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A fundamental understanding of how the HIV-1 envelope (Env) protein facilitates fusion is still lacking. The HIV-1 fusion peptide, consisting of 15 to 22 residues, is the N-terminus of the gp41 subunit of the Env protein. Further, this peptide, a promising vaccine candidate, initiates viral entry into target cells by inserting and anchoring into human immune cells. The influence of membrane lipid reorganization and the conformational changes of the fusion peptide during the membrane insertion and anchoring processes, which can significantly affect HIV-1 cell entry, remains largely unexplored due to the limitations of experimental measurements. In this work, we investigate the insertion of the fusion peptide into an immune cell membrane mimic through multiscale molecular dynamics simulations. We mimic the native T-cell by constructing a nine-lipid asymmetric membrane, along with geometrical restraints accounting for insertion in the context of gp41. To account for the slow time scale of lipid mixing while enabling conformational changes, we implement a protocol to go back and forth between atomistic and coarse-grained simulations. Our study provides a molecular understanding of the interactions between the HIV-1 fusion peptide and the T-cell membrane, highlighting the importance of the conformational flexibility of fusion peptides and local lipid reorganization in stabilizing the anchoring of gp41 into the targeted host membrane during the early events of HIV-1 cell entry. Importantly, we identify a motif within the fusion peptide critical for fusion that can be further manipulated in future immunological studies.

AbstractUsing a Plan-Do-Study-Act (PDSA) methodology, we describe our first cycle of a project using an ice-cream oral nutritional supplement (ONS ice-cream) to address malnutrition in older patients. A Scandishake-based®(Nutricia) vanilla flavored ice-cream was developed and piloted on a cohort of orthopedic patients over 3 days. All suitable patients were offered 100 g ice-cream portions (240 kcal/per portion). Acceptability and energy intake were our primary outcomes. Over 3 days, the ONS ice-cream was accepted in 77% (n = 27, median age, 75 years, IQR 12.5) of the times offered. Among these patients the average energy intake per day including the ONS ice-cream was 1006 kcal, a 41% increase in energy intake compared to an initial nutritional survey among the older orthopedic patients (714 kcal, p = 0.010). When surveyed 84% (n = 16) of patients stated they would have the ONS ice-cream again. An ONS ice-cream intervention to improve energy intake in older adults is feasible.

ABSTRACTAs global urbanisation continues to increase, we need to understand how urban environments contribute to maintenance of public health across different geographic regions. Current public health and environmental psychology research to this end is geographically constrained, deficient in direct cross-cultural comparisons between populations. This exploratory study applies a standardised analysis framework to health and wellbeing metrics of cities in the UK, Sweden, Estonia, Kenya and Thailand. This allows for comparison between geographically diverse cities to understand their role on citizens’ health. We assessed demographics, subjective stress and wellbeing, relationships between green and public spaces and features of the local environment on health in 659 adult participants across six study locations. The results indicate regional differences in stress and wellbeing and show correlations with living close to, and engaging with, green and/or public spaces. Issues regarding noise, air pollution and traffic congestion were reported as having an impact on personal wellbeing. We discuss the impact that diverse properties of green space may have had, as well as cross-cultural considerations between the impacts of the local environments. This exploratory research provides a base for future cross-cultural research using mixed-methods and multi-disciplinary approaches to explore socio-economic and infrastructure dimensions of urban spaces and their impact on health and wellbeing.

RAS proteins are small membrane-anchored GTPases that regulate key cellular signaling networks. It has been recently shown that different anionic lipid types can affect the spatiotemporal properties of RAS through dimerization/clustering and signaling fidelity. To understand the effects of anionic lipids on key spatiotemporal properties of RAS, we dissected 1 ms of data from all-atom molecular dynamics simulations for KRAS4B on two model anionic lipid membranes that have 30% of POPS mixed with neutral POPC and 8% of PIP2 mixed with POPC. We unveiled the orientation space of KRAS4B, whose kinetics were slower and more distinguishable on the membrane containing PIP2 than the membrane containing POPS. Particularly, the PIP2-mixed membrane can differentiate a third kinetic orientation state from the other two known orientation states. We observed that each orientation state may yield different binding modes with an RAF kinase, which is required for activating the MAPK/ERK signaling pathway. However, an overall occluded probability, for which RAF kinases cannot bind KRAS4B, remains unchanged on the two different membranes. We identified rare fast diffusion modes of KRAS4B that appear coupled with orientations exposed to cytosolic RAF. Particularly, on the membrane having PIP2, we found nonlinear correlations between the orientation states and the conformations of the cationic farnesylated hypervariable region, which acts as an anchor in the membrane. Using diffusion coefficients estimated from the all-atom simulations, we quantified the effect of PIP2 and POPS on the KRAS4B dimerization via Green’s function reaction dynamics simulations, in which the averaged dimerization rate is 12.5% slower on PIP2-mixed membranes.

ABSTRACTNeurourbanism looks to understand the relationship between urban environments and mental well-being and is well placed to assess the role of these environments on the urbanised and ageing global population. This study builds on research using mobile electroencephalography (EEG) to understand the impact of urban environments (busy, quiet and green urban spaces) on brain activity. Ninety-five older participants aged over 65 years undertook one of six walks in an urban neighbourhood, transitioning between two distinct environmental settings. This study explores changes in alpha (associated with relaxation) and beta (associated with attention) brain activity recorded during walking in differing urban environments. Neural activity significantly varies as participants walk between urban busy and green settings, with reduced levels of low beta activity in the green setting, suggesting attention changes consistent with Attention Restoration Theory. Levels of alpha activity significantly varied between the urban busy and the urban quiet settings, with increases in the urban busy setting. There were no significant differences in EEG activity between the urban green and urban quiet settings, suggesting that the magnitude of environmental contrast between the urban busy context and other urban settings is an important factor in understanding the effects of these spaces on brain activity.

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.

Ras protein colocalization at the plasma membrane is implicated in the activation of signaling cascades that promote cell growth, survival, and motility. However, the mechanisms that underpin Ras self-association remain unclear. We use molecular dynamics simulations to show how basic and hydrophobic components of the disordered C-terminal membrane tether of K-Ras4B combine to regulate its membrane interactions. Specifically, anionic lipids attract lysine residues to the membrane surface, thereby splitting the peptide population into two states that exchange on the microsecond time scale. These states differ in the membrane insertion of a methionine residue, which is influenced by local membrane composition. As a result, these states may impose context-dependent biases on the disposition of Ras’ signaling domain, with possible implications for the accessibility of its effector binding surfaces. We investigate Ras’ ability to nanocluster by fly-casting for patches of anionic lipids and find that while anionic lipids promote the intermolecular association of K-Ras4B membrane tethers, at short range this appears to be a passive process in which anionic lipids electrostatically screen these cationic peptides to mitigate their natural repulsion. Together with the sub-microsecond stability of interpeptide contacts, this result suggests that experimentally observed K-Ras4B nanoclustering is not driven by direct intermolecular contact of its membrane tethers.

Whether lipid rafts are present in the membranes of living cells remains hotly disputed despite their incontrovertible existence in liposomes at 298 K. In attempts to resolve this debate, molecular dynamics (MD) simulations have been extensively used to study lipid phase separation at high resolution. However, computation has been of limited utility in this respect because the experimental distributions of phases in lamellar lipid mixtures are poorly reproduced by simulations. In particular, all-atom (AA) approaches suffer from restrictions on accessible time scales and system sizes whereas the more efficient coarse-grained (CG) force fields remain insufficiently accurate to achieve correspondence with experiment. In this work, we refine the CG Martini parameters for the high- and low-melting temperature (Tm) lipids 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC) and 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine (DOPC). Our approach involves the modification of bonded Martini parameters based on fitting to atomistic simulations conducted with the CHARMM36 lipid force field. The resulting CG parameters reproduce experimental structural and thermodynamic properties of homogeneous lipid membranes while concurrently improving simulation fidelity to experimental phase diagrams of DPPC, DOPC, and cholesterol lipid mixtures. Importantly, the refined parameters provide much better phase accuracy for regions near the critical point that mimic the lipid concentrations under physiological conditions.

Force fields for molecular simulation are generally optimized to model macromolecules such as proteins at ambient temperature and pressure. Nevertheless, elevated temperatures are frequently used to enhance conformational sampling, either during system setup or as a component of an advanced sampling technique such as temperature replica exchange. Because macromolecular force fields are now put upon to simulate temperatures and time scales that greatly exceed their original design specifications, it is appropriate to re-evaluate whether these force fields are up to the task. Here, we quantify the rates of peptide bond isomerization in high-temperature simulations of three octameric peptides and a small fast-folding protein. We show that peptide octamers with and without proline residues undergo cis/transisomerization every 1–5 ns at 800 K with three classical atomistic force fields (AMBER99SB-ILDN, CHARMM22/CMAP, and OPLS-AA/L). On the low microsecond time scale, these force fields permit isomerization of nonprolyl peptide bonds at temperatures ≥500 K, and the CHARMM22/CMAP force field permits isomerization of prolyl peptide bonds ≥400 K. Moreover, the OPLS-AA/L force field allows chiral inversion about the Cαatom at 800 K. Finally, we show that temperature replica exchange permits cispeptide bonds developed at 540 K to subsequently migrate back to the 300 K ensemble, where cispeptide bonds are present in 2 ± 1% of the population of Trp-cage TC5b, including up to 4% of its folded state. Further work is required to assess the accuracy of cis/transisomerization in the current generation of protein force fields.

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 β2 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.

All molecular dynamics simulations are susceptible to sampling errors, which degrade the accuracy and precision of observed values. The statistical convergence of simulations containing atomistic lipid bilayers is limited by the slow relaxation of the lipid phase, which can exceed hundreds of nanoseconds. These long conformational autocorrelation times are exacerbated in the presence of charged solutes, which can induce significant distortions of the bilayer structure. Such long relaxation times represent hidden barriers that induce systematic sampling errors in simulations of solute insertion. To identify optimal methods for enhancing sampling efficiency, we quantitatively evaluate convergence rates using generalized ensemble sampling algorithms in calculations of the potential of mean force for the insertion of the ionic side chain analog of arginine in a lipid bilayer. Umbrella sampling (US) is used to restrain solute insertion depth along the bilayer normal, the order parameter commonly used in simulations of molecular solutes in lipid bilayers. When US simulations are modified to conduct random walks along the bilayer normal using a Hamiltonian exchange algorithm, systematic sampling errors are eliminated more rapidly and the rate of statistical convergence of the standard free energy of binding of the solute to the lipid bilayer is increased 3-fold. We compute the ratio of the replica flux transmitted across a defined region of the order parameter to the replica flux that entered that region in Hamiltonian exchange simulations. We show that this quantity, the transmission factor, identifies sampling barriers in degrees of freedom orthogonal to the order parameter. The transmission factor is used to estimate the depth-dependent conformational autocorrelation times of the simulation system, some of which exceed the simulation time, and thereby identify solute insertion depths that are prone to systematic sampling errors and estimate the lower bound of the amount of sampling that is required to resolve these sampling errors. Finally, we extend our simulations and verify that the conformational autocorrelation times estimated by the transmission factor accurately predict correlation times that exceed the simulation time scalesomething that, to our knowledge, has never before been achieved.

In recent years, atomistic molecular simulations have become a method of choice for studying the interaction of small molecules, peptides, and proteins with biological membranes. Here, we critically examine the statistical convergence of equilibrium properties in molecular simulations of two amino acid side-chain analogs, leucine and arginine, in the presence of a hydrated phospholipid bilayer. To this end, the convergence of the standard binding free energy for the reversible insertion of the solutes in the bilayer is systematically assessed by evaluating dozens of separate sets of umbrella sampling calculations for a total simulation time exceeding 400 μs. We identify rare and abrupt transitions in bilayer structure as a function of solute insertion depth. These transitions correspond to the slow reorganization of ionic interactions involving zwitterionic phospholipid headgroups when the solutes penetrate the lipid–water interface and when arginine is forced through the bilayer center. These rare events are shown to constitute hidden sampling barriers that limit the rate of convergence of equilibrium properties and result in systematic sampling errors. Our analysis demonstrates that the difficulty of attaining convergence for lipid bilayer-embedded solutes has, in general, been drastically underestimated. This information will assist future studies in improving accuracy by selecting a more appropriate reaction coordinate or by focusing computational resources on those regions of the reaction coordinate that exhibit slow convergence of equilibrium properties.

Magnesium translocation across cell membranes is essential for numerous physiological processes. Three recently reported crystal structures of the CorA magnesium transport system revealed a surprising architecture, with a bundle of giant α-helices forming a 60-Å-long pore that extends beyond the membrane before widening into a funnel-shaped cytosolic domain. The presence of divalent cations in putative intracellular regulation sites suggests that these structures correspond to the closed conformation of CorA. To examine the nature of the conduction pathway, we performed 110-ns molecular-dynamics simulations of two of these structures in a lipid bilayer with and without regulatory ions. The results show that a 15-Å-long hydrophobic constriction straddling the membrane-cytosol interface constitutes a steric bottleneck whose location coincides with an electrostatic barrier opposing cation translocation. In one of the simulations, structural relaxation after the removal of regulatory ions led to concerted changes in the tilt of the pore helices, resulting in iris-like dilation and spontaneous hydration of the hydrophobic neck. This simple and robust mechanism is consistent with the regulation of pore opening by intracellular magnesium concentration, and explains the unusual architecture of CorA.

Generalized-ensemble algorithms in temperature space have become popular tools to enhance conformational sampling in biomolecular simulations. A random walk in temperature leads to a corresponding random walk in potential energy, which can be used to cross over energetic barriers and overcome the problem of quasi-nonergodicity. In this paper, we introduce two novel methods: simulated tempering distributed replica sampling (STDR) and virtual replica exchange (VREX). These methods are designed to address the practical issues inherent in the replica exchange (RE), simulated tempering (ST), and serial replica exchange (SREM) algorithms. RE requires a large, dedicated, and homogeneous cluster of CPUs to function efficiently when applied to complex systems. ST and SREM both have the drawback of requiring extensive initial simulations, possibly adaptive, for the calculation of weight factors or potential energy distribution functions. STDR and VREX alleviate the need for lengthy initial simulations, and for synchronization and extensive communication between replicas. Both methods are therefore suitable for distributed or heterogeneous computing platforms. We perform an objective comparison of all five algorithms in terms of both implementation issues and sampling efficiency. We use disordered peptides in explicit water as test systems, for a total simulation time of over 42 μs. Efficiency is defined in terms of both structural convergence and temperature diffusion, and we show that these definitions of efficiency are in fact correlated. Importantly, we find that ST-based methods exhibit faster temperature diffusion and correspondingly faster convergence of structural properties compared to RE-based methods. Within the RE-based methods, VREX is superior to both SREM and RE. On the basis of our observations, we conclude that ST is ideal for simple systems, while STDR is well-suited for complex systems.

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.

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.

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.

Several letters to the editor are presented in response to articles in previous issues including one on the 1948 London Olympics Great Britain athletic men's team in the July 21, 2011 issue, "Your Say," in the July 21, 2011 issue, and a letter from a reader discussing Oscar Pistorius's participation in the 2011 International Association of Athletics Federations (IAAF) World Championships.