Computational virology: From the inside out

The Advantage of Using Immunoinformatic Tools on Vaccine Design and Development for Coronavirus

After the outbreak of SARS-CoV-2 by the end of 2019, the vaccine development strategies became a worldwide priority. Furthermore, the appearances of novel SARS-CoV-2 variants challenge researchers to develop new pharmacological or preventive strategies. However, vaccines still represent an efficient way to control the SARS-CoV-2 pandemic worldwide. This review describes the importance of bioinformatic and immunoinformatic tools (in silico) for guide vaccine design. In silico strategies permit the identification of epitopes (immunogenic peptides) which could be used as potential vaccines, as well as nonacarriers such as: vector viral based vaccines, RNA-based vaccines and dendrimers through immunoinformatics. Currently, nucleic acid and protein sequential as well structural analyses through bioinformatic tools allow us to get immunogenic epitopes which can induce immune response alone or in complex with nanocarriers. One of the advantages of in silico techniques is that they facilitate the identification of epitopes, while accelerating the process and helping to economize some stages of the development of safe vaccines.

RNAvigator: A Pipeline to Identify Candidates for Functional RNA Structure Elements

Identifying structural elements in long and complex RNAs, such as long non-coding and RNA viruses, can shed light on the functionality and mechanisms of such RNAs. Here we present RNAvigator, a tool able to identify elements of structural importance by using experimental SHAPE data or SHAPE-like predictions in conjunction with stability and entropy assessments. RNAvigator recognizes regions that are the most stable, unambiguous, and structured on RNA molecules, and thus potentially functional. When relying on predictions, RNAvigator uses the CROSS algorithm, a neural network trained on experimental data that achieved an AUC of 0.74 on hepatitis C virus SHAPE-MaP data and which was able to improve the predictive power of Superfold. By using RNAvigator, we can identify known functional regions on the complete hepatitis C virus genome, including the regulatory regions CRE and IRES, and the 3’ UTR of dengue virus, a region known for the presence of structural elements essential for its replication, and functional regions of long non-coding RNAs such as XIST and HOTAIR. We envision that RNAvigator will be a useful tool for studying long and complex RNA molecules using known chemical probing data or, if they are not available, by employing predicted profiles.

Model architectures for bacterial membranes

The complex composition of bacterial membranes has a significant impact on the understanding of pathogen function and their development towards antibiotic resistance. In addition to the inherent complexity and biosafety risks of studying biological pathogen membranes, the continual rise of antibiotic resistance and its significant economical and clinical consequences has motivated the development of numerous in vitro model membrane systems with tuneable compositions, geometries, and sizes. Approaches discussed in this review include liposomes, solid-supported bilayers, and computational simulations which have been used to explore various processes including drug-membrane interactions, lipid-protein interactions, host–pathogen interactions, and structure-induced bacterial pathogenesis. The advantages, limitations, and applicable analytical tools of all architectures are summarised with a perspective for future research efforts in architectural improvement and elucidation of resistance development strategies and membrane-targeting antibiotic mechanisms.

Molecular dynamics of the viral life cycle: progress and prospects

Molecular dynamics (MD) simulations across spatiotemporal resolutions are widely applied to study viruses and represent the central technique uniting the field of computational virology. We discuss the progress of MD in elucidating the dynamics of the viral life cycle, including the status of modeling intact extracellular virions and leveraging advanced simulations to mimic active life cycle processes. We further remark on the prospects of MD for continued contributions to the basic science characterization of viruses, especially given the increasing availability of high-quality experimental data and supercomputing power. Overall, integrative computational methods that are closely guided by experiments are unmatched in the level of detail they provide, enabling-now and in the future-new discoveries relevant to thwarting viral infection.

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.

Algorithm to minimize MPI communications in the parallelized fast multipole method combined with molecular dynamics calculations

In the era of exascale supercomputers, large-scale, and long-time molecular dynamics (MD) calculations are expected to make breakthroughs in various fields of science and technology. Here, we propose a new algorithm to improve the parallelization performance of message passing interface (MPI)-communication in the MPI-parallelized fast multipole method (FMM) combined with MD calculations under three-dimensional periodic boundary conditions. Our approach enables a drastic reduction in the amount of communication data, including the atomic coordinates and multipole coefficients, both of which are required to calculate the electrostatic interaction by using the FMM. In communications of multipole coefficients, the reduction rate of communication data in the new algorithm relative to the amount of data in the conventional one increases as both the number of FMM levels and the number of MPI processes increase. The aforementioned rate increase could exceed 50% as the number of MPI processes becomes larger for very large systems. The proposed algorithm, named the minimum-transferred data (MTD) method, should enable large-scale and long-time MD calculations to be calculated efficiently, under the condition of massive MPI-parallelization on exascale supercomputers.

Molecular determinants of Ebola nucleocapsid stability from molecular dynamics simulations

Ebola virus (EBOV) is a human pathogen with the ability to cause hemorrhagic fever and bleeding diathesis in hosts. The life cycle of EBOV depends on its nucleocapsid. The Ebola nucleocapsid consists of a helical assembly of nucleoproteins (NPs) encapsidating single-stranded viral RNA (ssRNA). Knowledge of the molecular determinants of Ebola nucleocapsid stability is essential for the development of therapeutics against EBOV. However, large degrees of freedom associated with the Ebola nucleocapsid helical assembly pose a computational challenge, thereby limiting the previous simulation studies to the level of monomers. In the present work, we have performed all atom molecular dynamics (MD) simulations of the helical assembly of EBOV nucleoproteins in the absence and presence of ssRNA. We found that ssRNA is essential for maintaining structural integrity of the nucleocapsid. Other molecular determinants observed to stabilize the nucleocapsid include NP-RNA and NP-NP interactions and ion distributions. Additionally, the structural and dynamical behavior of the nucleocapsid monomer depends on its position in the helical assembly. NP monomers present on the longitudinal edges of the helical tube are more exposed, flexible, and have weaker NP-NP interactions than those residing in the center. This work provides key structural features stabilizing the nucleocapsid that may serve as therapeutic targets.

Cellular pathways of recombinant adeno-associated virus production for gene therapy

Recombinant adeno-associated viruses (rAAVs) are among the most important vectors for in vivo gene therapies. With the rapid development of gene therapy, current rAAV manufacturing capacity faces a challenge to meet the emerging demand for these therapies in the future. To examine the bottlenecks in rAAV production during cell culture, we focus here on an analysis of cellular pathways of rAAV production, based on an overview of assembly mechanisms first in the wild-type (wt) AAV replication and then in the common methods of rAAV production. The differences analyzed between the wild-type and recombinant systems provide insights into the mechanistic differences that may correlate with viral productivity. Based on these analyses, we identify potential barriers to high productivity of rAAV and discuss future directions for improvement to meet the emerging needs set by the growth of rAAV-based therapy and the needs of patients.

Simulating realistic membrane shapes

Biological membranes exhibit diversity in their shapes and complexity in chemical compositions that are linked to many cellular functions. These two central features of biomembranes have been the subject of numerous simulation studies, using a diverse range of computational techniques. Currently, the field is able to capture this complexity at increasing levels of realism and connect the microscopic view on protein-lipid interactions to cellular morphologies at the level of entire organelles. Here we highlight recent advances in this topic, identify current bottlenecks, and sketch possible ways ahead.

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.

Frustration and Direct-Coupling Analyses to Predict Formation and Function of Adeno-Associated Virus

Adeno-associated virus (AAV) is a promising gene therapy vector because of its efficient gene delivery and relatively mild immunogenicity. To improve delivery target specificity, researchers use combinatorial and rational library design strategies to generate novel AAV capsid variants. These approaches frequently propose high proportions of nonforming or noninfective capsid protein sequences that reduce the effective depth of synthesized vector DNA libraries, thereby raising the discovery cost of novel vectors. We evaluated two computational techniques for their ability to estimate the impact of residue mutations on AAV capsid protein-protein interactions and thus predict changes in vector fitness, reasoning that these approaches might inform the design of functionally enriched AAV libraries and accelerate therapeutic candidate identification. The Frustratometer computes an energy function derived from the energy landscape theory of protein folding. Direct-coupling analysis (DCA) is a statistical framework that captures residue coevolution within proteins. We applied the Frustratometer to select candidate protein residues predicted to favor assembled or disassembled capsid states, then predicted mutation effects at these sites using the Frustratometer and DCA. Capsid mutants were experimentally assessed for changes in virus formation, stability, and transduction ability. The Frustratometer-based metric showed a counterintuitive correlation with viral stability, whereas a DCA-derived metric was highly correlated with virus transduction ability in the small population of residues studied. Our results suggest that coevolutionary models may be able to elucidate complex capsid residue-residue interaction networks essential for viral function, but further study is needed to understand the relationship between protein energy simulations and viral capsid metastability.

Forecasting the timeframe of 2019-nCoV and human cells interaction with reverse engineering

In December 2019, an atypical pneumonia invaded the city of Wuhan, China, and the causative agent of this disease turned out to be a new coronavirus. In January 2020, the World Health Organization named the new coronavirus 2019-nCoV and subsequently it is referred to as SARS-CoV2 and the related disease as CoViD-19 (Lai et al., 2020). Very quickly, the epidemic led to a pandemic and it is now a worldwide emergency requiring the creation of new antiviral therapies and a related vaccine. The purpose of this article is to review and investigate further the molecular mechanism by which the SARS-CoV2 virus infection proceeds via the formation of a hetero-trimer between its protein S, the ACE2 receptor and the B0AT1 protein, which is the "entry receptor" for the infection process involving membrane fusion (Li et al., 2003). A reverse engineering process uses the formalism of the Hill function to represent the functions related to the dynamics of the biochemical interactions of the viral infection process. Then, using a logical evaluation of viral density that measures the rate at which the cells are hijacked by the virus (and they provide a place for the virus to replicate) and considering the "time delay" given by the interaction between cell and virus, the expected duration of the incubation period is predicted. The conclusion is that the density of the virus varies from the "exposure time" to the "interaction time" (virus-cells). This model can be used both to evaluate the infectious condition and to analyze the incubation period.

BACKGROUND

The ongoing threat of the new coronavirus SARS-CoV2 pandemic is alarming and strategies for combating infection are highly desired. This RNA virus belongs to the β-coronavirus genus and is similar in some features to SARS-CoV. Currently, no vaccine or approved medical treatment is available. The complex dynamics of the rapid spread of this virus can be demonstrated with the aid of a computational framework.

METHODS

A mathematical model based on the principles of cell-virus interaction is developed in this manuscript. The amino acid sequence of S proein and its interaction with the ACE-2 protein is mimicked with the aid of Hill function. The mathematical model with delay is solved with the aid of numerical solvers and the parametric values are obtained with the help of MCMC algorithm.

RESULTS

A delay differential equation model is developed to demonstrate the dynamics of target cells, infected cells and the SARS-CoV2. The important parameters and coefficients are demonstrated with the aid of numerical computations. The resulting thresholds and forecasting may prove to be useful tools for future experimental studies and control strategies.

CONCLUSIONS

From the analysis, I is concluded that control strategy via delay is a promising technique and the role of Hill function formalism in control strategies can be better interpreted in an inexpensive manner with the aid of a theoretical framework.

Scalable Analysis of Authentic Viral Envelopes on FRONTERA

Enveloped viruses, such as SARS-CoV-2, infect cells via fusion of their envelope with the host membrane. By employing molecular simulations to characterize viral envelopes, researchers can gain insights into key determinants of infection. Here, the Frontera supercomputer is leveraged for large-scale modeling and analysis of authentic viral envelopes, whose lipid compositions are complex and realistic. Visual Molecular Dynamics (VMD) with support for MPI is employed, overcoming previous computational limitations and enabling investigation into virus biology at an unprecedented scale. The techniques applied here to an authentic HIV-1 envelope at two levels of spatial resolution (29 million particles and 280 million atoms) are broadly applicable to the study of other viruses. The authors are actively employing these techniques to develop and characterize an authentic SARS-CoV-2 envelope. A general framework for carrying out scalable analysis of simulation trajectories on Frontera is presented, expanding the utility of the machine in humanity’s ongoing fight against infectious diseases.

Coronavirus through Delaware's Computational Microscope

The Perilla/Hadden-Perilla research team at the University of Delaware presents an overview of computational structural biology, their efforts to model the SARS-CoV-2 viral particle, and their perspective on how their work and training endeavors can contribute to public health.

Computer simulations of protein-membrane systems

The interactions between proteins and membranes play critical roles in signal transduction, cell motility, and transport, and they are involved in many types of diseases. Molecular dynamics (MD) simulations have greatly contributed to our understanding of protein-membrane interactions, promoted by a dramatic development of MD-related software, increasingly accurate force fields, and available computer power. In this chapter, we present available methods for studying protein-membrane systems with MD simulations, including an overview about the various all-atom and coarse-grained force fields for lipids, and useful software for membrane simulation setup and analysis. A large set of case studies is discussed.

High-Performance Analysis of Biomolecular Containers to Measure Small-Molecule Transport, Transbilayer Lipid Diffusion, and Protein Cavities

Compartmentalization is a central theme in biology. Cells are composed of numerous membrane-enclosed structures, evolved to facilitate specific biochemical processes; viruses act as containers of genetic material, optimized to drive infection. Molecular dynamics simulations provide a mechanism to study biomolecular containers and the influence they exert on their environments; however, trajectory analysis software generally lacks knowledge of container interior versus exterior. Further, many relevant container analyses involve large-scale particle tracking endeavors, which may become computationally prohibitive with increasing system size. Here, a novel method based on 3-D ray casting is presented, which rapidly classifies the space surrounding biomolecular containers of arbitrary shape, enabling fast determination of the identities and counts of particles (e.g., solvent molecules) found inside and outside. The method is broadly applicable to the study of containers and enables high-performance characterization of properties such as solvent density, small-molecule transport, transbilayer lipid diffusion, and topology of protein cavities. The method is implemented in VMD, a widely used simulation analysis tool that supports personal computers, clouds, and parallel supercomputers, including ORNL's Summit and Titan and NCSA's Blue Waters, where the method can be employed to efficiently analyze trajectories encompassing millions of particles. The ability to rapidly characterize the spatial relationships of particles relative to a biomolecular container over many trajectory frames, irrespective of large particle counts, enables analysis of containers on a scale that was previously unfeasible, at a level of accuracy that was previously unattainable.

Mesoscale model of the assembly and cross-linking of HPV virus-like particles

We present a novel kinetic Monte Carlo model to simulate the real process time-scale of the assembly of Human Papillomavirus (HPV) virus-like particles (VLPs) incorporating the formation of intercapsomeric disulfide bonds. The objective was to develop insights into the underlying mechanisms of HPV VLP assembly and cross-linking during in vitro production of the HPV vaccine. The model integrates actual experimental data and detailed information of VLP geometrical structure in microscopic mechanistic steps. The principal novelty of this model is in the concurrent simulation of VLP assembly and cross-linking including a variable for spatial angular arrangement of capsomeres during their assembly that affects the overall rates of VLP assembly and cross-linking. The cross-linking modeled by using the mechanistic probability rules between involved cysteine residues. The model was utilized to better understand the actual process data and check on the hypothesis related to factors affecting the rates of HPV growth and maturation.

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.

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.

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.

All-atom virus simulations

The constant threat of viral disease can be combated by the development of novel vaccines and therapeutics designed to disrupt key features of virus structure or infection cycle processes. Such development relies on high-resolution characterization of viruses and their dynamical behaviors, which are often challenging to obtain solely by experiment. In response, all-atom molecular dynamics simulations are widely leveraged to study the structural components of viruses, leading to some of the largest simulation endeavors undertaken to date. The present work reviews exemplary all-atom simulation work on viruses, as well as progress toward simulating entire virions.

An Integrative Approach to Virus-Host Protein-Protein Interactions

Since cell regulation and protein expression can be dramatically altered upon infection by viruses, studying the mechanisms by which viruses infect cells and the regulatory networks they disrupt is essential to understanding viral pathogenicity. This line of study can also lead to discoveries about the workings of host cells themselves. Computational methods are rapidly being developed to investigate viral-host interactions, and here we highlight recent methods and the insights that they have revealed so far, with a particular focus on methods that integrate different types of data. We also review the challenges of working with viruses compared with traditional cellular biology, and the limitations of current experimental and informatics methods.

Instant Construction and Visualization of Crowded Biological Environments

We present the first approach to integrative structural modeling of the biological mesoscale within an interactive visual environment. These complex models can comprise up to millions of molecules with defined atomic structures, locations, and interactions. Their construction has previously been attempted only within a non-visual and non-interactive environment. Our solution unites the modeling and visualization aspect, enabling interactive construction of atomic resolution mesoscale models of large portions of a cell. We present a novel set of GPU algorithms that build the basis for the rapid construction of complex biological structures. These structures consist of multiple membrane-enclosed compartments including both soluble molecules and fibrous structures. The compartments are defined using volume voxelization of triangulated meshes. For membranes, we present an extension of the Wang Tile concept that populates the bilayer with individual lipids. Soluble molecules are populated within compartments distributed according to a Halton sequence. Fibrous structures, such as RNA or actin filaments, are created by self-avoiding random walks. Resulting overlaps of molecules are resolved by a forced-based system. Our approach opens new possibilities to the world of interactive construction of cellular compartments. We demonstrate its effectiveness by showcasing scenes of different scale and complexity that comprise blood plasma, mycoplasma, and HIV.

Molecular simulations of cellular processes

It is, nowadays, possible to simulate biological processes in conditions that mimic the different cellular compartments. Several groups have performed these calculations using molecular models that vary in performance and accuracy. In many cases, the atomistic degrees of freedom have been eliminated, sacrificing both structural complexity and chemical specificity to be able to explore slow processes. In this review, we will discuss the insights gained from computer simulations on macromolecule diffusion, nuclear body formation, and processes involving the genetic material inside cell-mimicking spaces. We will also discuss the challenges to generate new models suitable for the simulations of biological processes on a cell scale and for cell-cycle-long times, including non-equilibrium events such as the co-translational folding, misfolding, and aggregation of proteins. A prominent role will be played by the wise choice of the structural simplifications and, simultaneously, of a relatively complex energetic description. These challenging tasks will rely on the integration of experimental and computational methods, achieved through the application of efficient algorithms. Graphical abstract.

Broad-spectrum antiviral agents: secreted phospholipase A2 targets viral envelope lipid bilayers derived from the endoplasmic reticulum membrane

Hepatitis C virus (HCV), dengue virus (DENV) and Japanese encephalitis virus (JEV) belong to the family Flaviviridae. Their viral particles have the envelope composed of viral proteins and a lipid bilayer acquired from budding through the endoplasmic reticulum (ER). The phospholipid content of the ER membrane differs from that of the plasma membrane (PM). The phospholipase A2 (PLA2) superfamily consists of a large number of members that specifically catalyse the hydrolysis of phospholipids at a particular position. Here we show that the CM-II isoform of secreted PLA2 obtained from Naja mossambica mossambica snake venom (CM-II-sPLA2) possesses potent virucidal (neutralising) activity against HCV, DENV and JEV, with 50% inhibitory concentrations (IC50) of 0.036, 0.31 and 1.34 ng/ml, respectively. In contrast, the IC50 values of CM-II-sPLA2 against viruses that bud through the PM (Sindbis virus, influenza virus and Sendai virus) or trans-Golgi network (TGN) (herpes simplex virus) were >10,000 ng/ml. Moreover, the 50% cytotoxic (CC50) and haemolytic (HC50) concentrations of CM-II-sPLA2 were >10,000 ng/ml, implying that CM-II-sPLA2 did not significantly damage the PM. These results suggest that CM-II-sPLA2 and its derivatives are good candidates for the development of broad-spectrum antiviral drugs that target viral envelope lipid bilayers derived from the ER membrane.

Physical properties of the HIV-1 capsid from all-atom molecular dynamics simulations

Human immunodeficiency virus type 1 (HIV-1) infection is highly dependent on its capsid. The capsid is a large container, made of ∼1,300 proteins with altogether 4 million atoms. Although the capsid proteins are all identical, they nevertheless arrange themselves into a largely asymmetric structure made of hexamers and pentamers. The large number of degrees of freedom and lack of symmetry pose a challenge to studying the chemical details of the HIV capsid. Simulations of over 64 million atoms for over 1 μs allow us to conduct a comprehensive study of the chemical–physical properties of an empty HIV-1 capsid, including its electrostatics, vibrational and acoustic properties, and the effects of solvent (ions and water) on the capsid. The simulations reveal critical details about the capsid with implications to biological function.

The large and complex HIV-1 capsid modulates several molecular events during HIV-1’s infective cycle. Here the authors use all-atom molecular dynamic simulations to probe the biophysical properties of the genome-free HIV-1 capsid.

Study of the mechanism of protonated histidine-induced conformational changes in the Zika virus dimeric envelope protein using accelerated molecular dynamic simulations

The Zika virus has drawn worldwide attention because of the epidemic diseases it causes. It is a flavivirus that has an icosahedral protein shell constituted by an envelope glycoprotein (E-protein) and membrane protein (M-protein) in the mature virion. The multistep process of membrane fusion to infect the host cell is pH-induced. To understand the mechanism of the conformational changes in the (E-M)₂ protein homodimer embedded in the membrane, two 200-ns accelerated dynamic simulations were performed under different pH conditions. The low pH condition weakens the interactions and correlations in both E-protein monomers and in the E-M heterodimer. The highly conserved residues, His249, His288, His323 and His446, are protonated under low pH conditions and play key roles in driving the fusion process. The analysis and discussion in this study may provide some insight into the molecular mechanism of Zika virus infection.

Molecular dynamics simulations of membrane proteins and their interactions: from nanoscale to mesoscale

Molecular dynamics simulations provide a computational tool to probe membrane proteins and systems at length scales ranging from nanometers to close to a micrometer, and on microsecond timescales. All atom and coarse-grained simulations may be used to explore in detail the interactions of membrane proteins and specific lipids, yielding predictions of lipid binding sites in good agreement with available structural data. Building on the success of protein-lipid interaction simulations, larger scale simulations reveal crowding and clustering of proteins, resulting in slow and anomalous diffusional dynamics, within realistic models of cell membranes. Current methods allow near atomic resolution simulations of small membrane organelles, and of enveloped viruses to be performed, revealing key aspects of their structure and functionally important dynamics.