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We modeled 3D structures of all SARS‐CoV‐2 proteins, generating 2,060 models that span 69% of the viral proteome and provide details not available elsewhere. We found that ˜6% of the proteome mimicked human proteins, while ˜7% was implicated in hijacking mechanisms that reverse post‐translational modifications, block host translation, and disable host defenses; a further ˜29% self‐assembled into heteromeric states that provided insight into how the viral replication and translation complex forms. To make these 3D models more accessible, we devised a structural coverage map, a novel visualization method to show what is—and is not—known about the 3D structure of the viral proteome. We integrated the coverage map into an accompanying online resource (https://aquaria.ws/covid) that can be used to find and explore models corresponding to the 79 structural states identified in this work. The resulting Aquaria‐COVID resource helps scientists use emerging structural data to understand the mechanisms underlying coronavirus infection and draws attention to the 31% of the viral proteome that remains structurally unknown or dark., 2,060 structural models spanning 69% of the SARS‐CoV‐2 proteome are generated and presented in a novel visual layout that summarises current knowledge on viral protein structures, and provides insight into viral replication, mimicry, and hijacking.

In response to the COVID-19 pandemic, many life scientists are focused on SARS-CoV-2. To help them use available structural data, we systematically modeled all viral proteins using all related 3D structures, generating 872 models that provide detail not available elsewhere. To organise these models, we created a structural coverage map: a novel, one-stop visualization summarizing what is — and is not — known about the 3D structure of the viral proteome. The map highlights structural evidence for viral protein interactions, mimicry, and hijacking; it also helps researchers find 3D models of interest, which can then be mapped with UniProt, PredictProtein, or CATH features. The resulting Aquaria-COVID resource (https://aquaria.ws/covid) helps scientists understand molecular mechanisms underlying coronavirus infection. Based on insights gained using our resource, we propose mechanisms by which the virus may enter immune cells, sense the cell type, then switch focus from viral reproduction to disrupting host immune responses.SignificanceCurrently, much of the COVID-19 viral proteome has unknown molecular structure. To improve this, we generated ∼1,000 structural models, designed to capture multiple states for each viral protein. To organise these models, we created a structure coverage map: a novel, one-stop visualization summarizing what is — and is not — known about viral protein structure. We used these data to create an online resource, designed to help COVID-19 researchers gain insight into the key molecular processes that drive infection. Based on insights gained using our resource, we speculate that the virus may sense the type of cells it infects and, within certain cells, it may switch from reproduction to disruption of the immune system.

Novel visualization methods and strategies are necessary to cope with the deluge of datasets present in any scientific field to make discoveries and find answers to previously unanswered questions. These methods and strategies should not only present scientific findings as images in a concise way but also need to be effective and expressive, which often remain untested. Here, we present Versus, a tool to enable easy image quality assessment and image ranking, utilizing a two-alternative forced choice methodology (2AFC) and an efficient ranking algorithm based on a binary search. The tool provides a systematic way of setting up evaluation experiments via the web without the necessity to install any additional software or require any programming skills. Furthermore, Versus can easily interface with crowdsourcing platforms, such as Amazon’s Mechanical Turk, or can be used as a stand-alone system to carry out evaluations with experts. We demonstrate the use of Versus by means of an image evaluation study, aiming to determine if hue, saturation, brightness, and texture are good indicators of uncertainty in three-dimensional protein structures. Drawing from the power of crowdsourcing, we argue that there is demand and also great potential for this tool to become a standard for simple and fast image evaluations, with the aim to test the effectiveness and expressiveness of scientific visualizations. Keywords: Evaluation, Visualization, Visual analytics, Image comparison, Crowdsourcing, Evaluation methods, 2AFC, Image evaluation, Tool, Visualization evaluation

Human leucocyte antigen (HLA) class II molecules in humans are encoded by three different loci, HLA-DR, -DQ, and -DP. These molecules share approximately 70% sequence similarity and all present peptide ligands to circulating T cells. While the peptide repertoires of numerous HLA-DR, -DQ, and -DP allotypes have been examined, there have been few reports on the combined repertoire of these co-inherited molecules expressed in a single cell as an extended HLA haplotype. Here we describe the endogenous peptide repertoire of a human B lymphoblastoid cell line (C1R) expressing the class II haplotype HLA-DR12/DQ7/DP4. We have identified 71350 unique naturally processed peptides presented collectively by HLA-DR12, HLA-DQ7, or HLA-DP4. The resulting "haplodome" is complemented by the cellular proteome defined by standard LC-MS/MS approaches. This large dataset has shed light on properties of these class II ligands especially the preference for membrane and extracellular source proteins. Our data also provides insights into the co-evolution of these conserved haplotypes of closely linked and co-inherited HLA molecules; which together increase sequence coverage of cellular proteins for immune surveillance with minimal overlap between each co-inherited HLA-class II allomorph.

Major histocompatibility complex class I (MHC-I) molecules play a crucial role in immunity by capturing peptides for presentation to T cells and natural killer (NK) cells. The peptide termini are tethered within the MHC-I antigen-binding groove, but it is unknown whether other presentation modes occur. Here we show that 20% of the HLA-B*57:01 peptide repertoire comprises N-terminally extended sets characterized by a common motif at position 1 (P1) to P2. Structures of HLA-B*57:01 presenting N-terminally extended peptides, including the immunodominant HIV-1 Gag epitope TW10 (TSTLQEQIGW), showed that the N terminus protrudes from the peptide-binding groove. The common escape mutant TSNLQEQIGW bound HLA-B*57:01 canonically, adopting a dramatically different conformation than the TW10 peptide. This affected recognition by killer cell immunoglobulin-like receptor (KIR) 3DL1 expressed on NK cells. We thus define a previously uncharacterized feature of the human leukocyte antigen class I (HLA-I) immunopeptidome that has implications for viral immune escape. We further suggest that recognition of the HLA-B*57:01-TW10 epitope is governed by a 'molecular tension' between the adaptive and innate immune systems.

SummaryGranzyme B (GzmB) is a protease with a well-characterized intracellular role in targeted destruction of compromised cells by cytotoxic lymphocytes. However, GzmB also cleaves extracellular matrix components, suggesting that it influences the interplay between cytotoxic lymphocytes and their environment. Here, we show that GzmB-null effector T cells and natural killer (NK) cells exhibited a cell-autonomous homing deficit in mouse models of inflammation and Ectromelia virus infection. Intravital imaging of effector T cells in inflamed cremaster muscle venules revealed that GzmB-null cells adhered normally to the vessel wall and could extend lamellipodia through it but did not cross it efficiently. In vitro migration assays showed that active GzmB was released from migrating cytotoxic lymphocytes and enabled chemokine-driven movement through basement membranes. Finally, proteomic analysis demonstrated that GzmB cleaved basement membrane constituents. Our results highlight an important role for GzmB in expediting cytotoxic lymphocyte diapedesis via basement membrane remodeling.

Interactions between a host and a bacterial pathogen are mediated by cross-talk between molecules present on, or secreted by, pathogens and host binding-molecules. Identifying proteins involved at this interface would provide substantial insights into this interaction. Although numerous studies have examined in vitro models of infection at the level of transcriptional change and proteomic profiling, there is virtually no information available on naturally occurring host-pathogen interactions in vivo. We employed membrane shaving to identify peptide fragments cleaved from surface-expressed bacterial proteins and also detected proteins originating from the infected host. We optimized this technique for media-cultured Corynebacterium pseudotuberculosis, a sheep pathogen, revealing a set of 247 surface proteins. We then studied a natural host-pathogen interaction by performing membrane shaving on C. pseudotuberculosis harvested directly from naturally infected sheep lymph nodes. Thirty-one bacterial surface proteins were identified, including 13 not identified in culture media, suggesting that a different surface protein repertoire is expressed in this hostile environment. Forty-nine host proteins were identified, including immune mediators and antimicrobial peptides such as cathelicidin. This novel application of proteolytic shaving has documented sets of host and pathogen proteins present at the bacterial surface in an infection of the native host.

Molecular dynamics (MD) simulation is an established method for studying the conformational changes that are important for protein function. Recent advances in hardware and software have allowed MD simulations over the same timescales as experiment, improving the agreement between theory and experiment to a large extent. However, running such simulations are costly, in terms of resources, storage, and trajectory analysis. There is still a place for techniques that involve short MD simulations. In order to overcome the sampling paucity of short time-scales, hybrid methods that include some form of MD simulation can exploit certain features of the system of interest, often combining experimental information in surprising ways. Here, we review some recent hybrid approaches to the simulation of proteins.

Single-domain allostery has been postulated to occur through intramolecular pathways of signaling within a protein structure. We had previously investigated these pathways by introducing a local thermal perturbation and analyzed the anisotropic propagation of structural changes throughout the protein. Here, we develop an improved approach, the Rotamerically Induced Perturbation (RIP), that identifies strong couplings between residues by analyzing the pathways of heat-flow resulting from thermal excitation of rotameric rotations at individual residues. To explore the nature of these couplings, we calculate the complete coupling maps of 5 different PDZ domains. Although the PDZ domain is a well conserved structural fold that serves as a scaffold in many protein–protein complexes, different PDZ domains display unique patterns of conformational flexibility in response to ligand binding: some show a significant shift in a set of α-helices, while others do not. Analysis of the coupling maps suggests a simple relationship between the computed couplings and observed conformational flexibility. In domains where the α-helices are rigid, we find couplings of the α-helices to the body of the protein, whereas in domains having ligand-responsive α-helices, no couplings are found. This leads to a model where the α-helices are intrinsically dynamic but can be damped if sidechains interact at key tertiary contacts. These tertiary contacts correlate to high covariation contacts as identified by the statistical coupling analysis method. As these dynamic modules are exploited by various allosteric mechanisms, these tertiary contacts have been conserved by evolution.

What determines the shape of the allowed regions in the Ramachandran plot? Although Ramachandran explained these regions in terms of 1-4 hard-sphere repulsions, there are discrepancies with the data where, in particular, the alphaR, alphaL, and beta-strand regions are diagonal. The alphaR-region also varies along the alpha-helix where it is constrained at the center and the amino terminus but diffuse at the carboxyl terminus. By analyzing a high-resolution database of protein structures, we find that certain 1-4 hard-sphere repulsions in the standard steric map of Ramachandran do not affect the statistical distributions. By ignoring these steric clashes (NH(i+1) and O(i-1)C), we identify a revised set of steric clashes (CbetaO, O(i-1)N(i+1), CbetaN(i+1), O(i-1)Cbeta, and O(i-1)O) that produce a better match with the data. We also find that the strictly forbidden region in the Ramachandran plot is excluded by multiple steric clashes, whereas the outlier region is excluded by only one significant steric clash. However, steric clashes alone do not account for the diagonal regions. Using electrostatics to analyze the conformational dependence of specific interatomic interactions, we find that the diagonal shape of the alphaR and alphaL-regions also depends on the optimization of the NH(i+1) and O(i-1)C interactions, and the diagonal beta-strand region is due to the alignment of the CO and NH dipoles. Finally, we reproduce the variation of the Ramachandran plot along the alpha-helix in a simple model that uses only H-bonding constraints. This allows us to rationalize the difference between the amino terminus and the carboxyl terminus of the alpha-helix in terms of backbone entropy.

Amyloidogenic protein aggregation impairs cell function and is a hallmark of many chronic degenerative disorders. Protein aggregation is also a major event during acute injury; however, unlike amyloidogenesis, the process of injury-induced protein aggregation remains largely undefined. To provide this insight, we profiled the insoluble proteome of several cell types after acute injury. These experiments show that the disulfide-driven process of nucleocytoplasmic coagulation (NCC) is the main form of injury-induced protein aggregation. NCC is mechanistically distinct from amyloidogenesis, but still broadly impairs cell function by promoting the aggregation of hundreds of abundant and essential intracellular proteins. A small proportion of the intracellular proteome resists NCC and is instead released from necrotic cells. Notably, the physicochemical properties of NCC-resistant proteins are contrary to those of NCC-sensitive proteins. These observations challenge the dogma that liberation of constituents during necrosis is anarchic. Rather, inherent physicochemical features including cysteine content, hydrophobicity and intrinsic disorder determine whether a protein is released from necrotic cells. Furthermore, as half of the identified NCC-resistant proteins are known autoantigens, we propose that physicochemical properties that control NCC also affect immune tolerance and other host responses important for the restoration of homeostasis after necrotic injury.

In proteins, the proline ring exists predominantly in two discrete states. However, there is also a small but significant amount of flexibility in the proline ring of high-resolution protein structures. We have found that this side-chain flexibility is coupled to the backbone conformation. To study this coupling, we have developed a model that is simply based on geometric and steric factors and not on energetics. We show that the coupling between phi and chi1 torsions in the proline ring can be described by an analytic equation that was developed by Bricard in 1897, and we describe a computer algorithm that implements the equation. The model predicts the observed coupling very well. The strain in the C(gamma)-C(delta)-N angle appears to be the principal barrier between the UP and DOWN pucker. This strain is relaxed to allow the proline ring to flatten in the rare PLANAR conformation.

Two software plugins are presented for the Mac OSX operating system that allow rapid and convenient visualization of Protein Data Bank files and X-ray diffraction images directly within the file browser, without the need for full-featured applications., In structural biology, management of a large number of Protein Data Bank (PDB) files and raw X-ray diffraction images often presents a major organizational problem. Existing software packages that manipulate these file types were not designed for these kinds of file-management tasks. This is typically encountered when browsing through a folder of hundreds of X-ray images, with the aim of rapidly inspecting the diffraction quality of a data set. To solve this problem, a useful functionality of the Macintosh operating system (OSX) has been exploited that allows custom visualization plugins to be attached to certain file types. Software plugins have been developed for diffraction images and PDB files, which in many scenarios can save considerable time and effort. The direct visualization of diffraction images and PDB structures in the file browser can be used to identify key files of interest simply by scrolling through a list of files.

The annotation of surface exposed bacterial membrane proteins is an important step in interpretation and validation of proteomic experiments. In particular, proteins detected by cell surface protease shaving experiments can indicate exposed regions of membrane proteins that may contain antigenic determinants or constitute vaccine targets in pathogenic bacteria. Inmembrane is a tool to predict the membrane proteins with surface-exposed regions of polypeptide in sets of bacterial protein sequences. We have re-implemented a protocol for Gram-positive bacterial proteomes, and developed a new protocol for Gram-negative bacteria, which interface with multiple predictors of subcellular localization and membrane protein topology. Through the use of a modern scripting language, inmembrane provides an accessible code-base and extensible architecture that is amenable to modification for related sequence annotation tasks. Inmembrane easily integrates predictions from both local binaries and web-based queries to help gain an overview of likely surface exposed protein in a bacterial proteome. The program is hosted on the Github repository http://github.com/boscoh/inmembrane .

Kinetically stable proteins, those whose stability is derived from their slow unfolding kinetics and not thermodynamics, are examples of evolution's best attempts at suppressing unfolding. Especially in highly proteolytic environments, both partially and fully unfolded proteins face potential inactivation through degradation and/or aggregation, hence, slowing unfolding can greatly extend a protein's functional lifetime. The prokaryotic serine protease α-lytic protease (αLP) has done just that, as its unfolding is both very slow (t1/2 ∼1 year) and so cooperative that partial unfolding is negligible, providing a functional advantage over its thermodynamically stable homologs, such as trypsin. Previous studies have identified regions of the domain interface as critical to αLP unfolding, though a complete description of the unfolding pathway is missing. In order to identify the αLP unfolding pathway and the mechanism for its extreme cooperativity, we performed high temperature molecular dynamics unfolding simulations of both αLP and trypsin. The simulated αLP unfolding pathway produces a robust transition state ensemble consistent with prior biochemical experiments and clearly shows that unfolding proceeds through a preferential disruption of the domain interface. Through a novel method of calculating unfolding cooperativity, we show that αLP unfolds extremely cooperatively while trypsin unfolds gradually. Finally, by examining the behavior of both domain interfaces, we propose a model for the differential unfolding cooperativity of αLP and trypsin involving three key regions that differ between the kinetically stable and thermodynamically stable classes of serine proteases., Author Summary Proteins, synthesized as linear polymers of amino acids, fold up into compact native states, burying their hydrophobic amino acids into their interiors. Protein folding minimizes the non-specific interactions that unfolded protein chains can make, which include aggregation with other proteins and degradation by proteases. Unfortunately, even in the native state, proteins can partially unfold, opening up regions of their structure and making these adverse events possible. Some proteins, particularly those in harsh environments full of proteases, have evolved to virtually eliminate partial unfolding, significantly reducing their rate of degradation. This elimination of partial unfolding is termed “cooperative,” because unfolding is an all-or-none process. One class of proteins has diverged into two families, one bacterial and highly cooperative and the other animal and non-cooperative. We have used detailed simulations of unfolding for members of each family, α-lytic protease (bacterial) and trypsin (animal) to understand the unfolding pathways of each and the mechanism for the differential unfolding cooperativity. Our results explain prior biochemical experiments, reproduce the large difference in unfolding cooperativity between the families, and point to the interface between α-lytic protease's two domains as essential to establishing unfolding cooperativity. As seen in an unrelated protein family, generation of a cooperative domain interface may be a common evolutionary response for ensuring the highest protein stability.

Background An important element in homology modeling is the use of rotamers to parameterize the sidechain conformation. Despite the many libraries of sidechain rotamers that have been developed, a number of rotamers have been overlooked, due to the fact that they involve hydrogen atoms. Results We identify new, well-populated rotamers that involve the hydroxyl-hydrogen atoms of Ser, Thr and Tyr, and the sulfhydryl-hydrogen atom of Cys, using high-resolution crystal structures ( Conclusion Knowledge of these new rotamers will improve the evaluation of hydrogen-bonding networks in protein structures.

Peptides often have conformational preferences. We simulated 133 peptide 8-mer fragments from six different proteins, sampled by replica-exchange molecular dynamics using Amber7 with a GB/SA (generalized-Born/solvent-accessible electrostatic approximation to water) implicit solvent. We found that 85 of the peptides have no preferred structure, while 48 of them converge to a preferred structure. In 85% of the converged cases (41 peptides), the structures found by the simulations bear some resemblance to their native structures, based on a coarse-grained backbone description. In particular, all seven of the β hairpins in the native structures contain a fragment in the turn that is highly structured. In the eight cases where the bioinformatics-based I-sites library picks out native-like structures, the present simulations are largely in agreement. Such physics-based modeling may be useful for identifying early nuclei in folding kinetics and for assisting in protein-structure prediction methods that utilize the assembly of peptide fragments., Synopsis To carry out specific biochemical reactions, proteins must adopt precise three-dimensional conformations. During the folding of a protein, the protein picks out the right conformation out of billions of other conformations. It is not yet possible to do this computationally. Picking out the native conformation using physics-based atomically detailed models, sampled by molecular dynamics, is presently beyond the reach of computer methods. How can we speed up computational protein-structure prediction? One idea is that proteins start folding at specific parts of a chain that kink up early in the folding process. If we can identify these kinks, we should be able to speed up protein-structure prediction. Previous studies have identified likely kinks through bioinformatic analysis of existing protein structures. The goal of the authors here is to identify these putative folding initiation sites with a physical model instead. In this study, Ho and Dill show that, by chopping a protein chain into peptide pieces, then simulating the pieces in molecular dynamics, they can identify those peptide fragments that have conformational biases. These peptides identify the kinks in the protein chain.

The structures of the beta-sheets and the beta-ribbons have been analysed using high-resolution protein structure data. Systematic asymmetries measured in both parallel and antiparallel beta-structures include the sheet twist and the strand shear. In order to determine the origin of these asymmetries, numerous interactions and correlations were examined. The strongest correlations are observed for residues in antiparallel beta-sheets and beta-ribbons that form non-H-bonded pairs. For these residues, the sheet twist is correlated to the backbone phi angle but not to the psi angle. Our analysis supports the existence of an inter-strand C(alpha)H(alpha)...O weak H-bond, which, together with the CO...HN H-bond, constitutes a bifurcated H-bond that links neighbouring beta-strands. Residues of beta-sheets and beta-ribbons in high-resolution protein structures form a distinct region of the Ramachandran plot, which is determined by the formation of the bifurcated H-bond, the formation of an intra-strand O...H(alpha) non-bonded polar interaction, and an intra-strand O...C(beta) steric clash. Using beta-strands parameterised by phi-psi values from the allowed beta-sheet region of the Ramachandran plot, the shear and the right-hand twist can be reproduced in a simple model of the antiparallel and parallel beta-ribbon that models the bifurcated H-bonds specifically. The conformations of interior residues of beta-sheets are shown to be subsets of the conformations of residues of beta-ribbons.

Background The Ramachandran plot is a fundamental tool in the analysis of protein structures. Of the 4 basic types of Ramachandran plots, the interactions that determine the generic and proline Ramachandran plots are well understood. The interactions of the glycine and pre-proline Ramachandran plots are not. Results In glycine, the ψ angle is typically clustered at ψ = 180° and ψ = 0°. We show that these clusters correspond to conformations where either the Ni+1 or O atom is sandwiched between the two Hα atoms of glycine. We show that the shape of the 5 distinct regions of density (the α, αL, βS, βP and βPR regions) can be reproduced with electrostatic dipole-dipole interactions. In pre-proline, we analyse the origin of the ζ region of the Ramachandran plot, a region unique to pre-proline. We show that it is stabilized by a COi-1···CδHδ i+1 weak hydrogen bond. This is analogous to the COi-1···NHi+1 hydrogen bond that stabilizes the γ region in the generic Ramachandran plot. Conclusion We have identified the specific interactions that affect the backbone of glycine and pre-proline. Knowledge of these interactions will improve current force-fields, and help understand structural motifs containing these residues.

Background An accurate rendering of interior surfaces can facilitate the analysis of mechanisms at atomic-level detail, such as the transport of substrates in the ammonia channel. In molecular viewers, one must remove the exterior surface that obscures the channel surface by clipping the viewing plane or manually selecting the channel residues in order to display a partial surface. Neither method is entirely satisfactory, as unwanted additional pieces of surfaces are always generated. Results To cleanly visualize a channel surface, we present HOLLOW, a program that generates a "casting" of the interior volume of the protein as dummy atoms. We show that the molecular surface of the dummy atoms closely approximates the channel surface, where this complementary surface of the protein channel can be displayed without superfluous surfaces. Conclusion The use of HOLLOW significantly simplifies the generation of channel surfaces, and other interior surfaces of protein structures. HOLLOW is written in PYTHON and is available at http://hollow.sourceforge.net.