Comparing antiviral strategies against COVID-19 via multiscale within-host modelling

Within-host models of COVID-19 infection dynamics enable the merits of different forms of antiviral therapy to be assessed in individual patients. A stochastic agent-based model of COVID-19 intracellular dynamics is introduced here, that incorporates essential steps of the viral life cycle targeted by treatment options. Integration of model predictions with an intercellular ODE model of within-host infection dynamics, fitted to patient data, generates a generic profile of disease progression in patients that have recovered in the absence of treatment. This is contrasted with the profiles obtained after variation of model parameters pertinent to the immune response, such as effector cell and antibody proliferation rates, mimicking disease progression in immunocompromised patients. These profiles are then compared with disease progression in the presence of antiviral and convalescent plasma therapy against COVID-19 infections. The model reveals that using both therapies in combination can be very effective in reducing the length of infection, but these synergistic effects decline with a delayed treatment start. Conversely, early treatment with either therapy alone can actually increase the duration of infection, with infectious virions still present after the decline of other markers of infection. This suggests that usage of these treatments should remain carefully controlled in a clinical environment

Asymmetric Genome Organization in an RNA Virus Revealed via Graph-Theoretical Analysis of Tomographic Data

Cryo-electron microscopy permits 3-D structures of viral pathogens to be determined in remarkable detail. In particular, the protein containers encapsulating viral genomes have been determined to high resolution using symmetry averaging techniques that exploit the icosahedral architecture seen in many viruses. By contrast, structure determination of asymmetric components remains a challenge, and novel analysis methods are required to reveal such features and characterize their functional roles during infection. Motivated by the important, cooperative roles of viral genomes in the assembly of single-stranded RNA viruses, we have developed a new analysis method that reveals the asymmetric structural organization of viral genomes in proximity to the capsid in such viruses. The method uses geometric constraints on genome organization, formulated based on knowledge of icosahedrally-averaged reconstructions and the roles of the RNA-capsid protein contacts, to analyse cryo-electron tomographic data. We apply this method to the low-resolution tomographic data of a model virus and infer the unique asymmetric organization of its genome in contact with the protein shell of the capsid. This opens unprecedented opportunities to analyse viral genomes, revealing conserved structural features and mechanisms that can be targeted in antiviral drug desig

Exploiting protein flexibility to predict the location of allosteric sites

Background: Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. Results: By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity), by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing that this simple coarse-grained methodology is able to capture the effects triggered by allosteric ligands already described in the literature. Conclusions: We introduce a simple computational approach to predict the presence and position of allosteric sites in a protein based on the analysis of changes in protein normal modes upon the binding of a coarse-grained ligand at predicted cavities. Its performance has been demonstrated using a newly curated non-redundant set of 91 proteins with reported allosteric properties. The software developed in this work is available upon request from the authors

Mechanical and Assembly Units of Viral Capsids Identified via Quasi-Rigid Domain Decomposition

Key steps in a viral life-cycle, such as self-assembly of a protective protein container or in some cases also subsequent maturation events, are governed by the interplay of physico-chemical mechanisms involving various spatial and temporal scales. These salient aspects of a viral life cycle are hence well described and rationalised from a mesoscopic perspective. Accordingly, various experimental and computational efforts have been directed towards identifying the fundamental building blocks that are instrumental for the mechanical response, or constitute the assembly units, of a few specific viral shells. Motivated by these earlier studies we introduce and apply a general and efficient computational scheme for identifying the stable domains of a given viral capsid. The method is based on elastic network models and quasi-rigid domain decomposition. It is first applied to a heterogeneous set of well-characterized viruses (CCMV, MS2, STNV, STMV) for which the known mechanical or assembly domains are correctly identified. The validated method is next applied to other viral particles such as L-A, Pariacoto and polyoma viruses, whose fundamental functional domains are still unknown or debated and for which we formulate verifiable predictions. The numerical code implementing the domain decomposition strategy is made freely available

Observation of the low frequency vibrational modes of bacteriophage M13 in water by Raman spectroscopy

<p>Abstract</p> <p>Background</p> <p>Recently, a technique which departs radically from conventional approaches has been proposed. This novel technique utilizes biological objects such as viruses as nano-templates for the fabrication of nanostructure elements. For example, rod-shaped viruses such as the M13 phage and tobacco mosaic virus have been successfully used as biological templates for the synthesis of semiconductor and metallic nanowires.</p> <p>Results and discussion</p> <p>Low wave number (≤ 20 <it>cm</it>^-1) acoustic vibrations of the M13 phage have been studied using Raman spectroscopy. The experimental results are compared with theoretical calculations based on an elastic continuum model and appropriate Raman selection rules derived from a bond polarizability model. The observed Raman mode has been shown to belong to one of the Raman-active axial torsion modes of the M13 phage protein coat.</p> <p>Conclusion</p> <p>It is expected that the detection and characterization of this low frequency vibrational mode can be used for applications in nanotechnology such as for monitoring the process of virus functionalization and self-assembly. For example, the differences in Raman spectra can be used to monitor the coating of virus with some other materials and nano-assembly process, such as attaching a carbon nanotube or quantum dots.</p

Community service provider perceptions of implementing older adult fall prevention in Ontario, Canada: a qualitative study

Abstract Background Despite evidence for effective fall prevention interventions, measurable reductions in older adult (≥ 65 years) fall rates remain unrealized. This study aimed to describe the perceived barriers to and effective strategies for the implementation of evidence-based fall prevention practices within and across diverse community organizations. This study is unique in that it included community service providers who are not generally thought to provide fall prevention services to older adults, such as retail business, community support, volunteer services, community foundations, recreation centres, and various emergency services. Methods Interviews and focus groups were conducted with a purposive sampling of providers (n = 84) in varied roles within diverse community-based organizations across disparate geographical settings. Results Community service providers experience significant multi-level barriers to fall prevention within and across organizations and settings. The overall challenge of serving dispersed populations in adverse environmental conditions was heightened in northern rural areas. Barriers across the system, within organizations and among providers themselves emerged along themes of Limited Coordination of Communication, Restrictive Organizational Mandates and Policies, Insufficient Resources, and Beliefs about Aging and Falls. Participants perceived that Educating Providers, Working Together, and Changing Policies and Legislation were strategies that have worked or would work well in implementing fall prevention. An unintentional observation was made that several participants in this extremely varied sample identified expanded roles in fall prevention for themselves during the interview process. Conclusions Community service providers experience disabling contexts for implementing fall prevention on many levels: their specific geography, their service systems, their organizations and themselves. A systemic lack of fit between the older adult and fall prevention services limits access, making fall prevention inaccessible, unaccommodating, unavailable, unaffordable, and unacceptable. Educating Providers, Working Together, and Changing Policies and Legislation offers promise to create more enabling contexts for community stakeholders, including those who do not initially see their work as preventing falls

Parameterizing Elastic Network Models to Capture the Dynamics of Proteins

International audienceCoarse-grained normal mode analyses of protein dynamics rely on the idea that the geometry of a protein structure contains enough information for computing its fluctuations around its equilibrium conformation. This geometry is captured in the form of an elastic network (EN), namely a network of edges between its residues. The normal modes of a protein are then identified with the normal modes of its EN. Different approaches have been proposed to construct ENs, focusing on the choice of the edges that they are comprised of, and on their parameterizations by the force constants associated with those edges. Here we propose new tools to guide choices on these two facets of EN. We study first different geometric models for ENs. We compare cutoff-based ENs, whose edges have lengths that are smaller than a cutoff distance, with Delaunay-based ENs and find that the latter provide better representations of the geometry of protein structures. We then derive an analytical method for the parameterization of the EN such that its dynamics leads to atomic fluctuations that agree with experimental Bfactors. To limit overfitting, we attach a parameter referred to as flexibility constant to each atom instead of to each edge in the EN. The parameterization is expressed as a non-linear optimization problem whose parameters describe both rigid-body and internal motions. We show that this parameterization leads to improved ENs, whose dynamics mimic MD simulations better than ENs with uniform force constants, and reduces the number of normal modes needed to reproduce functional conformational changes