A Computational Assay that Explores the Hemagglutinin/Neuraminidase Functional Balance Reveals the Neuraminidase Secondary Site as a Novel Anti-Influenza Target

Breathing and Tilting: Mesoscale Simulations Illuminate Influenza Glycoprotein Vulnerabilities

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

TABI-PB 2.0: An Improved Version of the Treecode-Accelerated Boundary Integral Poisson-Boltzmann Solver

This work describes TABI-PB 2.0, an improved version of the treecode-accelerated boundary integral Poisson-Boltzmann solver. The code computes the electrostatic potential on the molecular surface of a solvated biomolecule, and further processing yields the electrostatic solvation energy. The new implementation utilizes the NanoShaper surface triangulation code, node-patch boundary integral discretization, a block preconditioner, and a fast multipole method based on barycentric Lagrange interpolation and dual tree traversal. Performance-critical portions of the code were implemented on a GPU. Numerical results for protein 1A63 and two viral capsids (Zika, H1N1) demonstrate the code's accuracy and efficiency.

Breathing and tilting: mesoscale simulations illuminate influenza glycoprotein vulnerabilities

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

Assembly and Analysis of Cell-Scale Membrane Envelopes

The march toward exascale computing will enable routine molecular simulation of larger and more complex systems, for example, simulation of entire viral particles, on the scale of approximately billions of atoms─a simulation size commensurate with a small bacterial cell. Anticipating the future hardware capabilities that will enable this type of research and paralleling advances in experimental structural biology, efforts are currently underway to develop software tools, procedures, and workflows for constructing cell-scale structures. Herein, we describe our efforts in developing and implementing an efficient and robust workflow for construction of cell-scale membrane envelopes and embedding membrane proteins into them. A new approach for construction of massive membrane structures that are stable during the simulations is built on implementing a subtractive assembly technique coupled with the development of a structure concatenation tool (fastmerge), which eliminates overlapping elements based on volumetric criteria rather than adding successive molecules to the simulation system. Using this approach, we have constructed two "protocells" consisting of MARTINI coarse-grained beads to represent cellular membranes, one the size of a cellular organelle and another the size of a small bacterial cell. The membrane envelopes constructed here remain whole during the molecular dynamics simulations performed and exhibit water flux only through specific proteins, demonstrating the success of our methodology in creating tight cell-like membrane compartments. Extended simulations of these cell-scale structures highlight the propensity for nonspecific interactions between adjacent membrane proteins leading to the formation of protein microclusters on the cell surface, an insight uniquely enabled by the scale of the simulations. We anticipate that the experiences and best practices presented here will form the basis for the next generation of cell-scale models, which will begin to address the addition of soluble proteins, nucleic acids, and small molecules essential to the function of a cell.

Building Structural Models of a Whole Mycoplasma Cell

Building structural models of entire cells has been a long-standing cross-discipline challenge for the research community, as it requires an unprecedented level of integration between multiple sources of biological data and enhanced methods for computational modeling and visualization. Here, we present the first 3D structural models of an entire Mycoplasma genitalium (MG) cell, built using the CellPACK suite of computational modeling tools. Our model recapitulates the data described in recent whole-cell system biology simulations and provides a structural representation for all MG proteins, DNA and RNA molecules, obtained by combining experimental and homology-modeled structures and lattice-based models of the genome. We establish a framework for gathering, curating and evaluating these structures, exposing current weaknesses of modeling methods and the boundaries of MG structural knowledge, and visualization methods to explore functional characteristics of the genome and proteome. We compare two approaches for data gathering, a manually-curated workflow and an automated workflow that uses homologous structures, both of which are appropriate for the analysis of mesoscale properties such as crowding and volume occupancy. Analysis of model quality provides estimates of the regularization that will be required when these models are used as starting points for atomic molecular dynamics simulations.

Newly Emerging Strategies in Antiviral Drug Discovery: Dedicated to Prof. Dr. Erik De Clercq on Occasion of His 80th Anniversary

Viral infections pose a persistent threat to human health. The relentless epidemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global health problem, with millions of infections and fatalities so far. Traditional approaches such as random screening and optimization of lead compounds by organic synthesis have become extremely resource- and time-consuming. Various modern innovative methods or integrated paradigms are now being applied to drug discovery for significant resistance in order to simplify the drug process. This review provides an overview of newly emerging antiviral strategies, including proteolysis targeting chimera (PROTAC), ribonuclease targeting chimera (RIBOTAC), targeted covalent inhibitors, topology-matching design and antiviral drug delivery system. This article is dedicated to Prof. Dr. Erik De Clercq, an internationally renowned expert in the antiviral drug research field, on the occasion of his 80th anniversary.

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.

Second sialic acid-binding site of influenza A virus neuraminidase: binding receptors for efficient release

Influenza A viruses (IAVs) are a major cause of human respiratory tract infections and cause significant disease and mortality. Human IAVs originate from animal viruses that breached the host species barrier. IAV particles contain sialoglycan receptor-binding hemagglutinin (HA) and receptor-destroying neuraminidase (NA) in their envelope. When IAV crosses the species barrier, the functional balance between HA and NA needs to be adjusted to the sialoglycan repertoire of the novel host species. Relatively little is known about the role of NA in host adaptation in contrast to the extensively studied HA. NA prevents virion aggregation and facilitates release of (newly assembled) virions from cell surfaces and from decoy receptors abundantly present in mucus and cell glycocalyx. In addition to a highly conserved catalytic site, NA carries a second sialic acid-binding site (2SBS). The 2SBS preferentially binds α2,3-linked sialic acids and enhances activity of the neighboring catalytic site by bringing/keeping multivalent substrates in close contact with this site. In this way, the 2SBS contributes to the HA-NA balance of virus particles and affects virus replication. The 2SBS is highly conserved in all NA subtypes of avian IAVs, with some notable exceptions associated with changes in the receptor-binding specificity of HA and host tropism. Conservation of the 2SBS is invariably lost in human (pandemic) viruses and in several other viruses adapted to mammalian host species. Preservation or loss of the 2SBS is likely to be an important factor of the viral host range.

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.

MD simulation of the interaction between sialoglycans and the second sialic acid binding site of influenza A virus N1 neuraminidase

The neuraminidases (NAs) of avian influenza viruses (IAVs) contain a second sialic acid-binding site (2SBS), historically known as the hemadsorption site, which is separated from the sialyl-hydrolase catalytic site and serves to facilitate NA catalytic activity towards multivalent sialyl-capped glycoconjugates. Transmission and adaptation of avian IAVs to humans decreases hemadsorption and catalytic activities of the NA. Here, we report the molecular recognition features of the NA 2SBS of two pandemic H1N1 IAVs, A/Brevig Mission /1/1918 (BM18) and A/California/04/2009 (CA09), differing by their 2SBS activity. Using explicit solvent MD simulation, molecular mechanics, and glycosidic conformation analysis we initially analyzed the interactions of BM18 2SBS with two sialyllacto-N-tetraose pentasaccharides, 3'SLN-LC and 6'SLN-LC, which are models for the glycan receptors of IAVs in birds and humans, respectively. These studies characterize the binding specificity of BM18 2SBS towards human-type and avian-type receptors and identifies the key amino acids that affects binding. We next compared the interactions of the 2SBSs of BM18 and CA09 with 6'SLN-LC, revealing the critical effect of amino acid 372 on binding. Our results expand the current knowledge of the molecular features of NA 2SBSs and its alteration during the adaptation of avian IAVs to humans.

High resolution electron tomography and segmentation-by-modeling interpretation in Bsoft

Bsoft offers many tools for the processing of tomographic tilt series and the interpretation of tomograms. Since I introduced tomography into Bsoft almost two decades ago, the field has advanced significantly, requiring refinement of old algorithms and development of new ones. The current direct detectors allow us to collect data more efficiently and with better quality, progressing towards automation. The goal is then to also automate alignment of tilt series and reconstruction. I added an estimation of the specimen thickness as well as fiducialless alignment, to augment the existing fiducial-based alignment. High-resolution work requires correction for the contrast transfer function, in tomography complicated by the tilted specimen. For this, I developed a method to generate a power spectrum using the whole micrograph, compensating for tilting. This is followed by routine determination of the contrast transfer function, and correction for it during reconstruction. The next steps involve interpretation of the tomogram, either by subtomogram averaging where possible, or by segmentation and modeling otherwise. Such interpretation actually constitutes the main time-consuming part of tomography and is less amenable to automation compared to the initial reconstruction.

Integrating molecular modelling methods to advance influenza A virus drug discovery

Since the discovery of the anti-influenza drugs oseltamivir and zanamivir using computer-aided drug design methods, there have been significant applications of molecular modelling methodologies applied to influenza A virus drug discovery, such as molecular dynamics (MD) simulation, molecular docking, and virtual screening (VS). In this review, we provide a brief general introduction to molecular modelling in the context of drug discovery and then focus on the advances and impact of integrating these methods with specific reference to potential influenza A antiviral drug targets.

Phylogenetic analysis and clinical characteristics of the co-occurring mutations in HA and NA genes of influenza A(H1N1)pdm09 viruses during 2015-2017 in Beijing, China

Background

Influenza A(H1N1)pdm09 viruses have undergone rapid evolution, and in recent years the complementary and antagonistic effects of HA and NA have gathered more attentions; however, the effects of co-occurring mutations in HA and NA on the patients’ clinical characteristics are still poorly understood. In this study, we analyzed molecular epidemiology and evolution of A(H1N1) pdm09, explored co-occurring mutations of HA and NA, and investigated effect of co-occurring mutations on patients’ clinical features.

Methods

A(H1N1)pdm09 was confirmed by reverse transcription-polymerase chain reaction. HA and NA genes were sequenced and phylogenetically analyzed. Clinical characteristics of the co-occurring mutations were analyzed statistically.

Results

By analyzing the HA and NA gene sequences of 33 A(H1N1)pdm09 viruses during the 2015–2017 influenza season, we found that all the viruses shared high similarities to each other and the HA genes of these viruses exclusively belonged to subclade 6B.1A. Several unreported substitutions in HA and NA proteins were observed, furthermore, co-occurring mutations of HA-V169T, A278S, E508G, D518E and NA-V67I were detected in 30.3% (10/33) A(H1N1)pdm09 virus strains when comparing with vaccine strains A/California/07/2009 and A/Michigan/45/2015 (H1N1). Sore throat was significantly associated with co-occurring mutations in HA and NA of A(H1N1)pdm09 (χ², P < 0.05).

Conclusions

Co-occurring mutations in HA and NA were detected in A(H1N1)pdm09 isolated during 2015–2017 in Beijing. Symptomatically, sore throat was associated with co-occurring mutations in HA and NA of A(H1N1)pdm09. Therefore, studying the effect and mechanism of co-occurring mutations in HA and NA on patients’ clinical features is of note needed.

Mucin-Inspired, High Molecular Weight Virus Binding Inhibitors Show Biphasic Binding Behavior to Influenza A Viruses

Multivalent binding inhibitors are a promising new class of antivirals that prevent virus infections by inhibiting virus binding to cell membranes. The design of these inhibitors is challenging as many properties, for example, inhibitor size and functionalization with virus attachment factors, strongly influence the inhibition efficiency. Here, virus binding inhibitors are synthesized, the size and functionalization of which are inspired by mucins, which are naturally occurring glycosylated proteins with high molecular weight (MDa range) and interact efficiently with various viruses. Hyperbranched polyglycerols (hPGs) with molecular weights ranging between 10 and 2600 kDa are synthesized, thereby hitting the size of mucins and allowing for determining the impact of inhibitor size on the inhibition efficiency. The hPGs are functionalized with sialic acids and sulfates, as suggested from the structure of mucins, and their inhibition efficiency is determined by probing the inhibition of influenza A virus (IAV) binding to membranes using various methods. The largest, mucin-sized inhibitor shows potent inhibition at pm concentrations, while the inhibition efficiency decreases with decreasing the molecular weight. Interestingly, the concentration-dependent IAV inhibition shows a biphasic behavior, which is attributed to differences in the binding affinity of the inhibitors to the two IAV envelope proteins, neuraminidase, and hemagglutinin.

Multiscale Simulations Examining Glycan Shield Effects on Drug Binding to Influenza Neuraminidase

Influenza neuraminidase is an important drug target. Glycans are present on neuraminidase and are generally considered to inhibit antibody binding via their glycan shield. In this work, we studied the effect of glycans on the binding kinetics of antiviral drugs to the influenza neuraminidase. We created all-atom in silico systems of influenza neuraminidase with experimentally derived glycoprofiles consisting of four systems with different glycan conformations and one system without glycans. Using Brownian dynamics simulations, we observe a two- to eightfold decrease in the rate of ligand binding to the primary binding site of neuraminidase due to the presence of glycans. These glycans are capable of covering much of the surface area of neuraminidase, and the ligand binding inhibition is derived from glycans sterically occluding the primary binding site on a neighboring monomer. Our work also indicates that drugs preferentially bind to the primary binding site (i.e., the active site) over the secondary binding site, and we propose a binding mechanism illustrating this. These results help illuminate the complex interplay between glycans and ligand binding on the influenza membrane protein neuraminidase.

Topology-Matching Design of an Influenza-Neutralizing Spiky Nanoparticle-Based Inhibitor with a Dual Mode of Action

In this study, we demonstrate the concept of "topology-matching design" for virus inhibitors. With the current knowledge of influenza A virus (IAV), we designed a nanoparticle-based inhibitor (nano-inhibitor) that has a matched nanotopology to IAV virions and shows heteromultivalent inhibitory effects on hemagglutinin and neuraminidase. The synthesized nano-inhibitor can neutralize the viral particle extracellularly and block its attachment and entry to the host cells. The virus replication was significantly reduced by 6 orders of magnitude in the presence of the reverse designed nano-inhibitors. Even when used 24 hours after the infection, more than 99.999 % inhibition is still achieved, which indicates such a nano-inhibitor might be a potent antiviral for the treatment of influenza infection.

Art and Science of the Cellular Mesoscale

Experimental information from microscopy, structural biology, and bioinformatics may be integrated to build structural models of entire cells with molecular detail. This integrative modeling is challenging in several ways: the intrinsic complexity of biology results in models with many closely packed and heterogeneous components; the wealth of available experimental data is scattered among multiple resources and must be gathered, reconciled, and curated; and computational infrastructure is only now gaining the capability of modeling and visualizing systems of this complexity. We present recent efforts to address these challenges, both with artistic approaches to depicting the cellular mesoscale, and development and application of methods to build quantitative models.

Reverse design of an influenza neutralizing spiky nano-inhibitor with a dual mode of action

In this study, we demonstrate the concept of 'reverse design' for virus inhibitors. With the current knowledge of influenza A virus (IAV), we designed a nano-inhibitor that has a reverse shape to the viral particle and heteromultivalent inhibitory effects on hemagglutinin and neuraminidase. The synthesized nano-inhibitor can neutralize the viral particle extracellularly and block its attachment and entry to the host cells. The virus replication was significantly reduced by 6 orders of magnitude in the presence of the reverse designed nano-inhibitors. Even being used 24 hours after the infection, >99.999% inhibition is also achieved, which indicates such a nano-inhibitor might be a potent antiviral for the treatment of influenza infection.

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

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

Brownian Dynamics Simulations of Biological Molecules

Brownian dynamics (BD) is a technique for carrying out computer simulations of physical systems that are driven by thermal fluctuations. Biological systems at the macromolecular and cellular level, while falling in the gap between well-established atomic-level models and continuum models, are especially suitable for such simulations. We present a brief history, examples of important biological processes that are driven by thermal motion, and those that have been profitably studied by BD. We also present some of the challenges facing developers of algorithms and software, especially in the attempt to simulate larger systems more accurately and for longer times.

Identification of the Initial Steps in Signal Transduction in the α4β2 Nicotinic Receptor: Insights from Equilibrium and Nonequilibrium Simulations

Nicotinic acetylcholine receptors (nAChRs) modulate synaptic transmission in the nervous system. These receptors have emerged as therapeutic targets in drug discovery for treating several conditions, including Alzheimer's disease, pain, and nicotine addiction. In this in silico study, we use a combination of equilibrium and nonequilibrium molecular dynamics simulations to map dynamic and structural changes induced by nicotine in the human α4β2 nAChR. They reveal a striking pattern of communication between the extracellular binding pockets and the transmembrane domains (TMDs) and show the sequence of conformational changes associated with the initial steps in this process. We propose a general mechanism for signal transduction for Cys-loop receptors: the mechanistic steps for communication proceed firstly through loop C in the principal subunit, and are subsequently transmitted, gradually and cumulatively, to loop F of the complementary subunit, and then to the TMDs through the M2-M3 linker.