Multiscale modelling and simulation of viruses

Spool-Nematic Ordering of dsDNA and dsRNA under Confinement

The ability of double-stranded DNA or RNA to locally melt and form kinks leads to strong nonlinear elasticity effects that qualitatively affect their packing in confined spaces. Using analytical theory and numerical simulation we show that kink formation entails a mixed spool-nematic ordering of double-stranded DNA or RNA in spherical capsids, consisting of an outer spool domain and an inner, twisted nematic domain. These findings explain the experimentally observed nematic domains in viral capsids and imply that nonlinear elasticity must be considered to predict the configurations and dynamics of double-stranded genomes in viruses, bacterial nucleoids or gene-delivery vehicles. The nonlinear elastic theory suggests that spool-nematic ordering is a general feature of strongly confined kinkable polymers.

Coarse-Grained Model of Glycosaminoglycans for Biomolecular Simulations

Proteoglycans contain glycosaminoglycans (GAGs) which are negatively charged linear polymers made of repeating disaccharide units of uronic acid and hexosamine units. They play vital roles in numerous physiological and pathological processes, particularly in governing cellular communication and attachment. Depending on their sulfonation state, acetylation, and glycosidic linkages, GAGs belong to different families. The high molecular weight, heterogeneity, and flexibility of GAGs hamper their characterization at atomic resolution, but this may be circumvented via coarse-grained (CG) approaches. In this work, we report a CG model for a library of common GAG types in their isolated or proteoglycan-linked states compatible with version 2.2 (v2.2) of the widely popular CG Martini force field. The model reproduces conformational and thermodynamic properties for a wide variety of GAGs, as well as matching structural and binding data for selected proteoglycan test systems. The parameters developed here may thus be employed to study a range of GAG-containing biomolecular systems, thereby benefiting from the efficiency and broad applicability of the Martini framework.

Structure and energetics guide dynamic behaviour in a T = 3 icosahedral virus capsid

Although virus capsids appear as rigid, symmetric particles in experimentally determined structures; biochemical studies suggest a significant degree of structural flexibility in the particles. We carried out all-atom simulations on the icosahedral capsid of an insect virus, Flock House Virus, which show intriguing differences in the degree of flexibility of quasi-equivalent capsid subunits consistent with previously described biological behaviour. The flexibility of all the β and γ subunits of the protein and RNA fragments is analysed and compared. Both γA subunit and RNA fragment exhibit higher flexibility than the γB and γC subunits. The capsid shell is permeable to the bidirectional movement of water molecules, and the movement is heavily influenced by the geometry of the capsid shell along specific symmetry axes. In comparison to the symmetry axes along I5 and I3, the I2 axis exhibits a slightly higher water content. This enriched water environment along I2 could play a pivotal role in facilitating the structural transitions necessary for RNA release, shedding some light on the intricate and dynamic processes underlying the viral life cycle. Our study suggests that the physical characterization of whole virus capsids is the key to identifying biologically relevant transition states in the virus life cycle and understanding the basis of virus infectivity.

Hexagonal Lattices of HIV Capsid Proteins Explored by Simulations Based on a Thermodynamically Consistent Model

HIV capsid proteins (CAs) may self-assemble into a variety of shapes under in vivo and in vitro conditions. Here, we employed simulations based on a residue-level coarse-grained (CG) model with full conformational flexibility to investigate hexagonal lattices, which are the underlying structural pattern for CA aggregations. Facilitated by enhanced sampling simulations to rigorously calculate CA dimerization and polymerization affinities, we calibrated our model to reproduce the experimentally measured affinities. Using the calibrated model, we performed unbiased simulations on several large systems consisting of 1512 CA subunits, allowing reversible binding and unbinding of the CAs in a thermodynamically consistent manner. In one simulation, a preassembled hexagonal CA sheet developed spontaneous curvatures reminiscent of those observed in experiments, and the edges of the sheet exhibited local curvatures larger than those of the interior. In other simulations starting with randomly distributed CAs at different concentrations, existing CA assemblies grew by binding free capsomeres to the edges and by merging with other assemblies. At high CA concentrations, rapid establishment of predominant aggregates was followed by much slower adjustments toward more regular hexagonal lattices, with increasing numbers of intact CA hexamers and pentamers being formed. Our approach of adapting a general CG model to specific systems by using experimental binding data represents a practical and effective strategy for simulating and elucidating intricate protein aggregations.

Virus-like particles nanoreactors: from catalysis towards bio-applications

Virus-like particles (VLPs) are self-assembled supramolecular structures found in nature, often used for compartmentalization. Exploiting their inherent properties, including precise nanoscale structures, monodispersity, and high stability, these architectures have been widely used as nanocarriers to protect or enrich catalysts, facilitating catalytic reactions and avoiding interference from the bulk solutions. In this review, we summarize the current progress of virus-like particles (VLPs)-based nanoreactors. First, we briefly introduce the physicochemical properties of the most commonly used virus particles to understand their roles in catalytic reactions beyond the confined space. Next, we summarize the self-assembly of nanoreactors forming higher-order hierarchical structures, highlighting the emerging field of nanoreactors as artificial organelles and their potential biomedical applications. Finally, we discuss the current findings and future perspectives of VLPs-based nanoreactors.

The SIRAH force field: A suite for simulations of complex biological systems at the coarse-grained and multiscale levels

The different combinations of molecular dynamics simulations with coarse-grained representations have acquired considerable popularity among the scientific community. Especially in biocomputing, the significant speedup granted by simplified molecular models opened the possibility of increasing the diversity and complexity of macromolecular systems, providing realistic insights on large assemblies for more extended time windows. However, a holistic view of biological ensembles' structural and dynamic features requires a self-consistent force field, namely, a set of equations and parameters that describe the intra and intermolecular interactions among moieties of diverse chemical nature (i.e., nucleic and amino acids, lipids, solvent, ions, etc.). Nevertheless, examples of such force fields are scarce in the literature at the fully atomistic and coarse-grained levels. Moreover, the number of force fields capable of handling simultaneously different scales is restricted to a handful. Among those, the SIRAH force field, developed in our group, furnishes a set of topologies and tools that facilitate the setting up and running of molecular dynamics simulations at the coarse-grained and multiscale levels. SIRAH uses the same classical pairwise Hamiltonian function implemented in the most popular molecular dynamics software. In particular, it runs natively in AMBER and Gromacs engines, and porting it to other simulation packages is straightforward. This review describes the underlying philosophy behind the development of SIRAH over the years and across families of biological molecules, discussing current limitations and future implementations.

Analyzing the Geometry and Dynamics of Viral Structures: A Review of Computational Approaches Based on Alpha Shape Theory, Normal Mode Analysis, and Poisson-Boltzmann Theories

The current SARS-CoV-2 pandemic highlights our fragility when we are exposed to emergent viruses either directly or through zoonotic diseases. Fortunately, our knowledge of the biology of those viruses is improving. In particular, we have more and more structural information on virions, i.e., the infective form of a virus that includes its genomic material and surrounding protective capsid, and on their gene products. It is important to have methods that enable the analyses of structural information on such large macromolecular systems. We review some of those methods in this paper. We focus on understanding the geometry of virions and viral structural proteins, their dynamics, and their energetics, with the ambition that this understanding can help design antiviral agents. We discuss those methods in light of the specificities of those structures, mainly that they are huge. We focus on three of our own methods based on the alpha shape theory for computing geometry, normal mode analyses to study dynamics, and modified Poisson-Boltzmann theories to study the organization of ions and co-solvent and solvent molecules around biomacromolecules. The corresponding software has computing times that are compatible with the use of regular desktop computers. We show examples of their applications on some outer shells and structural proteins of the West Nile Virus.

Dengue Virus Capsid Protein Facilitates Genome Compaction and Packaging

Dengue virus (DENV) is a single-stranded (+)-sense RNA virus that infects humans and mosquitoes, posing a significant health risk in tropical and subtropical regions. Mature virions are composed of an icosahedral shell of envelope (E) and membrane (M) proteins circumscribing a lipid bilayer, which in turn contains a complex of the approximately 11 kb genomic RNA with capsid (C) proteins. Whereas the structure of the envelope is clearly defined, the structure of the packaged genome in complex with C proteins remains elusive. Here, we investigated the interactions of C proteins with viral RNA, in solution and inside mature virions, via footprinting and cross-linking experiments. We demonstrated that C protein interaction with DENV genomes saturates at an RNA:C protein ratio below 1:250. Moreover, we also showed that the length of the RNA genome interaction sites varies, in a multimodal distribution, consistent with the C protein binding to each RNA site mostly in singlets or pairs (and, in some instances, higher numbers). We showed that interaction sites are preferentially sites with low base pairing, as previously measured by 2'-acetylation analyzed by primer extension (SHAPE) reactivity indicating structuredness. We found a clear association pattern emerged: RNA-C protein binding sites are strongly associated with long-range RNA-RNA interaction sites, particularly inside virions. This, in turn, explains the need for C protein in viral genome packaging: the protein has a chief role in coordinating these key interactions, promoting proper packaging of viral RNA. Such sites are, thus, highly consequential for viral assembly, and, as such, may be targeted in future drug development strategies against these and related viruses.

Hierarchical Coarse-Grained Strategy for Macromolecular Self-Assembly: Application to Hepatitis B Virus-Like Particles

Macromolecular self-assembly is at the basis of many phenomena in material and life sciences that find diverse applications in technology. One example is the formation of virus-like particles (VLPs) that act as stable empty capsids used for drug delivery or vaccine fabrication. Similarly to the capsid of a virus, VLPs are protein assemblies, but their structural formation, stability, and properties are not fully understood, especially as a function of the protein modifications. In this work, we present a data-driven modeling approach for capturing macromolecular self-assembly on scales beyond traditional molecular dynamics (MD), while preserving the chemical specificity. Each macromolecule is abstracted as an anisotropic object and high-dimensional models are formulated to describe interactions between molecules and with the solvent. For this, data-driven protein-protein interaction potentials are derived using a Kriging-based strategy, built on high-throughput MD simulations. Semi-automatic supervised learning is employed in a high performance computing environment and the resulting specialized force-fields enable a significant speed-up to the micrometer and millisecond scale, while maintaining high intermolecular detail. The reported generic framework is applied for the first time to capture the formation of hepatitis B VLPs from the smallest building unit, i.e., the dimer of the core protein HBcAg. Assembly pathways and kinetics are analyzed and compared to the available experimental observations. We demonstrate that VLP self-assembly phenomena and dependencies are now possible to be simulated. The method developed can be used for the parameterization of other macromolecules, enabling a molecular understanding of processes impossible to be attained with other theoretical models.

The stressed life of a lipid in the Zika virus membrane

Protein-lipid interactions modulate a plethora of physiopathologic processes and have been the subject of countless studies. However, these kinds of interactions in the context of viral envelopes have remained relatively unexplored, partially because the intrinsically small dimensions of the molecular systems escape to the current resolution of experimental techniques. However, coarse-grained and multiscale simulations may fill that niche, providing nearly atomistic resolution at an affordable computational price. Here we use multiscale simulations to characterize the lipid-protein interactions in the envelope of the Zika Virus, a prominent member of the Flavivirus genus. Comparisons between the viral envelope and simpler molecular systems indicate that the viral membrane is under extreme pressures and asymmetric forces. Furthermore, the dense net of protein-protein contacts established by the envelope proteins creates poorly solvated regions that destabilize the external leaflet leading to a decoupled dynamics between both membrane layers. These findings lead to the idea that the Flaviviral membrane may store a significant amount of elastic energy, playing an active role in the membrane fusion process.

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.

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.

Fighting viruses with computers, right now

The synergistic conjunction of various technological revolutions with the accumulated knowledge and workflows is rapidly transforming several scientific fields. Particularly, Virology can now feed from accurate physical models, polished computational tools, and massive computational power to readily integrate high-resolution structures into biological representations of unprecedented detail. That preparedness allows for the first time to get crucial information for vaccine and drug design from in-silico experiments against emerging pathogens of worldwide concern at relevant action windows. The present work reviews some of the main milestones leading to these breakthroughs in Computational Virology, providing an outlook for future developments in capacity building and accessibility to computational resources.

Wrapping Up Viruses at Multiscale Resolution: Optimizing PACKMOL and SIRAH Execution for Simulating the Zika Virus

Simulating huge biomolecular complexes of million atoms at relevant biological time scales is becoming accessible to the broad scientific community. That proves to be crucial for urgent responses against emergent diseases in real time. Yet, there are still issues to sort regarding the system setup so that molecular dynamics (MD) simulations can be run in a simple and standard way. Here, we introduce an optimized pipeline for building and simulating enveloped virus-like particles (VLP). First, the membrane packing problem is tackled with new features and optimized options in PACKMOL. This allows preparing accurate membrane models of thousands of lipids in the context of a VLP within a few hours using a single CPU. Then, the assembly of the VLP system is done within the multiscale framework of the coarse-grained SIRAH force field. Finally, the equilibration protocol provides a system ready for production MD simulations within a few days on broadly accessible GPU resources. The pipeline is applied to study the Zika virus as a test case for large biomolecular systems. The VLP stabilizes at approximately 0.5 μs of MD simulation, reproducing correlations greater than 0.90 against experimental density maps from cryo-electron microscopy. Detailed structural analysis of the protein envelope also shows very good agreement in root-mean-square deviations and B-factors with the experimental data. The level of details attained shows for the first time a possible role for anionic phospholipids in stabilizing the envelope. Combining an efficient and reliable setup procedure with an accurate coarse-grained force field provides a valuable pipeline for simulating arbitrary viral systems or subcellular compartments, paving the way toward whole-cell simulations.

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 impact of Gag non-cleavage site mutations on HIV-1 viral fitness from integrative modelling and simulations

The high mutation rate in retroviruses is one of the leading causes of drug resistance. In human immunodeficiency virus type-1 (HIV-1), synergistic mutations in its protease and the protease substrate - the Group-specific antigen (Gag) polyprotein - work together to confer drug resistance against protease inhibitors and compensate the mutations affecting viral fitness. Some Gag mutations can restore Gag-protease binding, yet most Gag-protease correlated mutations occur outside of the Gag cleavage site. To investigate the molecular basis for this, we now report multiscale modelling approaches to investigate various sequentially cleaved Gag products in the context of clinically relevant mutations that occur outside of the cleavage sites, including simulations of the largest Gag proteolytic product in its viral membrane-bound state. We found that some mutations, such as G123E and H219Q, involve direct interaction with cleavage site residues to influence their local environment, while certain mutations in the matrix domain lead to the enrichment of lipids important for Gag targeting and assembly. Collectively, our results reveal why non-cleavage site mutations have far-reaching implications outside of Gag proteolysis, with important consequences for drugging Gag maturation intermediates and tackling protease inhibitor resistance.

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.

Extending the Martini Coarse-Grained Force Field to N-Glycans

Glycans play a vital role in a large number of cellular processes. Their complex and flexible nature hampers structure-function studies using experimental techniques. Molecular dynamics (MD) simulations can help in understanding dynamic aspects of glycans if the force field parameters used can reproduce key experimentally observed properties. Here, we present optimized coarse-grained (CG) Martini force field parameters for N-glycans, calibrated against experimentally derived binding affinities for lectins. The CG bonded parameters were obtained from atomistic (ATM) simulations for different glycan topologies including high mannose and complex glycans with various branching patterns. In the CG model, additional elastic networks are shown to improve maintenance of the overall conformational distribution. Solvation free energies and octanol-water partition coefficients were also calculated for various N-glycan disaccharide combinations. When using standard Martini nonbonded parameters, we observed that glycans spontaneously aggregated in the solution and required down-scaling of their interactions for reproduction of ATM model radial distribution functions. We also optimized the nonbonded interactions for glycans interacting with seven lectin candidates and show that a relatively modest scaling down of the glycan-protein interactions can reproduce free energies obtained from experimental studies. These parameters should be of use in studying the role of glycans in various glycoproteins and carbohydrate binding proteins as well as their complexes, while benefiting from the efficiency of CG sampling.

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.