Understanding Virus Structure and Dynamics through Molecular Simulations

Trajectory Retracing of the Packaging and Ejection Processes of Coaxially Spooled DNA

The coaxial spool structure of DNA has been regarded as an equilibrium conformation inside of a viral capsid. It has also been accepted that the DNA conformation inside the viral capsid should correlate strongly with the ejection of DNA out of the viral capsid. However, how the coaxial spool structure of DNA would affect the ejection kinetics remains elusive at the molecular level. In this study, we perform extensive Langevin dynamics simulations for a single polymer chain packaged within a small confinement to mimic the packaging and ejection processes of viral DNA and investigate the effects of its conformation on the ejection kinetics. We show that when the polymer chain within a small rectangular confinement is coaxially spooled, its ejection kinetics is facilitated significantly due to the trajectory retracing. We tune the conformation of the polymer chain inside the confinement by changing both the chain rigidity and the aspect ratio (γ) of the confinement. As either the aspect ratio (γ) decreases or the rigidity increases, the chain packaged inside the confinement is more likely to have a coaxial spool structure. And the polymer chain of the coaxial spool structure ejects quickly than chains of other conformations. We find that the coaxial spool structure enables the single chain to follow the reverse pathway of the packaging during ejection without significant structural rearrangement, thus enhancing the ejection kinetics.

Molecular dynamics simulations of biological membranes and membrane-associated phenomena across scales

Membranes are fundamental components of cells that are involved in a wide variety of cellular functions. They are inherently complex, being composed of hugely diverse collections of lipids and proteins, and their various functions arise directly from the intricate interplay between their components. To investigate the interactions between these components in detail, molecular dynamics (MD) simulations have proven to be an invaluable tool. In this mini-review, we highlight several recent studies that illustrate the current state of the art in using MD to study membrane systems. In particular, we first examine how MD is being used to characterize membrane binding of peripheral membrane proteins, we next describe how interactions between lipids and integral membrane proteins are being probed with MD, and we conclude by discussing new tools that have recently been developed to address the significant challenge of building simulateable models of large-scale membranes with complex curvature.

Clicking viruses-with chemistry toward mechanisms in infection

Viruses subvert cells and evade host defense. They emerge unpredictably and threaten humans and livestock through their genetic and phenotypic diversity. Despite more than 100 years since the discovery of viruses, the molecular underpinnings of virus infections are incompletely understood. The introduction of new methodologies into the field, such as that of click chemistry some 10 years ago, keeps uncovering new facets of viruses. Click chemistry uses bio-orthogonal reactions on chemical probes and couples nucleic acids, proteins, and lipids with tractable labels, such as fluorophores for single-cell and single-molecule imaging, or biotin for biochemical profiling of infections. Its applications in single cells often achieve single-molecule resolution and provide important insights into the widely known phenomenon of cell-to-cell infection variability. This review describes click chemistry advances to unravel infection mechanisms of a select set of enveloped and nonenveloped DNA and RNA viruses, including adenovirus, herpesvirus, and human immunodeficiency virus. It highlights recent click chemistry breakthroughs with viral DNA, viral RNA, protein, as well as host-derived lipid functions in both live and chemically fixed cells. It discusses new insights on specific processes including virus entry, uncoating, transcription, replication, packaging, and assembly and provides a perspective for click chemistry to explore viral cell biology, infection variability, and genome organization in the particle.

All-atom virus simulations to tackle airborne disease

We briefly review the latest computational studies focused on modeling viruses with classical all-atom (AA) molecular dynamics. We report on the challenges, current solutions, and ongoing developments in constructing and simulating whole viruses, and discuss unique insights derived from AA mesoscale simulations that cannot be achieved by other means. Finally, we present new opportunities in computational virology to understand viral aerostability within the context of respiratory disease transmission. Overall, we highlight the value of large-scale AA simulation and champion the need for increased interdisciplinary collaboration to generate novel insights and guide future research in respiratory disease.

Challenges in simulating whole virus particles and how to fix them with the SIRAH force field

Current developments in specialized software and computer power make the simulation of large molecular assemblies a technical possibility despite their computational cost. Coarse-grained (CG) approaches simplify molecular complexity and reduce computational costs while preserving intermolecular physical/chemical interactions. These methods enable virus simulations, making them more accessible to research groups with limited supercomputing resources. However, setting up and running molecular dynamics simulations of multimillion systems requires specialized molecular modeling, editing, and visualization skills. Moreover, many issues related to the computational setup, the choice of simulation engines, and the force fields that rule the intermolecular interactions require particular attention and are key to attaining a realistic description of viral systems at the fully atomistic or CG levels. Here, we provide an overview of the current challenges in simulating entire virus particles and the potential of the SIRAH force field to address these challenges through its implementations for CG and multiscale simulations.

DeepPath: Overcoming data scarcity for protein transition pathway prediction using physics-based deep learning

The structural dynamics of proteins play a crucial role in their function, yet most experimental and deep learning methods produce only static models. While molecular dynamics (MD) simulations provide atomistic insight into conformational transitions, they remain computationally prohibitive, particularly for large-scale motions. Here, we introduce DeepPath, a deep-learning-based framework that rapidly generates physically realistic transition pathways between known protein states. Unlike conventional supervised learning approaches, DeepPath employs active learning to iteratively refine its predictions, leveraging molecular mechanical force fields as an oracle to guide pathway generation. We validated DeepPath on three biologically relevant test cases: SHP2 activation, CdiB H1 secretion, and the BAM complex lateral gate opening. DeepPath accurately predicted the transition pathways for all test cases, reproducing key intermediate structures and transient interactions observed in previous studies. Notably, DeepPath also predicted an intermediate between the BAM inward- and outward-open states that closely aligns with an experimentally observed hybrid-barrel structure (TMscore = 0.91). Across all cases, DeepPath achieved accurate pathway predictions within hours, showcasing an efficient alternative to MD simulations for exploring protein conformational transitions.

Viral entry mechanisms: the role of molecular simulation in unlocking a key step in viral infections

Viral infections are a major global health concern, affecting millions of people each year. Viral entry is one of the crucial stages in the infection process, but its details remain elusive. Enveloped viruses are enclosed by a lipid membrane that protects their genetic material and these viruses are linked to various human illnesses, including influenza, and COVID-19. Due to the advancements made in the field of molecular simulation, significant progress has been made in unraveling the dynamic processes involved in viral entry of enveloped viruses. Simulation studies have provided deep insight into the function of the proteins responsible for attaching to the host receptors and promoting membrane fusion (fusion proteins), deciphering interactions between these proteins and receptors, and shedding light on the functional significance of key regions, such as the fusion peptide. These studies have already significantly contributed to our understanding of this critical aspect of viral infection and assisted the development of effective strategies to combat viral diseases and improve global health. This review focuses on the vital role of fusion proteins in facilitating the entry process of enveloped viruses and highlights the contributions of molecular simulation studies to uncover the molecular details underlying their mechanisms of action.

The Role of Cholesterol in M2 Clustering and Viral Budding Explained

The influenza A M2 homotetrameric channel consists of four transmembrane (TM) and four amphipathic helices (AHs). This viral proton channel is suggested to form clusters in the catenoid budding neck areas in raft-like domains of the plasma membrane, resulting in cell membrane scission and viral release. The channel clustering environment is rich in cholesterol. Previous experiments have shown that cholesterol significantly contributes to lipid bilayer undulations in viral buds. However, a clear explanation of membrane curvature from the distribution of cholesterol around the M2TM-AH clusters is lacking. Using coarse-grained molecular dynamics simulations of M2TM-AH in bilayers, we observed that M2 channels form specific, C2-symmetric, clusters with conical shapes driven by the attraction of their AHs. We showed that cholesterol stabilized the formation of M2 channel clusters by filling and bridging the conical gap between M2 channels at specific sites in the N-termini of adjacent channels or via the C-terminal region of TM and AHs, with the latter sites displaying a longer interaction time and higher stability. The potential of mean force calculations showed that when cholesterols occupy the identified interfacial binding sites between two M2 channels, the dimer is stabilized by 11 kJ/mol. This translates to the cholesterol-bound dimer being populated by almost 2 orders of magnitude compared to a dimer lacking cholesterol. We demonstrated that the cholesterol-bridged M2 channels can exert a lateral force on the surrounding membrane to induce the necessary negative Gaussian curvature profile, which permits spontaneous scission of the catenoid membrane neck and leads to viral buds and scission.

Resolving viral structural complexity by super-resolution microscopy

In this review, we discuss different super-resolution microscopy (SRM) techniques employed to study viral structures and virus composition with nanometric resolution. We describe the basic principles of the different microscopy methods utilized to break the light diffraction limit, enabling the study of protein composition in viral structures. Finally, we demonstrate for the first time the differential spatial distribution of two structural proteins in an individual baculovirus using single-molecule super-resolution microscopy. We discuss the future of these powerful methods for virology, medicine, and biotechnology applications.

Effect of Pregenomic RNA on the Mechanical Stability of HBV Capsid by Coarse-Grained Molecular Simulations

Hepatitis B virus (HBV) is a double-stranded DNA virus, but its life cycle involves an intermediate stage, during which pregenomic RNA (pgRNA) is encapsulated in the capsid and then reverse-transcribed into the minus DNA strand. These immature HBV virions are the key target for antiviral drug discovery. In this study, we investigate the flexibility and mechanical stability of the HBV capsid containing pgRNA by employing residue-resolved coarse-grained molecular dynamics simulations. The results showed that the presence of pgRNA tends to decrease the overall flexibility of the capsid. In addition, the symmetrically arranged subunits of the capsid show asymmetry in the dominant modes of the conformational fluctuations with or without the presence of pgRNA. Furthermore, the simulations revealed that the presence of pgRNA enhances the overall mechanical stability of the virion particle. Electrostatic interactions between the disordered CTD of capsid and pgRNA were found to play a crucial role in modulating viral mechanical stability. Decreasing the electrostatic interactions by CTD phosphorylation or high salt concentration significantly reduces the mechanical stability of the HBV capsid containing pgRNA. Finally, the 2-fold symmetric sites have been proposed to be the most vulnerable to rupture during the initial stages of capsid disassembly. These findings could enhance our understanding of the physical basis of viral invasion and provide valuable insights into the development of antiviral drugs.

Determination of airborne influenza virus and coronavirus infectivity using capsid integrity polymerase chain reaction

Accurate airborne virus monitoring is important for preventing the spread of infectious diseases. Although standard reverse transcription-quantitative polymerase chain reaction (RT-qPCR) can efficiently detect viral ribonucleic acid (RNA), it cannot determine whether the RNA is associated with active (infectious) or inactive (non-infectious) viruses. Plaque assay is the gold standard for determining viral infectivity but is laborious and time-consuming. This study explored the viral infectivity of H1N1 influenza virus and human coronavirus (HCoV-229E) using capsid integrity RT-qPCR, where virus samples were pretreated with reagents penetrating viruses with damaged capsids, impeding amplification by binding to their RNA. Therefore, the amplified signals corresponded solely to active viruses with undamaged capsids. Propidium monoazide (PMA) and platinum (IV) chloride (PtCl4) were used to investigate the effects of reagent concentration. Feasibility tests revealed that PtCl4 was more efficient than PMA, with optimal concentrations of 125-250 μM and 250-500 μM for H1N1 influenza virus and HCoV-229E, respectively. The results of percentage of active virus showed that capsid integrity RT-qPCR provided a trend similar to that of plaque assay, indicating an accurate measure of viral infectivity. Virus sampling in the laboratory and field highlighted the precision of this methodology for determining viral infectivity. Therefore, this methodology enables rapid and accurate detection of infectious airborne H1N1 influenza virus and HCoV-229E, allowing swift response to outbreaks.

Viral Protein Dimerization Quality Control: A Design Strategy for a Potential Viral Inhibitor

The global pharmaceutical market has been profoundly impacted by the coronavirus pandemic, leading to an increased demand for specific drugs. Consequently, drug resistance has prompted continuous innovation in drug design strategies to effectively combat resistant pathogens or disease variants. Protein dimers play crucial roles in vivo, including catalytic reactions, signal transduction, and structural stability. The site of action for protein dimerization modulators typically does not reside within the active site of the protein, thereby potentially impeding resistance development. Therefore, harnessing viral protein dimerization modulators could represent a promising avenue for combating viral infections. In this Perspective, we provide a detailed introduction to the design principles and applications of dimerization modulators in antiviral research. Furthermore, we analyze various representative examples to elucidate their modes of action while presenting our perspective on dimerization modulators along with the opportunities and challenges associated with this groundbreaking area of investigation.

Investigation of small molecules disrupting dengue virus assembly by inhibiting capsid protein and blocking RNA encapsulation

Dengue fever is a significant global public health concern, causing substantial morbidity and mortality worldwide. The disease can manifest in various forms, from mild fever to potentially life-threatening complications. Developing effective treatments remains a critical challenge to healthcare systems. Despite extensive research, no antiviral drugs have been approved for either the prevention or treatment of dengue. Targeting the virus during its early phase of attachment is essential to inhibit viral replication. The capsid protein plays a crucial role in the virus's structural integrity, assembly, and viral genome release. In the present study, we employed a computational approach focused on the capsid protein to identify possible potent inhibitors against the dengue virus from a library of FDA-approved drugs. We employed high-throughput virtual screening on FDA-approved drugs to identify drug molecules that could potentially combat the disease and save both cost and time. The screening process identified four drug molecules (Nordihydroguaiaretic acid, Ifenprodil tartrate, Lathyrol, and Safinamide Mesylate) based on their highest binding affinity and MM/GBSA scores. Among these, Nordihydroguaiaretic acid showed higher binding affinity than the reference molecule with - 11.66 kcal/mol. In contrast, Ifenprodil tartrate and Lathyrol showed similar results to the reference molecule, with binding energies of - 9.42 kcal/mol and - 9.29 kcal/mol, respectively. Following the screening, molecular dynamic simulations were performed to explore the molecular stability and conformational possibilities. The drug molecules were further supported by post-molecular simulation analysis. Furthermore, binding energies were also computed using the MM/GBSA approach, and the free energy landscape was used to calculate the different transition states, revealing that the drugs exhibited significant transition states. Specifically, Nordihydroguaiaretic acid and Ifenprodil tartrate displayed higher flexibility, while Lathyrol and Safinamide Mesylate showed more predictable and consistent protein folding. This significant breakthrough offers new hope against dengue, highlighting the power of computational drug discovery in identifying potent inhibitors and paving the way for novel treatment approaches.

Molecular Mechanism of pH-Induced Protrusion Configuration Switching in Piscine Betanodavirus Implies a Novel Antiviral Strategy

Many viruses contain surface spikes or protrusions that are essential for virus entry. These surface structures can thereby be targeted by antiviral drugs to treat viral infections. Nervous necrosis virus (NNV), a simple nonenveloped virus in the genus of betanodavirus, infects fish and damages aquaculture worldwide. NNV has 60 conspicuous surface protrusions, each comprising three protrusion domains (P-domain) of its capsid protein. NNV uses protrusions to bind to common receptors of sialic acids on the host cell surface to initiate its entry via the endocytic pathway. However, structural alterations of NNV in response to acidic conditions encountered during this pathway remain unknown, while detailed interactions of protrusions with receptors are unclear. Here, we used cryo-EM to discover that Grouper NNV protrusions undergo low-pH-induced compaction and resting. NMR and molecular dynamics (MD) simulations were employed to probe the atomic details. A solution structure of the P-domain at pH 7.0 revealed a long flexible loop (amino acids 311-330) and a pocket outlined by this loop. Molecular docking analysis showed that the N-terminal moiety of sialic acid inserted into this pocket to interact with conserved residues inside. MD simulations demonstrated that part of this loop converted to a β-strand under acidic conditions, allowing for P-domain trimerization and compaction. Additionally, a low-pH-favored conformation is attained for the linker connecting the P-domain to the NNV shell, conferring resting protrusions. Our findings uncover novel pH-dependent conformational switching mechanisms underlying NNV protrusion dynamics potentially utilized for facilitating NNV entry, providing new structural insights into complex NNV-host interactions with the identification of putative druggable hotspots on the protrusion.

Nanomechanical resilience and thermal stability of RSJ2 phage

As the world moves toward a green economy and sustainable agriculture, bacterial viruses or bacteriophages (phages) become attractive biocontrol agents for controlling crop diseases. Effective utilization of phages in farms requires integrated knowledge of crops, pathogens, phages, and surroundings. Phages must encounter environmental fluctuations, including temperature, and must remain infectious for successful bacteria lysis. This work studied a soilborne RSJ2 phage discovered in Thailand, which can eliminate Ralstonia solanacearum, causing bacterial wilt disease in chili. We investigated how phage infectivity and nanomechanics responded to thermal changes. The plaque-based assay showed that the infectivity of the RSJ2 phage was stable within 24-40 °C, an average temperature fluctuation in tropical regions. The structural examination also showed that the phage remained intact. The nanomechanical property of the phage was inspected by the atomic force microscopy-based nanoindentation. The result revealed that the phage stiffness within 24-40 °C was statistically similar (0.05-0.06 N/m). Upon heating at 40 °C for 1, 5, and 10 h and resting at 25 °C, the stiffness of the phage particles increased to 0.09-0.11 N/m (54-83% increase). The stiffness results suggest structural adaptation of the protein subunits as a response to thermal alteration. The study exhibits that the phage structure is highly dynamic and can nanomechanically respond to varying temperatures. The phage stiffness may reveal insight into phage adaptation to environmental factors. Equipped with the knowledge of phage infectivity, structure, and nanomechanics, we can design practical guidelines for effective phage usage in farming and propelling green and safe agriculture.

Modeling membranes in situ

Molecular dynamics simulations of cellular membranes have come a long way-from simple model lipid bilayers to multicomponent systems capturing the crowded and complex nature of real cell membranes. In this opinionated minireview, we discuss the current challenge to simulate the dynamics of membranes in their native environment, in situ, with the prospect of reaching the level of whole cells and cell organelles using an integrative modeling framework.

The Applications of Artificial Intelligence (AI)-Driven Tools in Virus-Like Particles (VLPs) Research

Viral-like particles (VLPs) represent versatile nanoscale structures mimicking the morphology and antigenic characteristics of viruses, devoid of genetic material, making them promising candidates for various biomedical applications. The integration of artificial intelligence (AI) into VLP research has catalyzed significant advancements in understanding, production, and therapeutic applications of these nanostructures. This comprehensive review explores the collaborative utilization of AI tools, computational methodologies, and state-of-the-art technologies within the VLP domain. AI's involvement in bioinformatics facilitates sequencing and structure prediction, unraveling genetic intricacies and three-dimensional configurations of VLPs. Furthermore, AI-enabled drug discovery enables virtual screening, demonstrating promise in identifying compounds to inhibit VLP activity. In VLP production, AI optimizes processes by providing strategies for culture conditions, nutrient concentrations, and growth kinetics. AI's utilization in image analysis and electron microscopy expedites VLP recognition and quantification. Moreover, network analysis of protein-protein interactions through AI tools offers an understanding of VLP interactions. The integration of multi-omics data via AI analytics provides a comprehensive view of VLP behavior. Predictive modeling utilizing machine learning algorithms aids in forecasting VLP stability, guiding optimization efforts. Literature mining facilitated by text mining algorithms assists in summarizing information from the VLP knowledge corpus. Additionally, AI's role in laboratory automation enhances experimental efficiency. Addressing data security concerns, AI ensures the protection of sensitive information in the digital era of VLP research. This review serves as a roadmap, providing insights into AI's current and future applications in VLP research, thereby guiding innovative directions in medicine and beyond.

Incorporating Intracellular Processes in Virus Dynamics Models

In-host models have been essential for understanding the dynamics of virus infection inside an infected individual. When used together with biological data, they provide insight into viral life cycle, intracellular and cellular virus-host interactions, and the role, efficacy, and mode of action of therapeutics. In this review, we present the standard model of virus dynamics and highlight situations where added model complexity accounting for intracellular processes is needed. We present several examples from acute and chronic viral infections where such inclusion in explicit and implicit manner has led to improvement in parameter estimates, unification of conclusions, guidance for targeted therapeutics, and crossover among model systems. We also discuss trade-offs between model realism and predictive power and highlight the need of increased data collection at finer scale of resolution to better validate complex models.

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.

Modeling bacterial microcompartment architectures for enhanced cyanobacterial carbon fixation

The carboxysome is a bacterial microcompartment (BMC) which plays a central role in the cyanobacterial CO2-concentrating mechanism. These proteinaceous structures consist of an outer protein shell that partitions Rubisco and carbonic anhydrase from the rest of the cytosol, thereby providing a favorable microenvironment that enhances carbon fixation. The modular nature of carboxysomal architectures makes them attractive for a variety of biotechnological applications such as carbon capture and utilization. In silico approaches, such as molecular dynamics (MD) simulations, can support future carboxysome redesign efforts by providing new spatio-temporal insights on their structure and function beyond in vivo experimental limitations. However, specific computational studies on carboxysomes are limited. Fortunately, all BMC (including the carboxysome) are highly structurally conserved which allows for practical inferences to be made between classes. Here, we review simulations on BMC architectures which shed light on (1) permeation events through the shell and (2) assembly pathways. These models predict the biophysical properties surrounding the central pore in BMC-H shell subunits, which in turn dictate the efficiency of substrate diffusion. Meanwhile, simulations on BMC assembly demonstrate that assembly pathway is largely dictated kinetically by cargo interactions while final morphology is dependent on shell factors. Overall, these findings are contextualized within the wider experimental BMC literature and framed within the opportunities for carboxysome redesign for biomanufacturing and enhanced carbon fixation.

Mechanisms of allostery at the viral surface through the eyes of molecular simulation

The outermost surface layer of any virus is formed by either a capsid shell or envelope. Such layers have traditionally been thought of as immovable structures, but it is becoming apparent that they cannot be viewed exclusively as static architectures protecting the viral genome. A limited number of proteins on the virion surface must perform a multitude of functions in order to orchestrate the viral life cycle, and allostery can regulate their structures at multiple levels of organization, spanning individual molecules, protomers, large oligomeric assemblies, or entire viral surfaces. Here, we review recent contributions from the molecular simulation field to viral surface allostery, with a particular focus on the trimeric spike glycoprotein emerging from the coronavirus surface, and the icosahedral flaviviral envelope complex. As emerging viral pathogens continue to pose a global threat, an improved understanding of viral dynamics and allosteric regulation will prove crucial in developing novel therapeutic strategies.

Theoretical Studies on Assembly, Physical Stability, and Dynamics of Viruses

All matter must obey the general laws of physics and living matter is not an exception. Viruses have not only learnt how to cope with them but have managed to use them for their own survival. In this chapter, we will review some of the exciting physics that are behind viruses and discuss simple physical models that can shed some light on different aspects of the viral life cycle and viral properties. In particular, we will focus on how the structure and shape of the viral capsid, its assembly and stability, and the entry and exit of viral particles and their genomes can be explained using fundamental physics theories.

Molecular Dynamics Simulations of Deformable Viral Capsomers

Most coarse-grained models of individual capsomers associated with viruses employ rigid building blocks that do not exhibit shape adaptation during self-assembly. We develop a coarse-grained general model of viral capsomers that incorporates their stretching and bending energies while retaining many features of the rigid-body models, including an overall trapezoidal shape with attractive interaction sites embedded in the lateral walls to favor icosahedral capsid assembly. Molecular dynamics simulations of deformable capsomers reproduce the rich self-assembly behavior associated with a general T=1 icosahedral virus system in the absence of a genome. Transitions from non-assembled configurations to icosahedral capsids to kinetically-trapped malformed structures are observed as the steric attraction between capsomers is increased. An assembly diagram in the space of capsomer-capsomer steric attraction and capsomer deformability reveals that assembling capsomers of higher deformability into capsids requires increasingly large steric attraction between capsomers. Increasing capsomer deformability can reverse incorrect capsomer-capsomer binding, facilitating transitions from malformed structures to symmetric capsids; however, making capsomers too soft inhibits assembly and yields fluid-like structures.

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.