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.

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.

The Plasma Membrane as a Competitive Inhibitor and Positive Allosteric Modulator of KRas4B Signaling.

Mutant Ras proteins are important drivers of human cancers, yet no approved drugs act directly on this difficult target. Over the last decade, the idea has emerged that oncogenic signaling can be diminished by molecules that drive Ras into orientations in which effector-binding interfaces are occluded by the cell membrane. To support this approach to drug discovery, we characterize the orientational preferences of membrane-bound K-Ras4B in 1.45-ms aggregate time of atomistic molecular dynamics simulations. Individual simulations probe active or inactive states of Ras on membranes with or without anionic lipids. We find that the membrane orientation of Ras is relatively insensitive to its bound guanine nucleotide and activation state but depends strongly on interactions with anionic phosphatidylserine lipids. These lipids slow Ras' translational and orientational diffusion and promote a discrete population in which small changes in orientation control Ras' competence to bind multiple regulator and effector proteins. Our results suggest that compound-directed conversion of constitutively active mutant Ras into functionally inactive forms may be accessible via subtle perturbations of Ras' orientational preferences at the membrane surface.

Molecular recognition and packing frustration in a helical protein.

Biomolecular recognition entails attractive forces for the functional native states and discrimination against potential nonnative interactions that favor alternate stable configurations. The challenge posed by the competition of nonnative stabilization against native-centric forces is conceptualized as frustration. Experiment indicates that frustration is often minimal in evolved biological systems although nonnative possibilities are intuitively abundant. Much of the physical basis of minimal frustration in protein folding thus remains to be elucidated. Here we make progress by studying the colicin immunity protein Im9. To assess the energetic favorability of nonnative versus native interactions, we compute free energies of association of various combinations of the four helices in Im9 (referred to as H1, H2, H3, and H4) by extensive explicit-water molecular dynamics simulations (total simulated time > 300 µs), focusing primarily on the pairs with the largest native contact surfaces, H1-H2 and H1-H4. Frustration is detected in H1-H2 packing in that a nonnative packing orientation is significantly stabilized relative to native, whereas such a prominent nonnative effect is not observed for H1-H4 packing. However, in contrast to the favored nonnative H1-H2 packing in isolation, the native H1-H2 packing orientation is stabilized by H3 and loop residues surrounding H4. Taken together, these results showcase the contextual nature of molecular recognition, and suggest further that nonnative effects in H1-H2 packing may be largely avoided by the experimentally inferred Im9 folding transition state with native packing most developed at the H1-H4 rather than the H1-H2 interface.

Sampling errors in free energy simulations of small molecules in lipid bilayers.

Free energy simulations are a powerful tool for evaluating the interactions of molecular solutes with lipid bilayers as mimetics of cellular membranes. However, these simulations are frequently hindered by systematic sampling errors. This review highlights recent progress in computing free energy profiles for inserting molecular solutes into lipid bilayers. Particular emphasis is placed on a systematic analysis of the free energy profiles, identifying the sources of sampling errors that reduce computational efficiency, and highlighting methodological advances that may alleviate sampling deficiencies. This article is part of a Special Issue entitled: Biosimulations edited by Ilpo Vattulainen and Tomasz Róg.

The Aging Urban Brain: Analyzing Outdoor Physical Activity Using the Emotiv Affectiv Suite in Older People.

This research directly assesses older people's neural activation in response to a changing urban environment while walking, as measured by electroencephalography (EEG). The study builds on previous research that shows changes in cortical activity while moving through different urban settings. The current study extends this methodology to explore previously unstudied outcomes in older people aged 65 years or more (n = 95). Participants were recruited to walk one of six scenarios pairing urban busy (a commercial street with traffic), urban quiet (a residential street) and urban green (a public park) spaces in a counterbalanced design, wearing a mobile Emotiv EEG headset to record real-time neural responses to place. Each walk lasted around 15 min and was undertaken at the pace of the participant. We report on the outputs for these responses derived from the Emotiv Affectiv Suite software, which creates emotional parameters ('excitement', 'frustration', 'engagement' and 'meditation') with a real-time value assigned to them. The six walking scenarios were compared using a form of high dimensional correlated component regression (CCR) on difference data, capturing the change between one setting and another. The results showed that levels of 'engagement' were higher in the urban green space compared to those of the urban busy and urban quiet spaces, whereas levels of 'excitement' were higher in the urban busy environment compared with those of the urban green space and quiet urban space. In both cases, this effect is shown regardless of the order of exposure to these different environments. These results suggest that there are neural signatures associated with the experience of different urban spaces which may reflect the older age of the sample as well as the condition of the spaces themselves. The urban green space appears to have a restorative effect on this group of older adults.

Correction to: The Aging Urban Brain: Analyzing Outdoor Physical Activity Using the Emotiv Affectiv Suite in Older People.

Please note that the legend to Fig. 1 has been modified since this article was originally published, and also that in Tables 2, 3 and 4, R[2] was corrected to (the now correct) R squared.

Hydrophobic Gating of Ion Permeation in Magnesium Channel CorA.

Ion channels catalyze ionic permeation across membranes via water-filled pores. To understand how changes in intracellular magnesium concentration regulate the influx of Mg2+ into cells, we examine early events in the relaxation of Mg2+ channel CorA toward its open state using massively-repeated molecular dynamics simulations conducted either with or without regulatory ions. The pore of CorA contains a 2-nm-long hydrophobic bottleneck which remained dehydrated in most simulations. However, rapid hydration or "wetting" events concurrent with small-amplitude fluctuations in pore diameter occurred spontaneously and reversibly. In the absence of regulatory ions, wetting transitions are more likely and include a wet state that is significantly more stable and more hydrated. The free energy profile for Mg2+ permeation presents a barrier whose magnitude is anticorrelated to pore diameter and the extent of hydrophobic hydration. These findings support an allosteric mechanism whereby wetting of a hydrophobic gate couples changes in intracellular magnesium concentration to the onset of ionic conduction.

Can Specific Protein-Lipid Interactions Stabilize an Active State of the Beta 2 Adrenergic Receptor?

G-protein-coupled receptors are eukaryotic membrane proteins with broad biological and pharmacological relevance. Like all membrane-embedded proteins, their location and orientation are influenced by lipids, which can also impact protein function via specific interactions. Extensive simulations totaling 0.25 ms reveal a process in which phospholipids from the membrane's cytosolic leaflet enter the empty G-protein binding site of an activated ß2 adrenergic receptor and form salt-bridge interactions that inhibit ionic lock formation and prolong active-state residency. Simulations of the receptor embedded in an anionic membrane show increased lipid binding, providing a molecular mechanism for the experimental observation that anionic lipids can enhance receptor activity. Conservation of the arginine component of the ionic lock among Rhodopsin-like G-protein-coupled receptors suggests that intracellular lipid ingression between receptor helices H6 and H7 may be a general mechanism for active-state stabilization.

Indolicidin binding induces thinning of a lipid bilayer.

We use all-atom molecular dynamics simulations on a massive scale to compute the standard binding free energy of the 13-residue antimicrobial peptide indolicidin to a lipid bilayer. The analysis of statistical convergence reveals systematic sampling errors that correlate with reorganization of the bilayer on the microsecond timescale and persist throughout a total of 1.4 ms of sampling. Consistent with experimental observations, indolicidin induces membrane thinning, although the simulations significantly overestimate the lipophilicity of the peptide.

Characterization of disordered proteins with ENSEMBLE.

UNLABELLED: ENSEMBLE is a computational approach for determining a set of conformations that represents the structural ensemble of a disordered protein based on input experimental data. The disordered protein can be an unfolded or intrinsically disordered state. Here, we introduce the latest version of the program, which has been enhanced to facilitate its general release and includes an intuitive user interface, as well as new approaches to treat data and analyse results. AVAILABILITY AND IMPLEMENTATION: ENSEMBLE is a program implemented in C and embedded in a Perl wrapper. It is supported on main Linux distributions. Source codes and installation files, including a detailed example, can be freely downloaded at http://abragam.med.utoronto.ca/∼JFKlab.

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.

Cognitive effects of two nutraceuticals Ginseng and Bacopa benchmarked against modafinil: a review and comparison of effect sizes.

Over recent years there has been increasing research into both pharmaceutical and nutraceutical cognition enhancers. Here we aimed to calculate the effect sizes of positive cognitive effect of the pharmaceutical modafinil in order to benchmark the effect of two widely used nutraceuticals Ginseng and Bacopa (which have consistent acute and chronic cognitive effects, respectively). A search strategy was implemented to capture clinical studies into the neurocognitive effects of modafinil, Ginseng and Bacopa. Studies undertaken on healthy human subjects using a double-blind, placebo-controlled design were included. For each study where appropriate data were included, effect sizes (Cohen's d) were calculated for measures showing significant positive and negative effects of treatment over placebo. The highest effect sizes for cognitive outcomes were 0.77 for modafinil (visuospatial memory accuracy), 0.86 for Ginseng (simple reaction time) and 0.95 for Bacopa (delayed word recall). These data confirm that neurocognitive enhancement from well characterized nutraceuticals can produce cognition enhancing effects of similar magnitude to those from pharmaceutical interventions. Future research should compare these effects directly in clinical trials.

Intermediate-state-trapped mutants pinpoint G protein-coupled receptor conformational allostery.

Understanding the roles of intermediate states in signaling is pivotal to unraveling the activation processes of G protein-coupled receptors (GPCRs). However, the field is still struggling to define these conformational states with sufficient resolution to study their individual functions. Here, we demonstrate the feasibility of enriching the populations of discrete states via conformation-biased mutants. These mutants adopt distinct distributions among five states that lie along the activation pathway of adenosine A2A receptor (A2AR), a class A GPCR. Our study reveals a structurally conserved cation-π lock between transmembrane helix VI (TM6) and Helix8 that regulates cytoplasmic cavity opening as a "gatekeeper" for G protein penetration. A GPCR activation process based on the well-discerned conformational states is thus proposed, allosterically micro-modulated by the cation-π lock and a previously well-defined ionic interaction between TM3 and TM6. Intermediate-state-trapped mutants will also provide useful information in relation to receptor-G protein signal transduction.

GAP positions catalytic H-Ras residue Q61 for GTP hydrolysis in molecular dynamics simulations, complicating chemical rescue of Ras deactivation.

Functional interaction of Ras signaling proteins with upstream, negative regulatory GTPase activating proteins (GAPs) represents a crucial step in cellular decision making related to growth and survival. Key components of the catalytic transition state for Ras deactivation by GAP-accelerated hydrolysis of Ras-bound guanosine triphosphate (GTP) are thought to include an arginine residue from the GAP (the arginine finger), a glutamine residue from Ras (Q61), and a water molecule that is likely coordinated by Q61 to engage in nucleophilic attack on GTP. Here, we use in-vitro fluorescence experiments to show that 0.1-100 mM concentrations of free arginine, imidazole, and other small nitrogenous molecule fail to accelerate GTP hydrolysis, even in the presence of the catalytic domain of a mutant GAP lacking its arginine finger (R1276A NF1). This result is surprising given that imidazole can chemically rescue enzyme activity in arginine-to-alanine mutant protein tyrosine kinases (PTKs) that share many active site components with Ras/GAP complexes. Complementary all-atom molecular dynamics (MD) simulations reveal that an arginine finger GAP mutant still functions to enhance Ras Q61-GTP interaction, though less extensively than wild-type GAP. This increased Q61-GTP proximity may promote more frequent fluctuations into configurations that enable GTP hydrolysis as a component of the mechanism by which GAPs accelerate Ras deactivation in the face of arginine finger mutations. The failure of small molecule analogs of arginine to chemically rescue catalytic deactivation of Ras is consistent with the idea that the influence of the GAP goes beyond the simple provision of its arginine finger. However, the failure of chemical rescue in the presence of R1276A NF1 suggests that the GAPs arginine finger is either unsusceptible to rescue due to exquisite positioning or that it is involved in complex multivalent interactions. Therefore, in the context of oncogenic Ras proteins with mutations at codons 12 or 13 that inhibit arginine finger penetration toward GTP, drug-based chemical rescue of GTP hydrolysis may have bifunctional chemical/geometric requirements that are more difficult to satisfy than those that result from arginine-to-alanine mutations in other enzymes for which chemical rescue has been demonstrated.

Monatomic ions influence substrate permeation across bacterial microcompartment shells.

Bacterial microcompartments (BMCs) are protein organelles consisting of an inner enzymatic core encased within a selectively permeable shell. BMC shells are modular, tractable architectures that can be repurposed with new interior enzymes for biomanufacturing purposes. The permeability of BMC shells is function-specific and regulated by biophysical properties of the shell subunits, especially its pores. We hypothesized that ions may interact with pore residues in a manner that influences the substrate permeation process. In vitro activity comparisons between native and broken BMCs demonstrated that increasing NaCl negatively affects permeation rates. Molecular dynamics simulations of the dominant shell protein (BMC-H) revealed that chloride ions preferentially occupy the positive pore, hindering substrate permeation, while sodium cations remain excluded. Overall, these results demonstrate that shell properties influence ion permeability and leverages the integration of experimental and computational techniques to improve our understanding of BMC shells towards their repurposing for biotechnological applications.

Computational approaches to the rational design of nanoemulsions, polymeric micelles, and dendrimers for drug delivery.

Nanoparticles are promising drug delivery systems whose selection and optimization can be gainfully conducted by theoretical methods. This review is targeted to experimentalists who are interested in enhancing their time and cost efficiency through the incorporation of theoretical approaches. This review thus begins with a brief overview of theoretical approaches available to the development of contemporary drug delivery systems. Approaches include solubility parameters, Flory-Huggins theory, analytical predictions of partition coefficients, and molecular simulations. These methods are then compared as they relate to the optimization of drug-material pairs using important performance-related parameters including the size of the delivery particles, their surface properties, and the compatibility of the materials with the drug to be sequestered. Next, this review explores contemporary efforts to optimize a selection of existing nanoparticle platforms, including nanoemulsions, linear and star-shaped block co-polymer micelles, and dendrimers. The review concludes with an outlook on the challenges remaining in the successful application of these theoretical methods to the development of new drug formulations. FROM THE CLINICAL EDITOR: This paper is a comprehensive review of the many approaches available to assist the optimization of nanoparticle drug delivery vehicles, including a detailed discussion of methodological applicability, a survey of contemporary efforts to optimize a selection of frequently used nanoparticle subtypes.

Drug Discovery by Automated Adaptation of Chemical Structure and Identity.

Computer-aided drug design offers the potential to dramatically reduce the cost and effort required for drug discovery. While screening-based methods are valuable in the early stages of hit identification, they are frequently succeeded by iterative, hypothesis-driven computations that require recurrent investment of human time and intuition. To increase automation, we introduce a computational method for lead refinement that combines concerted dynamics of the ligand/protein complex via molecular dynamics simulations with integrated Monte Carlo-based changes in the chemical formula of the ligand. This approach, which we refer to as ligand-exchange Monte Carlo molecular dynamics, accounts for solvent- and entropy-based contributions to competitive binding free energies by coupling the energetics of bound and unbound states during the ligand-exchange attempt. Quantitative comparison of relative binding free energies to reference values from free energy perturbation, conducted in vacuum, indicates that ligand-exchange Monte Carlo molecular dynamics simulations sample relevant conformational ensembles and are capable of identifying strongly binding compounds. Additional simulations demonstrate the use of an implicit solvent model. We speculate that the use of chemical graphs in which exchanges are only permitted between ligands with sufficient similarity may enable an automated search to capture some of the benefits provided by human intuition during hypothesis-guided lead refinement.

Corrigendum: Assessing Inequalities in Wellbeing at a Neighbourhood Scale in Low-Middle-Income-Country Secondary Cities and Their Implications for Long-Term Livability.

[This corrects the article DOI: 10.3389/fsoc.2021.729453.].

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.