Multiscale molecular dynamics simulation approaches to the structure and dynamics of viruses

The structure and physical properties of a packaged bacteriophage particle

A string of nucleotides confined within a protein capsid contains all the instructions necessary to make a functional virus particle, a virion. Although the structure of the protein capsid is known for many virus species1,2, the three-dimensional organization of viral genomes has mostly eluded experimental probes3,4. Here we report all-atom structural models of an HK97 virion5, including its entire 39,732 base pair genome, obtained through multiresolution simulations. Mimicking the action of a packaging motor6, the genome was gradually loaded into the capsid. The structure of the packaged capsid was then refined through simulations of increasing resolution, which produced a 26 million atom model of the complete virion, including water and ions confined within the capsid. DNA packaging occurs through a loop extrusion mechanism7 that produces globally different configurations of the packaged genome and gives each viral particle individual traits. Multiple microsecond-long all-atom simulations characterized the effect of the packaged genome on capsid structure, internal pressure, electrostatics and diffusion of water, ions and DNA, and revealed the structural imprints of the capsid onto the genome. Our approach can be generalized to obtain complete all-atom structural models of other virus species, thereby potentially revealing new drug targets at the genome-capsid interface.

Molecular Dynamics Study of the Curvature-Driven Interactions between Carbon-Based Nanoparticles and Amino Acids

We researched the interaction between six representative carbon-based nanoparticles (CBNs) and 20 standard amino acids through all-atom molecular dynamics simulations. The six carbon-based nanoparticles are fullerene(C60), CNT55L3, CNT1010L3, CNT1515L3, CNT2020L3, and two-dimensional graphene (graphene33). Their curvatures decrease sequentially, and all of the CNTs are single-walled carbon nanotubes. We observed that as the curvature of CBNs decreases, the adsorption effect of the 20 amino acids with them has an increasing trend. In addition, we also used multi-dimensional clustering to analyze the adsorption effects of 20 amino acids on six carbon-based nanoparticles. We observed that the π-π interaction still plays an extremely important role in the adsorption of amino acids on carbon-based nanoparticles. Individual long-chain amino acids and "Benzene-like" Pro also have a strong adsorption effect on carbon-based nanoparticles.

Breathing and Tilting: Mesoscale Simulations Illuminate Influenza Glycoprotein Vulnerabilities

Influenza virus has resurfaced recently from inactivity during the early stages of the COVID-19 pandemic, raising serious concerns about the nature and magnitude of future epidemics. The main antigenic targets of influenza virus are two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA). Whereas the structural and dynamical properties of both glycoproteins have been studied previously, the understanding of their plasticity in the whole-virion context is fragmented. Here, we investigate the dynamics of influenza glycoproteins in a crowded protein environment through mesoscale all-atom molecular dynamics simulations of two evolutionary-linked glycosylated influenza A whole-virion models. Our simulations reveal and kinetically characterize three main molecular motions of influenza glycoproteins: NA head tilting, HA ectodomain tilting, and HA head breathing. The flexibility of HA and NA highlights antigenically relevant conformational states, as well as facilitates the characterization of a novel monoclonal antibody, derived from convalescent human donor, that binds to the underside of the NA head. Our work provides previously unappreciated views on the dynamics of HA and NA, advancing the understanding of their interplay and suggesting possible strategies for the design of future vaccines and antivirals against influenza.

Effects of External Perturbations on Protein Systems: A Microscopic View

Protein folding can be viewed as the origami engineering of biology resulting from the long process of evolution. Even decades after its recognition, research efforts worldwide focus on demystifying molecular factors that underlie protein structure-function relationships; this is particularly relevant in the era of proteopathic disease. A complex co-occurrence of different physicochemical factors such as temperature, pressure, solvent, cosolvent, macromolecular crowding, confinement, and mutations that represent realistic biological environments are known to modulate the folding process and protein stability in unique ways. In the current review, we have contextually summarized the substantial efforts in unveiling individual effects of these perturbative factors, with major attention toward bottom-up approaches. Moreover, we briefly present some of the biotechnological applications of the insights derived from these studies over various applications including pharmaceuticals, biofuels, cryopreservation, and novel materials. Finally, we conclude by summarizing the challenges in studying the combined effects of multifactorial perturbations in protein folding and refer to complementary advances in experiment and computational techniques that lend insights to the emergent challenges.

Breathing and tilting: mesoscale simulations illuminate influenza glycoprotein vulnerabilities

Influenza virus has resurfaced recently from inactivity during the early stages of the COVID-19 pandemic, raising serious concerns about the nature and magnitude of future epidemics. The main antigenic targets of influenza virus are two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA). Whereas the structural and dynamical properties of both glycoproteins have been studied previously, the understanding of their plasticity in the whole-virion context is fragmented. Here, we investigate the dynamics of influenza glycoproteins in a crowded protein environment through mesoscale all-atom molecular dynamics simulations of two evolutionary-linked glycosylated influenza A whole-virion models. Our simulations reveal and kinetically characterize three main molecular motions of influenza glycoproteins: NA head tilting, HA ectodomain tilting, and HA head breathing. The flexibility of HA and NA highlights antigenically relevant conformational states, as well as facilitates the characterization of a novel monoclonal antibody, derived from human convalescent plasma, that binds to the underside of the NA head. Our work provides previously unappreciated views on the dynamics of HA and NA, advancing the understanding of their interplay and suggesting possible strategies for the design of future vaccines and antivirals against influenza.

Canine Morbillivirus from Colombian Lineage Exhibits In Silico and In Vitro Potential to Infect Human Cells

Canine morbillivirus (CDV) is a viral agent that infects domestic dogs and a vast array of wildlife species. It belongs to the Paramyxoviridae family, genus Morbillivirus, which is shared with the Measles virus (MeV). Both viruses employ orthologous cellular receptors, SLAM in mononuclear cells and Nectin-4 in epithelial cells, to enter the cells. Although CDV and MeV hemagglutinin (H) have similar functions in viral pathogenesis and cell tropism, the potential interaction of CDV-H protein with human cellular receptors is still uncertain. Considering that CDV is classified as a multi-host pathogen, the potential risk of CDV transmission to humans has not been fully discarded. In this study, we aimed to evaluate both in silico and in vitro, whether there is a cross-species transmission potential from CDV to humans. To accomplish this, the CDV-H protein belonging to the Colombian lineage was modelled. After model validations, molecular docking and molecular dynamics simulations were carried out between Colombian CDV-H protein and canine and human cellular receptors to determine different aspects of the protein-protein interactions. Moreover, cell lines expressing orthologous cellular receptors, with both reference and wild-type CDV strains, were conducted to determine the CDV cross-species transmission potential from an in vitro model. This in silico and in vitro approach suggests the possibility that CDV interacts with ortholog human SLAM (hSLAM) and human Nectin-4 receptors to infect human cell lines, which could imply a potential cross-species transmission of CDV from dogs to humans.

Computational modelling of flavivirus dynamics: The ins and outs

Enveloped viruses such as the flaviviruses represent a significant burden to human health around the world, with hundreds of millions of people each year affected by dengue alone. In an effort to improve our understanding of the molecular basis for the infective mechanisms of these viruses, extensive computational modelling approaches have been applied to elucidate their conformational dynamics. Multiscale protocols have been developed to simulate flavivirus envelopes in close accordance with biophysical data, in particular derived from cryo-electron microscopy, enabling high-resolution refinement of their structures and elucidation of the conformational changes associated with adaptation both to host environments and to immunological factors such as antibodies. Likewise, integrative modelling efforts combining data from biophysical experiments and from genome sequencing with chemical modification are providing unparalleled insights into the architecture of the previously unresolved nucleocapsid complex. Collectively, this work provides the basis for the future rational design of new antiviral therapeutics and vaccine development strategies targeting enveloped viruses.

The analysis of the effects of high hydrostatic pressure (HHP) on amylose molecular conformation at atomic level based on molecular dynamics simulation

For more effective using of HHP (high hydrostatic pressure) in starch processing, in this study, molecular dynamics simulation was used to explore the effects of pressure on amylose molecular conformation at the atomic level. The results shown that, firstly, high pressure decreased the intramolecular hydrogen bonds and increased the amylose-solvent hydrogen bonds, which is consistent with the process of high pressure starch gelatinization. Secondly, high pressure made amylose polymers more "stout". Meanwhile, high pressure decreased the angle of α-1,4 glycosidic linkage and increased the dihedral angles of α-1,4 glycosidic linkage, which indicates that pressure has obvious effects on amylose molecular conformation. Thirdly, high pressure made amylose polymers more stable. Moreover, in view of the results of energies, HHP may have an opposite gelatinization mechanism to heating. The results may be complementary to the existing experimental phenomena and provide theoretical guidance value for the using of HHP in starch processing.

Characterization of the adipogenic protein E4orf1 from adenovirus 36 through an in silico approach

Adenovirus 36 (Ad-36) is related to human obesity due to its adipogenic activity mediated by the early 4 open reading frame 1 (E4orf1) protein. Mechanisms underlying the adipogenic effect of E4orf1 are not completely understood; however, the proliferation and differentiation of fat cells are increased through the activation of the phosphatidyl inositol 3 kinase pathway by binding proteins containing PDZ domain. This study characterized E4orf1 tridimensional structure and analyzed its interactions with PDZ domain-containing proteins in order to provide new information about the behavior of this viral protein and its targets, which could provide an interesting druggable target for obesity-related cardiometabolic alterations. In silico strategies such as homology modeling, docking, and molecular dynamics (MD) were used to study the interaction of E4orf1 with five PDZ domains of disk large homolog 1 (PDZ-1 and PDZ-2), membrane-associated guanylate kinase 1 (PDZ-3), and multi-PDZ domain protein 1 (PDZ-7 and PDZ-10). Mutagenesis analysis of selected residues was performed to evaluate their effects on the stabilization of E4orf1:PDZ complexes. MD simulations showed that the E4orf1:PDZ10 complex was more stable than the others ones. The highly hydrophobic residues at the C-terminal region (114-125) of the E4orf1 are essential in the initial phase stabilization of the complexes. Moreover, the residues 80-85 in the core region contribute to longer stabilization of the E4orf1:PDZ10 complex, a result that was confirmed by in silico mutagenesis. In conclusion, E4orf1 forms a stable complex with PDZ10 domain, and the residues 80-85 are of particular importance. The characterization of E4orf1 interactions with PDZ domains provides an initial approach to discover druggable targets for Ad-36-induced obesity.

Comparison of Different Chitosan Lipid Nanoparticles for Improved Ophthalmic Tetrandrine Delivery: Formulation, Characterization, Pharmacokinetic and Molecular Dynamics Simulation

In this study, three different chitosan, namely carboxymethyl chitosan (CMC), hydroxypropyl chitosan (HPC) and trimethyl chitosan (TMC) were used as cationic materials to prepare tetrandrine lipid nanoparticles (TET-LNPs) for the treatment of glaucoma. In vitro drug release and pre-corneal retention were used to select the optimal chitosan. In vitro drug release curves of three kinds of LNPs showed a sustained release and TMC-TET-LNPs were the slowest. Moreover, compared with CMC-TET-LNPs and HPC-TET-LNPs, TMC-TET-LNPs had longer corneal retention time. Afterwards, the characteristics of TMC-TET-LNPs were investigated. The ocular irritation study revealed no sign of irritation in rabbit eyes. The pharmacokinetic studies showed that the area under the curve of TMC-TET-LNPs was increased by 2.03 times than TET solution (p < 0.01). Furthermore, the drug biofilm interactions were evaluated by molecular dynamics (MD) simulation. In MD simulation, the strong hydrophobic group of TET interacted with the tail of POPC, making it hard to enter the hydrophobic region of the membrane, thereby restricting TET ocular bioavailability. The experiments and MD simulation indicated that TMC-TET-LNPs had great potential for ocular administration and MD simulation could predict transmembrane transport of drugs.

Binding mechanism of the matrix domain of HIV-1 gag on lipid membranes

Specific protein-lipid interactions are critical for viral assembly. We present a molecular dynamics simulation study on the binding mechanism of the membrane targeting domain of HIV-1 Gag protein. The matrix (MA) domain drives Gag onto the plasma membrane through electrostatic interactions at its highly-basic-region (HBR), located near the myristoylated (Myr) N-terminus of the protein. Our study suggests Myr insertion is involved in the sorting of membrane lipids around the protein-binding site to prepare it for viral assembly. Our realistic membrane models confirm interactions with PIP₂ and PS lipids are highly favored around the HBR and are strong enough to keep the protein bound even without Myr insertion. We characterized Myr insertion events from microsecond trajectories and examined the membrane response upon initial membrane targeting by MA. Insertion events only occur with one of the membrane models, showing a combination of surface charge and internal membrane structure modulate this process.

Trimethyl chitosan nanoparticles for ocular baicalein delivery: Preparation, optimization, in vitro evaluation, in vivo pharmacokinetic study and molecular dynamics simulation

To improve ocular bioavailability of baicalein (BAI), trimethyl chitosan coated lipid nanoparticles of baicalein (TMC-BAI-LNPs) were prepared, optimized and characterized. The properties of TMC-BAI-LNPs such as morphology, particle size, zeta potential and fourier transform infrared spectroscopy were investigated. Additionally, molecular dynamics simulation was applied as a new method to evaluate drug-biological membrane interactions. Transmission electron microscopy showed that the LNPs were approximately spherical in shape with a smooth surface. TMC-BAI-LNPs had a particle size of 162.8 nm, a positive surface charge with a zeta potential of 26.6 mV. The entrapment efficiency and drug loading values of BAI in the formulation were 90.65% and 2.04%, respectively. Moreover, in vitro drug release revealed that TMC-BAI-LNPs had a sustained release effect. In vivo studies indicated TMC-BAI-LNPs had no ocular irritation and the AUC of TMC-BAI-LNPs was 3.17-fold than that of the control (p < 0.01). Molecular dynamics simulation data showed that BAI had a poor membrane permeability, which limited the ocular bioavailability. The results indicated that TMC-BAI-LNPs might open up a new avenue for ocular administration. Furthermore, molecular dynamics simulation could predict permeability of drugs.

Mesoscale All-Atom Influenza Virus Simulations Suggest New Substrate Binding Mechanism

Influenza virus circulates in human, avian, and swine hosts, causing seasonal epidemic and occasional pandemic outbreaks. Influenza neuraminidase, a viral surface glycoprotein, has two sialic acid binding sites. The catalytic (primary) site, which also binds inhibitors such as oseltamivir carboxylate, is responsible for cleaving the sialic acid linkages that bind viral progeny to the host cell. In contrast, the functional annotation of the secondary site remains unclear. Here, we better characterize these two sites through the development of an all-atom, explicitly solvated, and experimentally based integrative model of the pandemic influenza A H1N1 2009 viral envelope, containing ∼160 million atoms and spanning ∼115 nm in diameter. Molecular dynamics simulations of this crowded subcellular environment, coupled with Markov state model theory, provide a novel framework for studying realistic molecular systems at the mesoscale and allow us to quantify the kinetics of the neuraminidase 150-loop transition between the open and closed states. An analysis of chloride ion occupancy along the neuraminidase surface implies a potential new role for the neuraminidase secondary site, wherein the terminal sialic acid residues of the linkages may bind before transfer to the primary site where enzymatic cleavage occurs. Altogether, our work breaks new ground for molecular simulation in terms of size, complexity, and methodological analyses of the components. It also provides fundamental insights into the understanding of substrate recognition processes for this vital influenza drug target, suggesting a new strategy for the development of anti-influenza therapeutics.

Investigating the stability of dengue virus envelope protein dimer using well-tempered metadynamics simulations

We explored the stability of the dengue virus envelope (E) protein dimer since it is widely assumed that the E protein dimer is stabilized by drug ligands or antibodies in an acidic environment, neutralizing the virus's ability to fuse with human cells. During this process, a large conformational change of the E protein dimer is required. We performed Molecular Dynamics simulations to mimic the conformational change and stability of the dimer in neutral and acidic conditions with the well-tempered metadynamics method. Furthermore, as a few neutralizing antibodies discovered from dengue patients were reported, we used the same simulation method to examine the influence of a selected antibody on the dimer stability in both neutral and acidic conditions. We also investigated the antibody's influence on a point-mutated E protein that had been reported to interrupt the protein-antibody interaction and result in more than 95% loss of the antibody's binding ability. Our simulation results are highly consistent with the experimental conclusion that binding of the antibody to the E protein dimer neutralizes the virus, especially in a low pH condition, while the mutation of W101A or N153A significantly reduces the antibody's ability in stabilizing the E protein dimer. We demonstrate that well-tempered metadynamics can be used to accurately explore the antibody's interaction on large protein complexes such as the E protein dimer, and the computational approach in this work is promising in future antibody development.

Emerging Diversity in Lipid-Protein Interactions

Membrane lipids interact with proteins in a variety of ways, ranging from providing a stable membrane environment for proteins to being embedded in to detailed roles in complicated and well-regulated protein functions. Experimental and computational advances are converging in a rapidly expanding research area of lipid-protein interactions. Experimentally, the database of high-resolution membrane protein structures is growing, as are capabilities to identify the complex lipid composition of different membranes, to probe the challenging time and length scales of lipid-protein interactions, and to link lipid-protein interactions to protein function in a variety of proteins. Computationally, more accurate membrane models and more powerful computers now enable a detailed look at lipid-protein interactions and increasing overlap with experimental observations for validation and joint interpretation of simulation and experiment. Here we review papers that use computational approaches to study detailed lipid-protein interactions, together with brief experimental and physiological contexts, aiming at comprehensive coverage of simulation papers in the last five years. Overall, a complex picture of lipid-protein interactions emerges, through a range of mechanisms including modulation of the physical properties of the lipid environment, detailed chemical interactions between lipids and proteins, and key functional roles of very specific lipids binding to well-defined binding sites on proteins. Computationally, despite important limitations, molecular dynamics simulations with current computer power and theoretical models are now in an excellent position to answer detailed questions about lipid-protein interactions.

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.

Why Enveloped Viruses Need Cores-The Contribution of a Nucleocapsid Core to Viral Budding

During the lifecycle of many enveloped viruses, a nucleocapsid core buds through the cell membrane to acquire an outer envelope of lipid membrane and viral glycoproteins. However, the presence of a nucleocapsid core is not required for assembly of infectious particles. To determine the role of the nucleocapsid core, we develop a coarse-grained computational model with which we investigate budding dynamics as a function of glycoprotein and nucleocapsid interactions, as well as budding in the absence of a nucleocapsid. We find that there is a transition between glycoprotein-directed budding and nucleocapsid-directed budding that occurs above a threshold strength of nucleocapsid interactions. The simulations predict that glycoprotein-directed budding leads to significantly increased size polydispersity and particle polymorphism. This polydispersity can be explained by a theoretical model accounting for the competition between bending energy of the membrane and the glycoprotein shell. The simulations also show that the geometry of a budding particle leads to a barrier to subunit diffusion, which can result in a stalled, partially budded state. We present a phase diagram for this and other morphologies of budded particles. Comparison of these structures against experiments could establish bounds on whether budding is directed by glycoprotein or nucleocapsid interactions. Although our model is motivated by alphaviruses, we discuss implications of our results for other enveloped viruses.

Multiscale Modeling and Simulation Approaches to Lipid-Protein Interactions

Lipid membranes play a crucial role in living systems by compartmentalizing biological processes and forming a barrier between these processes and the environment. Naturally, a large apparatus of biomolecules is responsible for construction, maintenance, transport, and degradation of these lipid barriers. Additional classes of biomolecules are tasked with transport of specific substances or transduction of signals from the environment across lipid membranes. In this article, we intend to describe a set of techniques that enable one to build accurate models of lipid systems and their associated proteins, and to simulate their dynamics over a variety of time and length scales. We discuss the methods and challenges that allow us to derive structural, mechanistic, and thermodynamic information from these models. We also show how these models have recently been applied in research to study some of the most complex lipid-protein systems to date, including bacterial and viral envelopes, neuronal membranes, and mammalian signaling systems.

Single-molecule studies of flavivirus envelope dynamics: Experiment and computation

Flaviviruses are simple enveloped viruses exhibiting complex structural and functional heterogeneities. Decades of research have provided crucial basic insights, antiviral medication and moderately successful gene therapy trials. The most infectious particle is, however, not always the most abundant one in a population, questioning the utility of classic ensemble-averaging virology approaches. Indeed, viral replication is often not particularly efficient, prone to errors or containing parallel routes. Here, we review different single-molecule sensitive fluorescence methods that are employed to investigate flaviviruses. In particular, we review how (i) time-resolved Förster resonance energy transfer (trFRET) was applied to probe dengue envelope conformations; (ii) FRET-fluorescence correlation spectroscopy to investigate dengue envelope intrinsic dynamics and (iii) single particle tracking to follow the path of dengue viruses in cells. We also discuss how such methods may be supported by molecular dynamics (MD) simulations over a range of spatio-temporal scales, to provide complementary data on the structure and dynamics of flaviviral systems. We describe recent improvements in multiscale MD approaches that allowed the simulation of dengue particle envelopes in near-atomic resolution. We hope this review is an incentive for setting up and applying similar single-molecule studies and combine them with MD simulations to investigate structural dynamics of entire flavivirus particles over the nanosecond-to-millisecond time-scale and follow viruses during infection in cells over milliseconds to minutes.

Electrostatics-Driven Inflation of Elastic Icosahedral Shells as a Model for Swelling of Viruses

We develop a clear theoretical description of radial swelling in virus-like particles that delineates the importance of electrostatic contributions to swelling in the absence of any conformational changes. The model couples the elastic parameters of the capsid-represented as a continuous elastic shell-to the electrostatic pressure acting on it. We show that different modifications of the electrostatic interactions brought about by, for instance, changes in pH or solution ionic strength are often sufficient to achieve the experimentally observed swelling (∼10% of the capsid radius). Additionally, we derive analytical expressions for the electrostatics-driven radial swelling of virus-like particles that enable one to quickly estimate the magnitudes of physical quantities involved.

Lipid-Protein Interactions Are Unique Fingerprints for Membrane Proteins

Cell membranes contain hundreds of different proteins and lipids in an asymmetric arrangement. Our current understanding of the detailed organization of cell membranes remains rather elusive, because of the challenge to study fluctuating nanoscale assemblies of lipids and proteins with the required spatiotemporal resolution. Here, we use molecular dynamics simulations to characterize the lipid environment of 10 different membrane proteins. To provide a realistic lipid environment, the proteins are embedded in a model plasma membrane, where more than 60 lipid species are represented, asymmetrically distributed between the leaflets. The simulations detail how each protein modulates its local lipid environment in a unique way, through enrichment or depletion of specific lipid components, resulting in thickness and curvature gradients. Our results provide a molecular glimpse of the complexity of lipid-protein interactions, with potentially far-reaching implications for our understanding of the overall organization of real cell membranes.

The Renormalization Group and Its Applications to Generating Coarse-Grained Models of Large Biological Molecular Systems

Understanding the dynamics of biomolecules is the key to understanding their biological activities. Computational methods ranging from all-atom molecular dynamics simulations to coarse-grained normal-mode analyses based on simplified elastic networks provide a general framework to studying these dynamics. Despite recent successes in studying very large systems with up to a 100,000,000 atoms, those methods are currently limited to studying small- to medium-sized molecular systems due to computational limitations. One solution to circumvent these limitations is to reduce the size of the system under study. In this paper, we argue that coarse-graining, the standard approach to such size reduction, must define a hierarchy of models of decreasing sizes that are consistent with each other, i.e., that each model contains the information of the dynamics of its predecessor. We propose a new method, Decimate, for generating such a hierarchy within the context of elastic networks for normal-mode analysis. This method is based on the concept of the renormalization group developed in statistical physics. We highlight the details of its implementation, with a special focus on its scalability to large systems of up to millions of atoms. We illustrate its application on two large systems, the capsid of a virus and the ribosome translation complex. We show that highly decimated representations of those systems, containing down to 1% of their original number of atoms, still capture qualitatively and quantitatively their dynamics. Decimate is available as an OpenSource resource.