Reverse Mapping of Coarse Grained Polyglutamine Conformations from PRIME20 Sampling

An inverse coarse-graining protocol is presented for generating and validating atomistic structures of large (bio-) molecules from conformations obtained via a coarse-grained sampling method. Specifically, the protocol is implemented and tested based on the (coarse-grained) PRIME20 protein model (P20/SAMC), and the resulting all-atom conformations are simulated using conventional biomolecular force fields. The phase space sampling at the coarse-grained level is performed with a stochastical approximation Monte Carlo approach. The method is applied to a series of polypeptides, specifically dimers of polyglutamine with varying chain length in aqueous solution. The majority (>70 %) of the conformations obtained from the coarse-grained peptide model can successfully be mapped back to atomistic structures that remain conformationally stable during 10 ns of molecular dynamics simulations. This work can be seen as the first step towards the overarching goal of improving our understanding of protein aggregation phenomena through simulation methods.

Benefits of Zero-Phase or Linear Phase Filters to Design Multiscale Entropy: Theory and Application

In various applications, multiscale entropy (MSE) is often used as a feature to characterize the complexity of the signals in order to classify them. It consists of estimating the sample entropies (SEs) of the signal under study and its coarse-grained (CG) versions, where the CG process amounts to (1) filtering the signal with an average filter whose order is the scale and (2) decimating the filter output by a factor equal to the scale. In this paper, we propose to derive a new variant of the MSE. Its novelty stands in the way to get the sequences at different scales by avoiding distortions during the decimation step. To this end, a linear-phase or null-phase low-pass filter whose cutoff frequency is well suited to the scale is used. Interpretations on how the MSE behaves and illustrations with a sum of sinusoids, as well as white and pink noises, are given. Then, an application to detect attentional tunneling is presented. It shows the benefit of the new approach in terms of p value when one aims at differentiating the set of MSEs obtained in the attentional tunneling state from the set of MSEs obtained in the nominal state. It should be noted that CG versions can be replaced not only for the MSE but also for other variants.

Extracting transition features among brain states based on coarse-grained similarity measurement for autism spectrum disorder analysis

BACKGROUND

The abnormal brain functional connectivity (FC) of patients with mental diseases is closely linked to the transition features among brain states. However, the current research on state transition will produce certain division deviations in the measurement method of state division, and also ignore the transition features among multiple states that contain more abundant information for analyzing brain diseases.

PURPOSE

To investigate the potential of the proposed method based on coarse-grained similarity measurement to solve the problem of state division, and consider the transition features among multiple states to analyze the FC abnormalities of autism spectrum disorder (ASD) patients.

METHODS

We used resting-state functional magnetic resonance imaging to examine 45 ASD and 47 healthy controls (HC). The FC between brain regions was calculated by the sliding window and correlation algorithm, and a novel coarse-grained similarity measure method was used to cluster the FC networks into five states, and then extract the features both of the state itself and the transition features among multiple states for analysis and diagnosis.

RESULTS

(1) The state as divided by the coarse-grained measurement method improves the diagnostic performance of individuals with ASD compared with previous methods. (2) The transition features among multiple states can provide complementary information to the features of the state itself in the ASD analysis and diagnosis. (3) ASD individuals have different brain state transitions than HC. Specifically, the abnormalities in intra- and inter-network connectivity of ASD patients mainly occur in the default mode network, the visual network, and the cerebellum.

CONCLUSIONS

Such results demonstrate that our approach with new measurements and new features is effective and promising in brain state analysis and ASD diagnosis.

Permeability of antioxidants through a lipid bilayer model with coarse-grained simulations

Oxidative stress caused by pollution and lifestyle changes causes an excess of free radicals that react chemically with cell constituents leading to irreversible damage. There are molecules known as antioxidants that reduce the levels of free radicals. Some pigments of fruits and vegetables known as anthocyanins have antioxidant properties. Their interaction with the cell membrane becomes a crucial step in studying these substances. In this research, molecular dynamics simulations, particularly, coarse-grained molecular dynamics (CGMD) were used. This technique aims to replace functional groups with corresponding beads that represent their level of polarity and affinities to other chemical groups. Also, umbrella sampling was carried out to obtain free energy profiles that describe well the orientation and location of antioxidants in a membrane considering Trolox, Cyanidin, Gallic Acid, and Resveratrol molecules to study the structural effects they cause on it. It was concluded in this study that an antioxidant when crossing the membrane does not cause either damage to the structural properties or the loss of packing and stratification of phospholipids. it was also observed that the most reactive part of the molecules could easily approach area A prone to lipid oxidation, which can describe the antioxidant capacity of these molecules.Communicated by Ramaswamy H. Sarma.

Protein-protein association properties of human βB2-crystallins

Protein-protein association events are involved in many physiological and pathological processes. Cataract disease is a pathology that manifests protein aggregation of crystallins. β-Crystallins are present in a high proportion in the eye lens. Therefore, the structural study of the dimerization properties of crystallins can shed light on the first stages of protein aggregation. In the present work, we examine the protein-protein association profiles of the human βB2-crystallin by employing extensive coarse-grained molecular dynamics (CG-MD) and the Markov state analysis. Interestingly, our results clearly show important changes in the protein dimerization kinetics between wt-HβB2C and the deamidated systems. The two systems show dimeric conformations. However, the association and dissociation rates are very different. Our results show that the deamidated system can associate faster and dissociate slower than the wt- HβB2C. The deamidated system is in a slightly opened conformation with the Greek-key motifs well folded, suggesting that a complete unfolding of the protein is not required for aggregation. Our results describe the first stages of crystallin aggregation due to post-translational modifications.

How Alligator Immune Peptides Kill Gram-Negative Bacteria: A Lipid-Scrambling, Squeezing, and Extracting Mechanism Revealed by Theoretical Simulations

Alligator sinensis cathelicidins (As-CATHs) are antimicrobial peptides extracted from alligators that enable alligators to cope with diseases caused by bacterial infections. This study assessed the damaging effects of sequence-truncated and residue-substituted variants of As-CATH4, AS4-1, AS4-5, and AS4-9 (with decreasing charges but increasing hydrophobicity) on the membranes of Gram-negative bacteria at the molecular level by using coarse-grained molecular dynamics simulations. The simulations predicted that all the variants disrupt the structures of the inner membrane of Gram-negative bacteria, with AS4-9 having the highest antibacterial activity that is able to squeeze the membrane and extract lipids from the membrane. However, none of them can disrupt the structure of asymmetric outer membrane of Gram-negative bacteria, which is composed of lipopolysaccharides in the outer leaflet and phospholipids in the inner leaflet. Nonetheless, the adsorption of AS4-9 induces lipid scrambling in the membrane by lowering the free energy of a phospholipid flipping from the inner leaflet up to the outer leaflet. Upon binding onto the lipid-scrambled outer membrane, AS4-9s are predicted to squeeze and extract phospholipids from the membrane, AS4-5s have a weak pull-out effect, and AS4-1s mainly stay free in water without any lipid-extracting function. These findings provide inspiration for the development of potent therapeutic agents targeting bacteria.

Metastable alpha-rich and beta-rich conformations of small Aβ42 peptide oligomers

Probing the structures of amyloid-β (Aβ) peptides in the early steps of aggregation is extremely difficult experimentally and computationally. Yet, this knowledge is extremely important as small oligomers are the most toxic species. Experiments and simulations on Aβ42 monomer point to random coil conformations with either transient helical or β-strand content. Our current conformational description of small Aβ42 oligomers is funneled toward amorphous aggregates with some β-sheet content and rare high energy states with well-ordered assemblies of β-sheets. In this study, we emphasize another view based on metastable α-helix bundle oligomers spanning the C-terminal residues, which are predicted by the machine-learning AlphaFold2 method and supported indirectly by low-resolution experimental data on many amyloid polypeptides. This finding has consequences in developing novel chemical tools and to design potential therapies to reduce aggregation and toxicity.

Coarse-Grained Molecular Dynamics of pH-Sensitive Lipids

pH-sensitive lipids represent a class of lipids that can be protonated and destabilized in acidic environments, as they become positively charged in response to low-pH conditions. They can be incorporated into lipidic nanoparticles such as liposomes, which are able to change their properties and allow specific drug delivery at the acidic conditions encountered in some pathological microenvironments. In this work, we used coarse-grained molecular-dynamic simulations to study the stability of neutral and charged lipid bilayers containing POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) and various kinds of ISUCA ((F)2-(imidazol-1-yl)succinic acid)-derived lipids, which can act as pH-sensitive molecules. In order to explore such systems, we used a MARTINI-derived forcefield, previously parameterized using all-atom simulation results. We calculated the average area per lipid, the second-rank order parameter and the lipid diffusion coefficient of both lipid bilayers made of pure components and mixtures of lipids in different proportions, under neutral or acidic conditions. The results show that the use of ISUCA-derived lipids disturbs the lipid bilayer structure, with the effect being particularly marked under acidic conditions. Although more-in depth studies on these systems must be carried out, these initial results are encouraging and the lipids designed in this research could be a good basis for developing new pH-sensitive liposomes.

The effect of rhamnolipids on fungal membrane models as described by their interactions with phospholipids and sterols: An in silico study

Introduction: Rhamnolipids (RLs) are secondary metabolites naturally produced by bacteria of the genera Pseudomonas and Burkholderia with biosurfactant properties. A specific interest raised from their potential as biocontrol agents for crop culture protection in regard to direct antifungal and elicitor activities. As for other amphiphilic compounds, a direct interaction with membrane lipids has been suggested as the key feature for the perception and subsequent activity of RLs. Methods: Molecular Dynamics (MD) simulations are used in this work to provide an atomistic description of their interactions with different membranous lipids and focusing on their antifungal properties. Results and discussion: Our results suggest the insertion of RLs into the modelled bilayers just below the plane drawn by lipid phosphate groups, a placement that is effective in promoting significant membrane fluidification of the hydrophobic core. This localization is promoted by the formation of ionic bonds between the carboxylate group of RLs and the amino group of the phosphatidylethanolamine (PE) or phosphatidylserine (PS) headgroups. Moreover, RL acyl chains adhere to the ergosterol structure, forming a significantly higher number of van der Waals contact with respect to what is observed for phospholipid acyl chains. All these interactions might be essential for the membranotropic-driven biological actions of RLs.

A Core-Shell Approach for Systematically Coarsening Nanoparticle-Membrane Interactions: Application to Silver Nanoparticles

The continuous release of engineered nanomaterial (ENM) into the environment may bring about health concerns following human exposure. One important source of ENMs are silver nanoparticles (NPs) that are extensively used as anti-bacterial additives. The introduction of ENMs into the human body can occur via ingestion, skin uptake or the respiratory system. Therefore, evaluating how NPs translocate over bio-membranes is essential in assessing their primary toxicity. Unfortunately, data regarding membrane-NP interaction is still scarce, as is theoretical and in silico insight into what governs adhesion and translocation for the most relevant NPs and membranes. Coarse-grained (CG) molecular descriptions have the potential to alleviate this situation, but are hampered by the absence of a direct link to NP materials and membrane adhesion mechanisms. Here, we interrogate the relationship between the most common NP representation at the CG level and the adhesion characteristics of a model lung membrane. We find that this representation for silver NPs is non-transferable, meaning that a proper CG representation for one size is not suited for other sizes. We also identify two basic types of primary adhesion-(partial) NPs wrapping by the membrane and NP insertion into the membrane-that closely relate to the overall NP hydrophobicity and significantly differ in terms of lipid coatings. The proven non-transferability of the standard CG representation with size forms an inspiration for introducing a core-shell model even for bare NPs that are uniform in composition. Using existing all-atom molecular dynamics (MD) data as a reference, we show that this extension does allow us to reproduce size-dependent NP adhesion properties and lipid responses to NP binding at the CG level. The subsequent CGMD evaluation for 10 nm Ag NPs provides new insight into membrane binding for relevant NP sizes and into the role of water in trapping NPs into defected mixed monolayer-bilayer states. This development will be instrumental for simulating NP-membrane adhesion towards more experimentally relevant length and time scales for particular NP materials.

Coarse-grained tight-binding models

Calculating the electronic structure of systems involving very different length scales presents a challenge. Empirical atomistic descriptions such as pseudopotentials or tight-binding models allow one to calculate the effects of atomic placements, but the computational burden increases rapidly with the size of the system, limiting the ability to treat weakly bound extended electronic states. Here we propose a new method to connect atomistic and quasi-continuous models, thus speeding up tight-binding calculations for large systems. We divide a structure into blocks consisting of several unit cells which we diagonalize individually. We then construct a tight-binding Hamiltonian for the full structure using a truncated basis for the blocks, ignoring states having large energy eigenvalues and retaining states with energies close to the band edge energies. A numerical test using a GaAs/AlAs quantum well shows the computation time can be decreased to less than 5% of the full calculation with errors of less than 1%. We give data for the trade-offs between computing time and loss of accuracy. We also tested calculations of the density of states for a GaAs/AlAs quantum well and find a ten times speedup without much loss in accuracy.

Molecular Structure Effect of a Self-Assembled Monolayer on Thermal Resistance across an Interface

Understanding heat transfer across an interface is essential to a variety of applications, including thermal energy storage systems. Recent studies have shown that introducing a self-assembled monolayer (SAM) can decrease thermal resistance between solid and fluid. However, the effects of the molecular structure of SAM on interfacial thermal resistance (ITR) are still unclear. Using the gold–SAM/PEG system as a model, we performed nonequilibrium molecular dynamics simulations to calculate the ITR between the PEG and gold. We found that increasing the SAM angle value from 100° to 150° could decrease ITR from 140.85 × 10⁻⁹ to 113.79 × 10⁻⁹ m² K/W owing to penetration of PEG into SAM chains, which promoted thermal transport across the interface. Moreover, a strong dependence of ITR on bond strength was also observed. When the SAM bond strength increased from 2 to 640 kcal⋅mol−1Å−2, ITR first decreased from 106.88 × 10⁻⁹ to 102.69 × 10⁻⁹ m² K/W and then increased to 123.02 × 10⁻⁹ m² K/W until reaching a steady state. The minimum ITR was obtained when the bond strength of SAM was close to that of PEG melt. The matching vibrational spectra facilitated the thermal transport between SAM chains and PEG. This work provides helpful information regarding the optimized design of SAM to enhance interfacial thermal transport.

Preference Parameters for the Calculation of Thermal Conductivity by Multiparticle Collision Dynamics

Calculation of the thermal conductivity of nanofluids by molecular dynamics (MD) is very common. Regrettably, general MD can only be employed to simulate small systems due to the huge computation workload. Instead, the computation workload can be considerably reduced due to the coarse-grained fluid when multiparticle collision dynamics (MPCD) is employed. Hence, such a method can be utilized to simulate a larger system. However, the selection of relevant parameters of MPCD noticeably influences the calculation results. To this end, parameterization investigations for various bin sizes, number densities, time-steps, rotation angles and temperatures are carried out, and the influence of these parameters on the calculation of thermal conductivity are analyzed. Finally, the calculations of thermal conductivity for liquid argon, water and Cu-water nanofluid are performed, and the errors compared to the theoretical values are 3.4%, 1.5% and 1.2%, respectively. This proves that the method proposed in the present work for calculating the thermal conductivity of nanofluids is applicable.

Effect of Microstructure Refinement on Surface Morphology and Dynamic Mechanical Properties of W-Cu Alloys

Two ultrafine-grained W-Cu alloys and two coarse-grained W-Cu alloys were prepared to study the effect of tungsten grain refinement on the interface characteristics between coating and W-Cu alloys. The experimental results show that in the coarse-grained W-Cu alloys, the tungsten phase near the surface is easy to form pits and cracks during impact loading, while the fine-grained tungsten alloy is not prone to this phenomenon. Simulations show that refining tungsten grains can not only reduce the impact absorption energy, but also increase the contact area of tungsten and copper phases, thereby reducing the fracture probability of tungsten phases and improving the dynamic mechanical properties of the W-Cu alloys under impact loading. The tested results show that the shear strength of gold studs on the coating is increased by about 33%, after grain refinement for the W-Cu alloys.

Development of Martini 2.2 parameters for N-glycans: a case study of the HIV-1 Env glycoprotein dynamics

N-linked glycans are ubiquitous in nature and play key roles in biology. For example, glycosylation of pathogenic proteins is a common immune evasive mechanism, hampering the development of successful vaccines. Due to their chemical variability and complex dynamics, an accurate molecular understanding of glycans is still limited by the lack of effective resolution of current experimental approaches. Here, we have developed and implemented a reductive model based on the popular Martini 2.2 coarse-grained force field for the computational study of N-glycosylation. We used the HIV-1 Env as a direct applied example of a highly glycosylated protein. Our results indicate that the model not only reproduces many observables in very good agreement with a fully atomistic force field but also can be extended to study large amount of glycosylation variants, a fundamental property that can aid in the development of drugs and vaccines.

RNA 3D Structure Prediction Using Coarse-Grained Models

The three-dimensional (3D) structures of Ribonucleic acid (RNA) molecules are essential to understanding their various and important biological functions. However, experimental determination of the atomic structures is laborious and technically difficult. The large gap between the number of sequences and the experimentally determined structures enables the thriving development of computational approaches to modeling RNAs. However, computational methods based on all-atom simulations are intractable for large RNA systems, which demand long time simulations. Facing such a challenge, many coarse-grained (CG) models have been developed. Here, we provide a review of CG models for modeling RNA 3D structures, compare the performance of the different models, and offer insights into potential future developments.

Binding of Ca2+-independent C2 domains to lipid membranes: A multi-scale molecular dynamics study

C2 domains facilitate protein interactions with lipid bilayers in either a Ca²⁺-dependent or -independent manner. We used molecular dynamics (MD) simulations to explore six Ca²⁺-independent C2 domains, from KIBRA, PI3KC2α, RIM2, PTEN, SHIP2, and Smurf2. In coarse-grained MD simulations these C2 domains formed transient interactions with zwitterionic bilayers, compared with longer-lived interactions with anionic bilayers containing phosphatidylinositol bisphosphate (PIP₂). Type I C2 domains bound non-canonically via the front, back, or side of the β sandwich, whereas type II C2 domains bound canonically, via the top loops. C2 domains interacted strongly with membranes containing PIP₂, causing bound anionic lipids to cluster around the protein. Binding modes were refined via atomistic simulations. For PTEN and SHIP2, CG simulations of their phosphatase plus C2 domains with PIP₂-containing bilayers were also performed, and the roles of the two domains in membrane localization compared. These studies establish a simulation protocol for membrane-recognition proteins.

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Binding of Ca²⁺-independent C2 domains to membranes was explored by MD simulation

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C2 domains from KIBRA, PI3KC2α, RIM2, PTEN, SHIP2, and Smurf2 were compared

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C2 domains formed longer-lived interactions with lipid bilayers containing PIP₂

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For PTEN and SHIP2, simulations of their phosphatase plus C2 domains were performed

Molecular Dynamics of Janus Nanodimers Dispersed in Lamellar Phases of a Block Copolymer

We investigate structural and dynamical properties of Janus nanodimers (NDs) dispersed in lamellar phases of a diblock copolymer. By performing molecular dynamics simulations, we show that an accurate tuning of the interactions between NDs and copolymer blocks can lead to a close control of NDs' space distribution and orientation. In particular, NDs are preferentially found within the lamellae if enthalpy-driven forces offset their entropic counterpart. By contrast, when enthalpy-driven forces are not significant, the distribution of NDs, preferentially observed within the inter-lamellar spacing, is mostly driven by excluded-volume effects. Not only does the degree of affinity between host and guest species drive the NDs' distribution in the polymer matrix, but it also determines their space orientation. In turn, these key structural properties influence the long-time dynamics and the ability of NDs to diffuse through the polymer matrix.

Understanding the Synergistic Correlation between the Spatial Distribution of Drug-Loaded Mixed Micellar Systems and In Vitro Behavior via Experimental and Computational Approaches

To better promote the application of polymeric mixed micelles (PMMs), a coarse-grained molecular dynamics simulation (CGMD) has been employed to investigate the factors controlling the spatial distribution within the PMMs and predict their drug-loading properties, meanwhile, combined with experimental methods to validate and examine it. In this study, the snapshots obtained from CGMD and the results of proton nuclear magnetic resonance (¹H NMR) and transmission electron microscopy (TEM) provide new insights into the distribution principle that the spatial distribution depends on the hydrophobic compatibility of drugs with the regions within PMMs. Docetaxel (DTX) is located within the interior or near the core-corona interface of the HS15 hydrophobic core inside FS/PMMs (PMMs fabricated from a nonionic triblock copolymer (F127)) and a nonionic surfactant (HS15), and therefore, the system with a high HS15 ratio, such as system I, is more suitable for loading DTX. In contrast, the more water-soluble puerarin (PUE) is more likely to be solubilized in the "secondary hydrophobic area," mainly formed by the hydrophobic part of F127 within FS/PMMs. However, when the initial feeding concentration of the drug is increased or the FS mixing ratios are changed, an inappropriate distribution would occur and hence influence the drug-loading stability. Also, this impact was further elucidated by the calculated parameters (solvent-accessible surface area (SASA), the radius of gyration (R_g), and energy landscape), and the analysis of the drug leakage, concluding that inappropriate distribution of the drug would lower the stability of the drug in the PMMs. These results combined together provide new insights into the distribution principle that the spatial distribution of drugs within PMMs depends on the hydrophobic compatibility of drugs with the regions formed by micellar materials. Additionally, in vitro drug release yielded a consistent picture with the above conclusions and provides evidence that both the location of the drug within the systems and the stability of the drug-loading system have a great influence on the drug release behavior. Accordingly, this work demonstrates that we can tune the drug-loading stability and drug release behavior via the drug-PMM interaction and drug location study, and CGMD technology would be a step forward in the search for suitable drug-delivery PMMs.

CUTie2: The Attack of the Cyclic Nucleotide Sensor Clones

The detection of small molecules in living cells using genetically encoded FRET sensors has revolutionized our understanding of signaling pathways at the sub-cellular level. However, engineering fluorescent proteins and specific binding domains to create new sensors remains challenging because of the difficulties associated with the large size of the polypeptides involved, and their intrinsically huge conformational variability. Indeed, FRET sensors’ design still relies on vague structural notions, and trial and error combinations of linkers and protein modules. We recently designed a FRET sensor for the second messenger cAMP named CUTie (Cyclic nucleotide Universal Tag for imaging experiments), which granted sub-micrometer resolution in living cells. Here we apply a combination of sequence/structure analysis to produce a new-generation FRET sensor for the second messenger cGMP based on Protein kinase G I (PKGI), which we named CUTie2. Coarse-grained molecular dynamics simulations achieved an exhaustive sampling of the relevant spatio-temporal coordinates providing a quasi-quantitative prediction of the FRET efficiency, as confirmed by in vitro experiments. Moreover, biochemical characterization showed that the cGMP binding module maintains virtually the same affinity and selectivity for its ligand thant the full-length protein. The computational approach proposed here is easily generalizable to other allosteric protein modules, providing a cost effective-strategy for the custom design of FRET sensors.

Role of pKA in Charge Regulation and Conformation of Various Peptide Sequences

Peptides containing amino acids with ionisable side chains represent a typical example of weak ampholytes, that is, molecules with multiple titratable acid and base groups, which generally exhibit charge regulating properties upon changes in pH. Charged groups on an ampholyte interact electrostatically with each other, and their interaction is coupled to conformation of the (macro)molecule, resulting in a complex feedback loop. Their charge-regulating properties are primarily determined by the pKA of individual ionisable side-chains, modulated by electrostatic interactions between the charged groups. The latter is determined by the amino acid sequence in the peptide chain. In our previous work we introduced a simple coarse-grained model of a flexible peptide. We validated it against experiments, demonstrating its ability to quantitatively predict charge on various peptides in a broad range of pH. In the current work, we investigated two types of peptide sequences: diblock and alternating, each of them consisting of an equal number of amino acids with acid and base side-chains. We showed that changing the sequence while keeping the same overall composition has a profound effect on the conformation, whereas it practically does not affect total charge on the peptide. Nevertheless, the sequence significantly affects the charge state of individual groups, showing that the zero net effect on the total charge is a consequence of unexpected cancellation of effects. Furthermore, we investigated how the difference between the pKA of acid and base side chains affects the charge and conformation of the peptide, showing that it is possible to tune the charge-regulating properties by following simple guiding principles based on the pKA and on the amino acid sequence. Our current results provide a theoretical basis for understanding of the complex coupling between the ionisation and conformation in flexible polyampholytes, including synthetic polymers, biomimetic materials and biological molecules, such as intrinsically disordered proteins, whose function can be regulated by changes in the pH.

Oxidation degree of a cell membrane model and its response to structural changes, a coarse-grained molecular dynamics approach

Oxidative stress plays an essential role in the regulation of vital processes in living organisms. Reactive oxygen species can react chemically with the constituents of the cells leading to irreversible damage. The first structure of the cell in contact with the environment that surrounds it is the membrane, which protects it and allows the exchange of substances. Some signals manifest when the components of a bilayer are undergoing oxidation, like an increase in the lipid area, decrease in the thickness of the bilayer, and exchange of the oxidized groups toward the bilayer surface. In this investigation, a molecular dynamics simulation was done on a set of Dioleoylphosphatidylcholine membranes with different percentage of oxidized lipids, in order to observe the effect of the oxidation degree on the membrane structure. It was found that, as higher the concentration of oxidized lipids is, the larger the damage of the membrane. This is reflected in the increase in the lipid area and the decrease in the thickness and membrane packing. Also, it was observed that hydrophobicity inside the membrane decreases as the oxidation percentage increases.Communicated by Ramaswamy H. Sarma.

Hybrid MM/CG Webserver: Automatic Set Up of Molecular Mechanics/Coarse-Grained Simulations for Human G Protein-Coupled Receptor/Ligand Complexes

Hybrid Molecular Mechanics/Coarse-Grained (MM/CG) simulations help predict ligand poses in human G protein-coupled receptors (hGPCRs), the most important protein superfamily for pharmacological applications. This approach allows the description of the ligand, the binding cavity, and the surrounding water molecules at atomistic resolution, while coarse-graining the rest of the receptor. Here, we present the Hybrid MM/CG Webserver (mmcg.grs.kfa-juelich.de) that automatizes and speeds up the MM/CG simulation setup of hGPCR/ligand complexes. Initial structures for such complexes can be easily and efficiently generated with other webservers. The Hybrid MM/CG server also allows for equilibration of the systems, either fully automatically or interactively. The results are visualized online (using both interactive 3D visualizations and analysis plots), helping the user identify possible issues and modify the setup parameters accordingly. Furthermore, the prepared system can be downloaded and the simulation continued locally.

Exploring the use of molecular dynamics in assessing protein variants for phenotypic alterations

With the advent of rapid sequencing technologies, making sense of all the genomic variations that we see among us has been a major challenge. A plethora of algorithms and methods exist that try to address genome interpretation through genotype-phenotype linkage analysis or evaluating the loss of function/stability mutations in protein. Critical Assessment of Genome Interpretation (CAGI) offers an exceptional platform to blind-test all such algorithms and methods to assess their true ability. We take advantage of this opportunity to explore the use of molecular dynamics simulation as a tool to assess alteration of phenotype, loss of protein function, interaction, and stability. The results show that coarse-grained dynamics based protein flexibility analysis on 34 CHEK2 and 1719 CALM1 single mutants perform reasonably well for class-based predictions for phenotype alteration and two-thirds of the predicted scores return a correlation coefficient of 0.6 or more. When all-atom dynamics is used to predict altered stability due to mutations for Frataxin protein (8 cases), the predictions are comparable to the state-of-the-art methods. The competitive performance of our straightforward approach to phenotype interpretation contrasts with heavily trained machine learning approaches, and open new avenues to rationally improve genome interpretation.

Modeling of Disordered Protein Structures Using Monte Carlo Simulations and Knowledge-Based Statistical Force Fields

The description of protein disordered states is important for understanding protein folding mechanisms and their functions. In this short review, we briefly describe a simulation approach to modeling protein interactions, which involve disordered peptide partners or intrinsically disordered protein regions, and unfolded states of globular proteins. It is based on the CABS coarse-grained protein model that uses a Monte Carlo (MC) sampling scheme and a knowledge-based statistical force field. We review several case studies showing that description of protein disordered states resulting from CABS simulations is consistent with experimental data. The case studies comprise investigations of protein⁻peptide binding and protein folding processes. The CABS model has been recently made available as the simulation engine of multiscale modeling tools enabling studies of protein⁻peptide docking and protein flexibility. Those tools offer customization of the modeling process, driving the conformational search using distance restraints, reconstruction of selected models to all-atom resolution, and simulation of large protein systems in a reasonable computational time. Therefore, CABS can be combined in integrative modeling pipelines incorporating experimental data and other modeling tools of various resolution.

Gating mechanisms during actin filament elongation by formins

Formins play an important role in the polymerization of unbranched actin filaments, and particular formins slow elongation by 5–95%. We studied the interactions between actin and the FH2 domains of formins Cdc12, Bni1 and mDia1 to understand the factors underlying their different rates of polymerization. All-atom molecular dynamics simulations revealed two factors that influence actin filament elongation and correlate with the rates of elongation. First, FH2 domains can sterically block the addition of new actin subunits. Second, FH2 domains flatten the helical twist of the terminal actin subunits, making the end less favorable for subunit addition. Coarse-grained simulations over longer time scales support these conclusions. The simulations show that filaments spend time in states that either allow or block elongation. The rate of elongation is a time-average of the degree to which the formin compromises subunit addition rather than the formin-actin complex literally being in ‘open’ or ‘closed’ states.

Multiscale Computational Modeling of the Nanostructure of Solid Dispersions of Hydroxypropyl Methylcellulose Acetate Succinate (HPMCAS) and Phenytoin

We recently developed coarse-grained (CG) force fields for hydroxypropyl methylcellulose acetate succinate (HPMCAS) polymers and the model drug molecule phenytoin, and a continuum transport model to study the polymer-drug nanostructures presented during a dissolution test after solvation of solid dispersion particles. We model the polymer-drug interactions that contribute to suppression of drug aggregation, release, and crystal growth during the dissolution process, and we take these as indicators of polymer effectiveness. We find that the size and the intermolecular interaction strength of the functional group and the drug loading concentration are the major factors that impact the effectiveness of the polymeric excipient. The hydroxypropyl acetyl group is the most effective functional group, followed by the acetyl group, while the deprotonated succinyl group is the least effective functional group, except that the deprotonated succinyl group at the 6-position is very effective in slowing down the phenytoin crystal growth. Our simulation results thus suggest HPMCAS with higher acetyl and lower succinyl content is more effective in promoting phenytoin solubility in dissolution media, and polymers become less effective when drug loading becomes high (i.e., 50% of the mass of the polymer/drug solid dispersion), agreeing with previous experimental studies. In addition, our transport model indicates that the drug release time from a solid dispersion particle of 2 μm diameter is less than 10 min, correlating well with the experimental time scale for a typical dissolution profile to reach maximum peak concentration. Our modeling effort, therefore, provides new avenues to understand the dissolution behavior of complex HPMCAS-phenytoin solid dispersions and offers a new design tool to optimize the formulation. Moreover, the systematic and robust approach used in our computational models can be extended to other polymeric excipients and drug candidates.

Efficient estimation of binding free energies between peptides and an MHC class II molecule using coarse-grained molecular dynamics simulations with a weighted histogram analysis method

We estimate the binding free energy between peptides and an MHC class II molecule using molecular dynamics (MD) simulations with the weighted histogram analysis method (WHAM). We show that, owing to its more thorough sampling in the available computational time, the binding free energy obtained by pulling the whole peptide using a coarse-grained (CG) force field (MARTINI) is less prone to significant error induced by inadequate-sampling than using an atomistic force field (AMBER). We further demonstrate that using CG MD to pull 3-4 residue peptide segments while leaving the remaining peptide segments in the binding groove and adding up the binding free energies of all peptide segments gives robust binding free energy estimations, which are in good agreement with the experimentally measured binding affinities for the peptide sequences studied. Our approach thus provides a promising and computationally efficient way to rapidly and reliably estimate the binding free energy between an arbitrary peptide and an MHC class II molecule. © 2017 Wiley Periodicals, Inc.

The 1-Particle-per-k-Nucleotides (1PkN) Elastic Network Model of DNA Dynamics with Sequence-Dependent Geometry

Coarse-grained models of DNA have made important contributions to the determination of the physical properties of genomic DNA, working as a molecular machine for gene regulation. In this study, to analyze the global dynamics of long DNA sequences with consideration of sequence-dependent geometry, we propose elastic network models of DNA where each particle represents k nucleotides (1-particle-per-k-nucleotides, 1PkN). The models were adjusted according to profiles of the anisotropic fluctuations obtained from our previous 1-particle-per-1-nucleotide (1P1N) model, which was proven to reproduce such profiles of all-atom models. We confirmed that the 1P3N and 1P4N models are suitable for the analysis of detailed dynamics such as local twisting motion. The models are intended for the analysis of large structures, e.g., 10-nm fibers in the nucleus, and nucleoids of mitochondrial or phage DNA at low computational costs. As an example, we surveyed the physical characteristics of the whole mitochondrial human and Plasmodium falciparum genomes.

Influence of Temperature on Transdermal Penetration Enhancing Mechanism of Borneol: A Multi-Scale Study

The influence of temperature on the transdermal permeation enhancing mechanism of borneol (BO) was investigated using a multi-scale method, containing a coarse-grained molecular dynamic (CG-MD) simulation, an in vitro permeation experiment, and a transmission electron microscope (TEM) study. The results showed that BO has the potential to be used as a transdermal penetration enhancer to help osthole (OST) penetrate into the bilayer. With the increasing temperature, the stratum corneum (SC) becomes more flexible, proving to be synergistic with the permeation enhancement of BO, and the lag time (T_Lag) of BO and OST are shortened. However, when the temperature increased too much, with the effect of BO, the structure of SC was destroyed; for example, a water pore was formed and the micelle reversed. Though there were a number of drugs coming into the SC, the normal bilayer structure was absent. In addition, through comparing the simulation, in vitro experiment, and TEM study, we concluded that the computer simulation provided some visually detailed information, and the method plays an important role in related studies of permeation.

Association of Peripheral Membrane Proteins with Membranes: Free Energy of Binding of GRP1 PH Domain with Phosphatidylinositol Phosphate-Containing Model Bilayers

Understanding the energetics of peripheral protein-membrane interactions is important to many areas of biophysical chemistry and cell biology. Estimating free-energy landscapes by molecular dynamics (MD) simulation is challenging for such systems, especially when membrane recognition involves complex lipids, e.g., phosphatidylinositol phosphates (PIPs). We combined coarse-grained MD simulations with umbrella sampling to quantify the binding of the well-explored GRP1 pleckstrin homology (PH) domain to model membranes containing PIP molecules. The experimentally observed preference of GRP1-PH for PIP3 over PIP2 was reproduced. Mutation of a key residue (K273A) within the canonical PIP-binding site significantly reduced the free energy of PIP binding. The presence of a noncanonical PIP-interaction site, observed experimentally in other PH domains but not previously in GRP1-PH, was also revealed. These studies demonstrate how combining coarse-grained simulations and umbrella sampling can unmask the molecular basis of the energetics of interactions between peripheral membrane proteins and complex cellular membranes.

From residue coevolution to protein conformational ensembles and functional dynamics

The analysis of evolutionary amino acid correlations has recently attracted a surge of renewed interest, also due to their successful use in de novo protein native structure prediction. However, many aspects of protein function, such as substrate binding and product release in enzymatic activity, can be fully understood only in terms of an equilibrium ensemble of alternative structures, rather than a single static structure. In this paper we combine coevolutionary data and molecular dynamics simulations to study protein conformational heterogeneity. To that end, we adapt the Boltzmann-learning algorithm to the analysis of homologous protein sequences and develop a coarse-grained protein model specifically tailored to convert the resulting contact predictions to a protein structural ensemble. By means of exhaustive sampling simulations, we analyze the set of conformations that are consistent with the observed residue correlations for a set of representative protein domains, showing that (i) the most representative structure is consistent with the experimental fold and (ii) the various regions of the sequence display different stability, related to multiple biologically relevant conformations and to the cooperativity of the coevolving pairs. Moreover, we show that the proposed protocol is able to reproduce the essential features of a protein folding mechanism as well as to account for regions involved in conformational transitions through the correct sampling of the involved conformers.

MD Simulations of tRNA and Aminoacyl-tRNA Synthetases: Dynamics, Folding, Binding, and Allostery

While tRNA and aminoacyl-tRNA synthetases are classes of biomolecules that have been extensively studied for decades, the finer details of how they carry out their fundamental biological functions in protein synthesis remain a challenge. Recent molecular dynamics (MD) simulations are verifying experimental observations and providing new insight that cannot be addressed from experiments alone. Throughout the review, we briefly discuss important historical events to provide a context for how far the field has progressed over the past few decades. We then review the background of tRNA molecules, aminoacyl-tRNA synthetases, and current state of the art MD simulation techniques for those who may be unfamiliar with any of those fields. Recent MD simulations of tRNA dynamics and folding and of aminoacyl-tRNA synthetase dynamics and mechanistic characterizations are discussed. We highlight the recent successes and discuss how important questions can be addressed using current MD simulations techniques. We also outline several natural next steps for computational studies of AARS:tRNA complexes.

Simulating the antimicrobial mechanism of human β-defensin-3 with coarse-grained molecular dynamics

Human β-defensin-3 (HβD-3) is an endogenous antimicrobial peptide with potent and broad killing activity against various microorganisms, and thus, it is an attractive candidate for the development of novel peptide antibiotics, but its antimicrobial mechanism remains elusive. To characterize the mechanism, we used multi-microsecond coarse-grained simulations with the MARTINI force field. These simulations show HβD-3 peptides can form oligomers on the surface of bacterial membrane and make anionic lipids (POPG) clustered. Furthermore, two kinds of regions (one is composed of pure POPG lipids, and the other is enriched in POPE lipids) are formed in the membrane; on the border of them, there are some obvious defects, which result in the membrane disruption. By contrast, the simulations also reveal that the contacts between the HβD-3 peptides and mammalian membrane are not stable. These results provide biophysical insights into HβD-3 selectivity and suggest a possible antimicrobial mechanism.

Parameterizing the Morse Potential for Coarse-Grained Modeling of Blood Plasma

Multiscale simulations of fluids such as blood represent a major computational challenge of coupling the disparate spatiotemporal scales between molecular and macroscopic transport phenomena characterizing such complex fluids. In this paper, a coarse-grained (CG) particle model is developed for simulating blood flow by modifying the Morse potential, traditionally used in Molecular Dynamics for modeling vibrating structures. The modified Morse potential is parameterized with effective mass scales for reproducing blood viscous flow properties, including density, pressure, viscosity, compressibility and characteristic flow dynamics of human blood plasma fluid. The parameterization follows a standard inverse-problem approach in which the optimal micro parameters are systematically searched, by gradually decoupling loosely correlated parameter spaces, to match the macro physical quantities of viscous blood flow. The predictions of this particle based multiscale model compare favorably to classic viscous flow solutions such as Counter-Poiseuille and Couette flows. It demonstrates that such coarse grained particle model can be applied to replicate the dynamics of viscous blood flow, with the advantage of bridging the gap between macroscopic flow scales and the cellular scales characterizing blood flow that continuum based models fail to handle adequately.

In vivo trp scanning of the small multidrug resistance protein EmrE confirms 3D structure models'

The quaternary structure of the homodimeric small multidrug resistance protein EmrE has been studied intensely over the past decade. Structural models derived from both two- and three-dimensional crystals show EmrE as an anti-parallel homodimer. However, the resolution of the structures is rather low and their relevance for the in vivo situation has been questioned. Here, we have challenged the available structural models by a comprehensive in vivo Trp scanning of all four transmembrane helices in EmrE. The results are in close agreement with the degree of lipid exposure of individual residues predicted from coarse-grained molecular dynamics simulations of the anti-parallel dimeric structure obtained by X-ray crystallography, strongly suggesting that the X-ray structure provides a good representation of the active in vivo form of EmrE.

Molecular mechanism of membrane binding of the GRP1 PH domain

The pleckstrin homology (PH) domain of the general receptor of phosphoinositides 1 (GRP1) protein selectively binds to a rare signaling phospholipid, phosphatidylinositol (3,4,5)-trisphosphate (PIP3), in the membrane. The specific PIP3 lipid docking of GRP1 PH domain is essential to protein cellular function and is believed to occur in a stepwise process, electrostatic-driven membrane association followed by the specific PIP3 binding. By a combination of all-atom molecular dynamics (MD) simulations, coarse-grained analysis, electron paramagnetic resonance (EPR) membrane docking geometry, and fluorescence resonance energy transfer (FRET) kinetic studies, we have investigated the search and bind process in the GRP1 PH domain at the molecular scale. We simulated the two membrane binding states of the GRP1 PH domain in the PIP3 search process, before and after the GRP1 PH domain docks with the PIP3 lipid. Our results suggest that the background anionic phosphatidylserine lipids, which constitute around one-fifth of the membrane by composition, play a critical role in the initial stages of recruiting protein to the membrane surface through non-specific electrostatic interactions. Our data also reveal a previously unseen transient membrane association mechanism that is proposed to enable a two-dimensional "hopping" search of the membrane surface for the rare PIP3 target lipid. We further modeled the PIP3-bound membrane-protein system using the EPR membrane docking structure for the MD simulations, quantitatively validating the EPR membrane docking structure and augmenting our understanding of the binding interface with atomic-level detail. Several observations and hypotheses reached from our MD simulations are also supported by experimental kinetic studies.

Molecular dynamics simulations of DPPC bilayers using "LIME", a new coarse-grained model

A new intermediate resolution model for phospholipids, LIME, designed for use with discontinuous molecular dynamics (DMD) simulations is presented. The implicit-solvent model was developed using a multiscale modeling approach in which the geometric and energetic parameters are obtained by collecting data from atomistic simulations of a system composed of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) molecules and explicit water. In the model, 14 coarse-grained sites that are classified as 1 of 6 types represent DPPC. DMD simulations performed on a random solution of DPPC resulted in the formation of a defect-free bilayer in less than 4 h. The bilayer formed quantitatively reproduces the main structural properties (e.g., area per lipid, bilayer thickness, bond order parameters) that are observed experimentally. In addition, the bilayer transitions from a liquid-crystalline phase to a tilted gel phase when the temperature is reduced. Transbilayer movement of a lipid from the bottom leaflet to the top leaflet is observed when the temperature is increased.

Can morphing methods predict intermediate structures?

Movement is crucial to the biological function of many proteins, yet crystallographic structures of proteins can give us only a static snapshot. The protein dynamics that are important to biological function often happen on a timescale that is unattainable through detailed simulation methods such as molecular dynamics as they often involve crossing high-energy barriers. To address this coarse-grained motion, several methods have been implemented as web servers in which a set of coordinates is usually linearly interpolated from an initial crystallographic structure to a final crystallographic structure. We present a new morphing method that does not extrapolate linearly and can therefore go around high-energy barriers and which can produce different trajectories between the same two starting points. In this work, we evaluate our method and other established coarse-grained methods according to an objective measure: how close a coarse-grained dynamics method comes to a crystallographically determined intermediate structure when calculating a trajectory between the initial and final crystal protein structure. We test this with a set of five proteins with at least three crystallographically determined on-pathway high-resolution intermediate structures from the Protein Data Bank. For simple hinging motions involving a small conformational change, segmentation of the protein into two rigid sections outperforms other more computationally involved methods. However, large-scale conformational change is best addressed using a nonlinear approach and we suggest that there is merit in further developing such methods.

The molecular face of lipid rafts in model membranes

Cell membranes contain a large number of different lipid species. Such a multicomponent mixture exhibits a complex phase behavior with regions of structural and compositional heterogeneity. Especially domains formed in ternary mixtures, composed of saturated and unsaturated lipids together with cholesterol, have received a lot of attention as they may resemble raft formation in real cells. Here we apply a simulation model to assess the molecular nature of these domains at the nanoscale, information that has thus far eluded experimental determination. We are able to show the spontaneous separation of a saturated phosphatidylcholine (PC)/unsaturated PC/cholesterol mixture into a liquid-ordered and a liquid-disordered phase with structural and dynamic properties closely matching experimental data. The near-atomic resolution of the simulations reveals remarkable features of both domains and the boundary domain interface. Furthermore, we predict the existence of a small surface tension between the monolayer leaflets that drives registration of the domains. At the level of molecular detail, raft-like lipid mixtures show a surprising face with possible implications for many cell membrane processes.