-FRET, the focus lies on measuring the fluorescence lifetime of the donor molecule, which diminishes upon interaction with a neighboring acceptor molecule. In this study, we present a step-by-step experimental protocol for applying FLIM-FRET to investigate protein-protein interactions involving various RAS isoforms and RAS effectors at the live cell's plasma membrane. By utilizing the FRET pair comprising enhanced green fluorescent protein (eGFP) and fluorescent mCherry, we demonstrate that the proximity and possible nanoclustering of eGFP-tagged KRAS4b G12D and mCherry-tagged KRAS4b WT led to a reduction in the donor eGFP's fluorescence lifetime. The donor lifetime of eGFP-tagged KRAS decreases even further when treated with a dimer-inducing small molecule, or in the presence of RAF proteins, suggesting a greater FRET efficiency, and thus less distance, between donor and acceptor.

Membrane lipids drive formation of KRAS4b-RAF1 RBDCRD nanoclusters on the membrane.

The oncogene RAS, extensively studied for decades, presents persistent gaps in understanding, hindering the development of effective therapeutic strategies due to a lack of precise details on how RAS initiates MAPK signaling with RAF effector proteins at the plasma membrane. Recent advances in X-ray crystallography, cryo-EM, and super-resolution fluorescence microscopy offer structural and spatial insights, yet the molecular mechanisms involving protein-protein and protein-lipid interactions in RAS-mediated signaling require further characterization. This study utilizes single-molecule experimental techniques, nuclear magnetic resonance spectroscopy, and the computational Machine-Learned Modeling Infrastructure (MuMMI) to examine KRAS4b and RAF1 on a biologically relevant lipid bilayer. MuMMI captures long-timescale events while preserving detailed atomic descriptions, providing testable models for experimental validation. Both in vitro and computational studies reveal that RBDCRD binding alters KRAS lateral diffusion on the lipid bilayer, increasing cluster size and decreasing diffusion. RAS and membrane binding cause hydrophobic residues in the CRD region to penetrate the bilayer, stabilizing complexes through ß-strand elongation. These cooperative interactions among lipids, KRAS4b, and RAF1 are proposed as essential for forming nanoclusters, potentially a critical step in MAP kinase signal activation.

Direct Modulators of K-Ras-Membrane Interactions.

Protein-membrane interactions (PMIs) are ubiquitous in cellular signaling. Initial steps of signal transduction cascades often rely on transient and dynamic interactions with the inner plasma membrane leaflet to populate and regulate signaling hotspots. Methods to target and modulate these interactions could yield attractive tool compounds and drug candidates. Here, we demonstrate that the conjugation of a medium-chain lipid tail to the covalent K-Ras(G12C) binder MRTX849 at a solvent-exposed site enables such direct modulation of PMIs. The conjugated lipid tail interacts with the tethered membrane and changes the relative membrane orientation and conformation of K-Ras(G12C), as shown by molecular dynamics (MD) simulation-supported NMR studies. In cells, this PMI modulation restricts the lateral mobility of K-Ras(G12C) and disrupts nanoclusters. The described strategy could be broadly applicable to selectively modulate transient PMIs.

Machine Learning-Driven Multiscale Modeling: Bridging the Scales with a Next-Generation Simulation Infrastructure.

Interdependence across time and length scales is common in biology, where atomic interactions can impact larger-scale phenomenon. Such dependence is especially true for a well-known cancer signaling pathway, where the membrane-bound RAS protein binds an effector protein called RAF. To capture the driving forces that bring RAS and RAF (represented as two domains, RBD and CRD) together on the plasma membrane, simulations with the ability to calculate atomic detail while having long time and large length- scales are needed. The Multiscale Machine-Learned Modeling Infrastructure (MuMMI) is able to resolve RAS/RAF protein-membrane interactions that identify specific lipid-protein fingerprints that enhance protein orientations viable for effector binding. MuMMI is a fully automated, ensemble-based multiscale approach connecting three resolution scales: (1) the coarsest scale is a continuum model able to simulate milliseconds of time for a 1 µm2 membrane, (2) the middle scale is a coarse-grained (CG) Martini bead model to explore protein-lipid interactions, and (3) the finest scale is an all-atom (AA) model capturing specific interactions between lipids and proteins. MuMMI dynamically couples adjacent scales in a pairwise manner using machine learning (ML). The dynamic coupling allows for better sampling of the refined scale from the adjacent coarse scale (forward) and on-the-fly feedback to improve the fidelity of the coarser scale from the adjacent refined scale (backward). MuMMI operates efficiently at any scale, from a few compute nodes to the largest supercomputers in the world, and is generalizable to simulate different systems. As computing resources continue to increase and multiscale methods continue to advance, fully automated multiscale simulations (like MuMMI) will be commonly used to address complex science questions.

Exploring CRD mobility during RAS/RAF engagement at the membrane.

During the activation of mitogen-activated protein kinase (MAPK) signaling, the RAS-binding domain (RBD) and cysteine-rich domain (CRD) of RAF bind to active RAS at the plasma membrane. The orientation of RAS at the membrane may be critical for formation of the RAS-RBDCRD complex and subsequent signaling. To explore how RAS membrane orientation relates to the protein dynamics within the RAS-RBDCRD complex, we perform multiscale coarse-grained and all-atom molecular dynamics (MD) simulations of KRAS4b bound to the RBD and CRD domains of RAF-1, both in solution and anchored to a model plasma membrane. Solution MD simulations describe dynamic KRAS4b-CRD conformations, suggesting that the CRD has sufficient flexibility in this environment to substantially change its binding interface with KRAS4b. In contrast, when the ternary complex is anchored to the membrane, the mobility of the CRD relative to KRAS4b is restricted, resulting in fewer distinct KRAS4b-CRD conformations. These simulations implicate membrane orientations of the ternary complex that are consistent with NMR measurements. While a crystal structure-like conformation is observed in both solution and membrane simulations, a particular intermolecular rearrangement of the ternary complex is observed only when it is anchored to the membrane. This configuration emerges when the CRD hydrophobic loops are inserted into the membrane and helices α3-5 of KRAS4b are solvent exposed. This membrane-specific configuration is stabilized by KRAS4b-CRD contacts that are not observed in the crystal structure. These results suggest modulatory interplay between the CRD and plasma membrane that correlate with RAS/RAF complex structure and dynamics, and potentially influence subsequent steps in the activation of MAPK signaling.

Asynchronous Reciprocal Coupling of Martini 2.2 Coarse-Grained and CHARMM36 All-Atom Simulations in an Automated Multiscale Framework.

The appeal of multiscale modeling approaches is predicated on the promise of combinatorial synergy. However, this promise can only be realized when distinct scales are combined with reciprocal consistency. Here, we consider multiscale molecular dynamics (MD) simulations that combine the accuracy and macromolecular flexibility accessible to fixed-charge all-atom (AA) representations with the sampling speed accessible to reductive, coarse-grained (CG) representations. AA-to-CG conversions are relatively straightforward because deterministic routines with unique outcomes are achievable. Conversely, CG-to-AA conversions have many solutions due to a surge in the number of degrees of freedom. While automated tools for biomolecular CG-to-AA transformation exist, we find that one popular option, called Backward, is prone to stochastic failure and the AA models that it does generate frequently have compromised protein structure and incorrect stereochemistry. Although these shortcomings can likely be circumvented by human intervention in isolated instances, automated multiscale coupling requires reliable and robust scale conversion. Here, we detail an extension to Multiscale Machine-learned Modeling Infrastructure (MuMMI), including an improved CG-to-AA conversion tool called sinceCG. This tool is reliable (∼98% weakly correlated repeat success rate), automatable (no unrecoverable hangs), and yields AA models that generally preserve protein secondary structure and maintain correct stereochemistry. We describe how the MuMMI framework identifies CG system configurations of interest, converts them to AA representations, and simulates them at the AA scale while on-the-fly analyses provide feedback to update CG parameters. Application to systems containing the peripheral membrane protein RAS and proximal components of RAF kinase on complex eight-component lipid bilayers with ∼1.5 million atoms is discussed in the context of MuMMI.

Recapitulation of cell-like KRAS4b membrane dynamics on complex biomimetic membranes.

Understanding the spatiotemporal distribution and dynamics of RAS on the plasma membrane (PM) is the key for elucidating the molecular mechanisms of the RAS signaling pathway. Single particle tracking (SPT) experiments show that in cells, KRAS diffuses in at least three interchanging states on the cellular PM; however, KRAS remains monomeric and always shows homogeneous diffusion on artificial membranes. Here, we show for the first time on a supported lipid bilayer composed of heterogeneous lipid components that we can recapitulate the three-state diffusion of KRAS seen in cells. The use of a biologically relevant eight-lipid system opens a new frontier in the biophysical studies of RAS and other membrane associated proteins on a biomimetic system that recapitulates the complexity of a cellular PM.

Machine learning-driven multiscale modeling reveals lipid-dependent dynamics of RAS signaling proteins.

RAS is a signaling protein associated with the cell membrane that is mutated in up to 30% of human cancers. RAS signaling has been proposed to be regulated by dynamic heterogeneity of the cell membrane. Investigating such a mechanism requires near-atomistic detail at macroscopic temporal and spatial scales, which is not possible with conventional computational or experimental techniques. We demonstrate here a multiscale simulation infrastructure that uses machine learning to create a scale-bridging ensemble of over 100,000 simulations of active wild-type KRAS on a complex, asymmetric membrane. Initialized and validated with experimental data (including a new structure of active wild-type KRAS), these simulations represent a substantial advance in the ability to characterize RAS-membrane biology. We report distinctive patterns of local lipid composition that correlate with interfacially promiscuous RAS multimerization. These lipid fingerprints are coupled to RAS dynamics, predicted to influence effector binding, and therefore may be a mechanism for regulating cell signaling cascades.

RAS Nanoclusters: Dynamic Signaling Platforms Amenable to Therapeutic Intervention.

RAS proteins are mutated in approximately 20% of all cancers and are generally associated with poor clinical outcomes. RAS proteins are localized to the plasma membrane and function as molecular switches, turned on by partners that receive extracellular mitogenic signals. In the on-state, they activate intracellular signal transduction cascades. Membrane-bound RAS molecules segregate into multimers, known as nanoclusters. These nanoclusters, held together through weak protein-protein and protein-lipid associations, are highly dynamic and respond to cellular input signals and fluctuations in the local lipid environment. Disruption of RAS nanoclusters results in downregulation of RAS-mediated mitogenic signaling. In this review, we discuss the propensity of RAS proteins to display clustering behavior and the interfaces that are associated with these assemblies. Strategies to therapeutically disrupt nanocluster formation or the stabilization of signaling incompetent RAS complexes are discussed.

Direct Measurement of the Effect of Cholesterol and 6-Ketocholestanol on the Membrane Dipole Electric Field Using Vibrational Stark Effect Spectroscopy Coupled with Molecular Dynamics Simulations.

Biological membranes are heterogeneous structures with complex electrostatic profiles arising from lipids, sterols, membrane proteins, and water molecules. We investigated the effect of cholesterol and its derivative 6-ketocholestanol (6-kc) on membrane electrostatics by directly measuring the dipole electric field (F⃗d) within lipid bilayers containing cholesterol or 6-kc at concentrations of 0-40 mol% through the vibrational Stark effect (VSE). We found that adding low concentrations of cholesterol, up to ∼10 mol %, increases F⃗d, while adding more cholesterol up to 40 mol% lowers F⃗d. In contrast, we measured a monotonic increase in F⃗d as 6-kc concentration increased. We propose that this membrane electric field is affected by multiple factors: the polarity of the sterol molecules, the reorientation of the phospholipid dipole due to sterol, and the impact of the sterol on hydrogen bonding with surface water. We used molecular dynamics simulations to examine the distribution of phospholipids, sterol, and helix in bilayers containing these sterols. At low concentrations, we observed clustering of sterols near the vibrational probe whereas at high concentrations, we observed spatial correlation between the positions of the sterol molecules. This work demonstrates how a one-atom difference in a sterol changes the physicochemical and electric field properties of the bilayer.

Membrane permeation of a peptide: it is better to be positive.

A joint experimental and computational study investigates the translocation of a tryptophan molecule through a phospholipid membrane. Time dependent spectroscopy of the tryptophan side chain determines the rate of permeation into 150 nm phospholipid vesicles. Atomically detailed simulations are conducted to calculate the free energy profiles and the permeation coefficient. Different charging conditions of the peptide (positive, negative, or zwitterion) are considered. Both experiment and simulation reproduce the qualitative trend and suggest that the fastest permeation is when the tryptophan is positively charged. The permeation mechanism, which is revealed by molecular dynamics simulations, is of a translocation assisted by a local defect. The influence of long-range electrostatic interactions, such as the membrane dipole potential on the permeation process, is not significant.

Measurement of the membrane dipole electric field in DMPC vesicles using vibrational shifts of p-cyanophenylalanine and molecular dynamics simulations.

The magnitude of the membrane dipole field was measured using vibrational Stark effect (VSE) shifts of nitrile oscillators placed on the unnatural amino acid p-cyanophenylalanine (p-CN-Phe) added to a peptide sequence at four unique positions. These peptides, which were based on a repeating alanine-leucine motif, intercalated into small unilamellar DMPC vesicles which formed an α-helix as confirmed by circular dichroic (CD) spectroscopy. Molecular dynamics simulations of the membrane-intercalated helix containing two of the nitrile probes, one near the headgroup region of the lipid (αLAX(25)) and one buried in the interior of the bilayer (αLAX(16)), were used to examine the structure of the nitrile with respect to the membrane normal, the assumed direction of the dipole field, by quantifying both a small tilt of the helix in the bilayer and conformational rotation of the p-CN-Phe side chain at steady state. Vibrational absorption energies of the nitrile oscillator at each position showed a systematic blue shift as the nitrile was stepped toward the membrane interior; for several different concentrations of peptide, the absorption energy of the nitrile located in the middle of the bilayer was ∼3 cm(-1) greater than that of the nitrile closest to the surface of the membrane. Taken together, the measured VSE shifts and nitrile orientations within the membrane resulted in an absolute magnitude of 8-11 MV/cm for the dipole field, at the high end of the range of possible values that have been accumulated from a variety of indirect measurements. Implications for this are discussed.