Using AlphaFold Predictions in Viral Research.

Elucidation of the tertiary structure of proteins is an important task for biological and medical studies. AlphaFold, a modern deep-learning algorithm, enables the prediction of protein structure to a high level of accuracy. It has been applied in numerous studies in various areas of biology and medicine. Viruses are biological entities infecting eukaryotic and procaryotic organisms. They can pose a danger for humans and economically significant animals and plants, but they can also be useful for biological control, suppressing populations of pests and pathogens. AlphaFold can be used for studies of molecular mechanisms of viral infection to facilitate several activities, including drug design. Computational prediction and analysis of the structure of bacteriophage receptor-binding proteins can contribute to more efficient phage therapy. In addition, AlphaFold predictions can be used for the discovery of enzymes of bacteriophage origin that are able to degrade the cell wall of bacterial pathogens. The use of AlphaFold can assist fundamental viral research, including evolutionary studies. The ongoing development and improvement of AlphaFold can ensure that its contribution to the study of viral proteins will be significant in the future.

Targeting the I7L Protease: A Rational Design for Anti-Monkeypox Drugs?

The latest monkeypox virus outbreak in 2022 showcased the potential threat of this viral zoonosis to public health. The lack of specific treatments against this infection and the success of viral protease inhibitors-based treatments against HIV, Hepatitis C, and SARS-CoV-2, brought the monkeypox virus I7L protease under the spotlight as a potential target for the development of specific and compelling drugs against this emerging disease. In the present work, the structure of the monkeypox virus I7L protease was modeled and thoroughly characterized through a dedicated computational study. Furthermore, structural information gathered in the first part of the study was exploited to virtually screen the DrugBank database, consisting of drugs approved by the Food and Drug Administration (FDA) and clinical-stage drug candidates, in search for readily repurposable compounds with similar binding features as TTP-6171, the only non-covalent I7L protease inhibitor reported in the literature. The virtual screening resulted in the identification of 14 potential inhibitors of the monkeypox I7L protease. Finally, based on data collected within the present work, some considerations on developing allosteric modulators of the I7L protease are reported.

Modelling the Transitioning of SARS-CoV-2 nsp3 and nsp4 Lumenal Regions towards a More Stable State on Complex Formation.

During coronavirus infection, three non-structural proteins, nsp3, nsp4, and nsp6, are of great importance as they induce the formation of double-membrane vesicles where the replication and transcription of viral gRNA takes place, and the interaction of nsp3 and nsp4 lumenal regions triggers membrane pairing. However, their structural states are not well-understood. We investigated the interactions between nsp3 and nsp4 by predicting the structures of their lumenal regions individually and in complex using AlphaFold2 as implemented in ColabFold. The ColabFold prediction accuracy of the nsp3-nsp4 complex was increased compared to nsp3 alone and nsp4 alone. All cysteine residues in both lumenal regions were modelled to be involved in intramolecular disulphide bonds. A linker region in the nsp4 lumenal region emerged as crucial for the interaction, transitioning to a structured state when predicted in complex. The key interactions modelled between nsp3 and nsp4 appeared stable when the transmembrane regions of nsp3 and nsp4 were added to the modelling either alone or together. While molecular dynamics simulations (MD) demonstrated that the proposed model of the nsp3 lumenal region on its own is not stable, key interactions between nsp and nsp4 in the proposed complex model appeared stable after MD. Together, these observations suggest that the interaction is robust to different modelling conditions. Understanding the functional importance of the nsp4 linker region may have implications for the targeting of double membrane vesicle formation in controlling coronavirus infection.

Improved Antibody-Specific Epitope Prediction Using AlphaFold and AbAdapt.

Antibodies recognize their cognate antigens with high affinity and specificity, but the prediction of binding sites on the antigen (epitope) corresponding to a specific antibody remains a challenging problem. To address this problem, we developed AbAdapt, a pipeline that integrates antibody and antigen structural modeling with rigid docking in order to derive antibody-antigen specific features for epitope prediction. In this study, we systematically assessed the impact of integrating the state-of-the-art protein modeling method AlphaFold with the AbAdapt pipeline. By incorporating more accurate antibody models, we observed improvement in docking, paratope prediction, and prediction of antibody-specific epitopes. We further applied AbAdapt-AF in an anti-receptor binding domain (RBD) antibody complex benchmark and found AbAdapt-AF outperformed three alternative docking methods. Also, AbAdapt-AF demonstrated higher epitope prediction accuracy than other tested epitope prediction tools in the anti-RBD antibody complex benchmark. We anticipate that AbAdapt-AF will facilitate prediction of antigen-antibody interactions in a wide range of applications.

Neuropeptides, New Ligands of SARS-CoV-2 Nucleoprotein, a Potential Link between Replication, Inflammation and Neurotransmission.

This work identifies new ligands of the nucleoprotein N of SARS-CoV-2 by in silico screening, which used a new model of N, built from an Alphafold model refined by molecular dynamic simulations. The ligands were neuropeptides, such as substance P (1-7) and enkephalin, bound at a large site of the C-terminal or associated with the N-terminal ß-sheet. The BA4 and BA5 Omicron variants of N also exhibited a large site as in wt N, and an increased flexibility of the BA5 variant, enabling substance P binding. The binding sites of some ligands deduced from modeling in wt N were assessed by mutation studies in surface plasmon resonance experiments. Dynamic light scattering showed that the ligands impeded RNA binding to N, which likely inhibited replication. We suggest that the physiological role of these neuropeptides in neurotransmission, pain and vasodilation for cholecystokinin and substance P could be altered by binding to N. We speculate that N may link between viral replication and multiple pathways leading to long COVID-19 symptoms. Therefore, N may constitute a "danger hub" that needs to be inhibited, even at high cost for the host. Antivirals targeted to N may therefore reduce the risk of brain fog and stroke, and improve patients' health.

In Silico Protein Folding Prediction of COVID-19 Mutations and Variants.

With its fast-paced mutagenesis, the SARS-CoV-2 Omicron variant has threatened many societies worldwide. Strategies for predicting mutagenesis such as the computational prediction of SARS-CoV-2 structural diversity and its interaction with the human receptor will greatly benefit our understanding of the virus and help develop therapeutics against it. We aim to use protein structure prediction algorithms along with molecular docking to study the effects of various mutations in the Receptor Binding Domain (RBD) of the SARS-CoV-2 and its key interactions with the angiotensin-converting enzyme 2 (ACE-2) receptor. The RBD structures of the naturally occurring variants of SARS-CoV-2 were generated from the WUHAN-Hu-1 using the trRosetta algorithm. Docking (HADDOCK) and binding analysis (PRODIGY) between the predicted RBD sequences and ACE-2 highlighted key interactions at the Receptor-Binding Motif (RBM). Further mutagenesis at conserved residues in the Original, Delta, and Omicron variants (P499S and T500R) demonstrated stronger binding and interactions with the ACE-2 receptor. The predicted T500R mutation underwent some preliminary tests in vitro for its binding and transmissibility in cells; the results correlate with the in-silico analysis. In summary, we suggest conserved residues P499 and T500 as potential mutation sites that could increase the binding affinity and yet do not exist in nature. This work demonstrates the use of the trRosetta algorithm to predict protein structure and future mutations at the RBM of SARS-CoV-2, followed by experimental testing for further efficacy verification. It is important to understand the protein structure and folding to help develop potential therapeutics.

Using Alphafold2 to Predict the Structure of the Gp5/M Dimer of Porcine Respiratory and Reproductive Syndrome Virus.

Porcine reproductive and respiratory syndrome virus is a positive-stranded RNA virus of the family Arteriviridae. The Gp5/M dimer, the major component of the viral envelope, is required for virus budding and is an antibody target. We used alphafold2, an artificial-intelligence-based system, to predict a credible structure of Gp5/M. The short disulfide-linked ectodomains lie flat on the membrane, with the exception of the erected N-terminal helix of Gp5, which contains the antibody epitopes and a hypervariable region with a changing number of carbohydrates. The core of the dimer consists of six curved and tilted transmembrane helices, and three are from each protein. The third transmembrane regions extend into the cytoplasm as amphiphilic helices containing the acylation sites. The endodomains of Gp5 and M are composed of seven ß-strands from each protein, which interact via ß-strand seven. The area under the membrane forms an open cavity with a positive surface charge. The M and Orf3a proteins of coronaviruses have a similar structure, suggesting that all four proteins are derived from the same ancestral gene. Orf3a, like Gp5/M, is acylated at membrane-proximal cysteines. The role of Gp5/M during virus replication is discussed, in particular the mechanisms of virus budding and models of antibody-dependent virus neutralization.

NMR Observation of Sulfhydryl Signals in SARS-CoV-2 Main Protease Aids Structural Studies.

The 68-kDa homodimeric 3C-like protease of SARS-CoV-2, Mpro (3CLpro /Nsp5), is a key antiviral drug target. NMR spectroscopy of this large system proved challenging and resonance assignments have remained incomplete. Here we present the near-complete (>97 %) backbone assignments of a C145A variant of Mpro (Mpro C145A ) both with, and without, the N-terminal auto-cleavage substrate sequence, in its native homodimeric state. We also present SILLY (Selective Inversion of thioL and Ligand for NOESY), a simple yet effective pseudo-3D NMR experiment that utilizes NOEs to identify interactions between Cys-thiol or aliphatic protons, and their spatially proximate backbone amides in a perdeuterated protein background. High protection against hydrogen exchange is observed for 10 of the 11 thiol groups in Mpro C145A , even those that are partially accessible to solvent. A combination of SILLY methods and high-resolution triple-resonance NMR experiments reveals site-specific interactions between Mpro , its substrate peptides, and other ligands, which present opportunities for competitive binding studies in future drug design efforts.

PTX3 structure determination using a hybrid cryoelectron microscopy and AlphaFold approach offers insights into ligand binding and complement activation.

Pattern recognition molecules (PRMs) form an important part of innate immunity, where they facilitate the response to infections and damage by triggering processes such as inflammation. The pentraxin family of soluble PRMs comprises long and short pentraxins, with the former containing unique N-terminal regions unrelated to other proteins or each other. No complete high-resolution structural information exists about long pentraxins, unlike the short pentraxins, where there is an abundance of both X-ray and cryoelectron microscopy (cryo-EM)-derived structures. This study presents a high-resolution structure of the prototypical long pentraxin, PTX3. Cryo-EM yielded a 2.5-Å map of the C-terminal pentraxin domains that revealed a radically different quaternary structure compared to other pentraxins, comprising a glycosylated D4 symmetrical octameric complex stabilized by an extensive disulfide network. The cryo-EM map indicated α-helices that extended N terminal of the pentraxin domains that were not fully resolved. AlphaFold was used to predict the remaining N-terminal structure of the octameric PTX3 complex, revealing two long tetrameric coiled coils with two hinge regions, which was validated using classification of cryo-EM two-dimensional averages. The resulting hybrid cryo-EM/AlphaFold structure allowed mapping of ligand binding sites, such as C1q and fibroblast growth factor-2, as well as rationalization of previous biochemical data. Given the relevance of PTX3 in conditions ranging from COVID-19 prognosis, cancer progression, and female infertility, this structure could be used to inform the understanding and rational design of therapies for these disorders and processes.

Data-driven platform for identifying variants of interest in COVID-19 virus.

New SARS-CoV-2 variants emerge as part of the virus' adaptation to the human host. The Health Organizations are monitoring newly emerging variants with suspected impact on disease or vaccination efficacy as Variants Being Monitored (VBM), like Delta and Omicron. Genetic changes (SNVs) compared to the Wuhan variant characterize VBMs with current emphasis on the spike protein and lineage markers. However, monitoring VBMs in such a way might miss SNVs with functional effect on disease. Here we introduce a lineage-agnostic genome-wide approach to identify SNVs associated with disease. We curated a case-control dataset of 10,520 samples and identified 117 SNVs significantly associated with adverse patient outcome. While 40% (47) SNV are already monitored and 36% (43) are in the spike protein, we also identified 70 new SNVs that are associated with disease outcome. 31 of these are disease-worsening and predominantly located in the 3'-5' exonuclease (NSP14) with structural modelling revealing a concise cluster in the Zn binding domain that has known host-immune modulating function. Furthermore, we generate clade-independent VBM groupings by identifying interacting SNVs (epistasis). We find 37 sets of higher-order epistatic interactions joining 5 genomic regions (nsp3, nsp14, Spike S1, ORF3a, N). Structural modelling of these regions provides insights into potential mechanistic pathways of increased virulence as well as orthogonal methods of validation. Clade-independent monitoring of functionally interacting (epistasis, co-evolution) SNVs detected emerging VBM a week before they were flagged by Health Organizations and in conjunction with structural modelling provides faster, mechanistic insight into emerging strains to guide public health interventions.

Potential Autoimmunity Resulting from Molecular Mimicry between SARS-CoV-2 Spike and Human Proteins.

Molecular mimicry between viral antigens and host proteins can produce cross-reacting antibodies leading to autoimmunity. The coronavirus SARS-CoV-2 causes COVID-19, a disease curiously resulting in varied symptoms and outcomes, ranging from asymptomatic to fatal. Autoimmunity due to cross-reacting antibodies resulting from molecular mimicry between viral antigens and host proteins may provide an explanation. Thus, we computationally investigated molecular mimicry between SARS-CoV-2 Spike and known epitopes. We discovered molecular mimicry hotspots in Spike and highlight two examples with tentative high autoimmune potential and implications for understanding COVID-19 complications. We show that a TQLPP motif in Spike and thrombopoietin shares similar antibody binding properties. Antibodies cross-reacting with thrombopoietin may induce thrombocytopenia, a condition observed in COVID-19 patients. Another motif, ELDKY, is shared in multiple human proteins, such as PRKG1 involved in platelet activation and calcium regulation, and tropomyosin, which is linked to cardiac disease. Antibodies cross-reacting with PRKG1 and tropomyosin may cause known COVID-19 complications such as blood-clotting disorders and cardiac disease, respectively. Our findings illuminate COVID-19 pathogenesis and highlight the importance of considering autoimmune potential when developing therapeutic interventions to reduce adverse reactions.

At Least Three Doses of Leading Vaccines Essential for Neutralisation of SARS-CoV-2 Omicron Variant.

Plasma samples taken at different time points from donors who received either AstraZeneca (Vaxzevria) or Pfizer (Comirnaty) or Moderna (Spikevax) coronavirus disease-19 (COVID-19) vaccine were assessed in virus neutralization assays against Delta and Omicron variants of concern and a reference isolate (VIC31). With the Pfizer vaccine there was 6-8-fold reduction in 50% neutralizing antibody titres (NT50) against Delta and VIC31 at 6 months compared to 2 weeks after the second dose; followed by 25-fold increase at 2 weeks after the third dose. Neutralisation of Omicron was only consistently observed 2 weeks after the third dose, with most samples having titres below the limit of detection at earlier timepoints. Moderna results were similar to Pfizer at 2 weeks after the second dose, while the titres for AstraZeneca samples derived from older donors were 7-fold lower against VIC31 and below the limit of detection against Delta and Omicron. Age and gender were not found to significantly impact our results. These findings indicate that vaccine matching may be needed, and that at least a third dose of these vaccines is necessary to generate sufficient neutralising antibodies against emerging variants of concern, especially Omicron, amidst the challenges of ensuring vaccine equity worldwide.

Conformational ensemble of the TNF-derived peptide solnatide in solution.

Tumor necrosis factor (TNF) is a homotrimer that has two spatially distinct binding regions, three lectin-like domains (LLD) at the TIP of the protein and three basolaterally located receptor-binding sites, the latter of which are responsible for the inflammatory and cell death-inducing properties of the cytokine. Solnatide (a.k.a. TIP peptide, AP301) is a 17-mer cyclic peptide that mimics the LLD of human TNF which activates the amiloride-sensitive epithelial sodium channel (ENaC) and, as such, recapitulates the capacity of TNF to enhance alveolar fluid clearance, as demonstrated in numerous preclinical studies. TNF and solnatide interact with glycoproteins and these interactions are necessary for their trypanolytic and ENaC-activating activities. In view of the crucial role of ENaC in lung liquid clearance, solnatide is currently being evaluated as a novel therapeutic agent to treat pulmonary edema in patients with moderate-to-severe acute respiratory distress syndrome (ARDS), as well as severe COVID-19 patients with ARDS. To facilitate the description of the functional properties of solnatide in detail, as well as to further target-docking studies, we have analyzed its folding properties by NMR. In solution, solnatide populates a set of conformations characterized by a small hydrophobic core and two electrostatically charged poles. Using the structural information determined here and also that available for the ENaC protein, we propose a model to describe solnatide interaction with the C-terminal domain of the ENaCα subunit. This model may serve to guide future experiments to validate specific interactions with ENaCα and the design of new solnatide analogs with unexplored functionalities.

Highly Thermotolerant SARS-CoV-2 Vaccine Elicits Neutralising Antibodies against Delta and Omicron in Mice.

As existing vaccines fail to completely prevent COVID-19 infections or community transmission, there is an unmet need for vaccines that can better combat SARS-CoV-2 variants of concern (VOC). We previously developed highly thermo-tolerant monomeric and trimeric receptor-binding domain derivatives that can withstand 100 °C for 90 min and 37 °C for four weeks and help eliminate cold-chain requirements. We show that mice immunised with these vaccine formulations elicit high titres of antibodies that neutralise SARS-CoV-2 variants VIC31 (with Spike: D614G mutation), Delta and Omicron (BA.1.1) VOC. Compared to VIC31, there was an average 14.4-fold reduction in neutralisation against BA.1.1 for the three monomeric antigen-adjuvant combinations and a 16.5-fold reduction for the three trimeric antigen-adjuvant combinations; the corresponding values against Delta were 2.5 and 3.0. Our findings suggest that monomeric formulations are suitable for upcoming Phase I human clinical trials and that there is potential for increasing the efficacy with vaccine matching to improve the responses against emerging variants. These findings are consistent with in silico modelling and AlphaFold predictions, which show that, while oligomeric presentation can be generally beneficial, it can make important epitopes inaccessible and also carries the risk of eliciting unwanted antibodies against the oligomerisation domain.

"But Mouse, You Are Not Alone": On Some Severe Acute Respiratory Syndrome Coronavirus 2 Variants Infecting Mice.

In silico predictions combined with in vitro, in vivo, and in situ observations collectively suggest that mouse adaptation of the severe acute respiratory syndrome 2 virus requires an aromatic substitution in position 501 or position 498 (but not both) of the spike protein's receptor binding domain. This effect could be enhanced by mutations in positions 417, 484, and 493 (especially K417N, E484K, Q493K, and Q493R), and to a lesser extent by mutations in positions 486 and 499 (such as F486L and P499T). Such enhancements, due to more favorable binding interactions with residues on the complementary angiotensin-converting enzyme 2 interface, are, however, unlikely to sustain mouse infectivity on their own based on theoretical and experimental evidence to date. Our current understanding thus points to the Alpha, Beta, Gamma, and Omicron variants of concern infecting mice, whereas Delta and "Delta Plus" lack a similar biomolecular basis to do so. This paper identifies 11 countries (Brazil, Chile, Djibouti, Haiti, Malawi, Mozambique, Reunion, Suriname, Trinidad and Tobago, Uruguay, and Venezuela) where targeted local field surveillance of mice is encouraged because they may have come in contact with humans who had the virus with adaptive mutation(s). It also provides a systematic methodology to analyze the potential for other animal reservoirs and their likely locations.

High Molecular Weight Kininogen: A Review of the Structural Literature.

Kininogens are multidomain glycoproteins found in the blood of most vertebrates. High molecular weight kininogen demonstrate both carrier and co-factor activity as part of the intrinsic pathway of coagulation, leading to thrombin generation. Kininogens are the source of the vasoactive nonapeptide bradykinin. To date, attempts to crystallize kininogen have failed, and very little is known about the shape of kininogen at an atomic level. New advancements in the field of cryo-electron microscopy (cryoEM) have enabled researchers to crack the structure of proteins that has been refractory to traditional crystallography techniques. High molecular weight kininogen is a good candidate for structural investigation by cryoEM. The goal of this review is to summarize the findings of kininogen structural studies.

PDBsum extras: SARS-CoV-2 and AlphaFold models.

The PDBsum web server provides structural analyses of the entries in the Protein Data Bank (PDB). Two recent additions are described here. The first is the detailed analysis of the SARS-CoV-2 virus protein structures in the PDB. These include the variants of concern, which are shown both on the sequences and 3D structures of the proteins. The second addition is the inclusion of the available AlphaFold models for human proteins. The pages allow a search of the protein against existing structures in the PDB via the Sequence Annotated by Structure (SAS) server, so one can easily compare the predicted model against experimentally determined structures. The server is freely accessible to all at http://www.ebi.ac.uk/pdbsum.

Crystallographic molecular replacement using an in silico-generated search model of SARS-CoV-2 ORF8.

The majority of crystal structures are determined by the method of molecular replacement (MR). The range of application of MR is limited mainly by the need for an accurate search model. In most cases, pre-existing experimentally determined structures are used as search models. In favorable cases, ab initio predicted structures have yielded search models adequate for MR. The ORF8 protein of SARS-CoV-2 represents a challenging case for MR using an ab initio prediction because ORF8 has an all ß-sheet fold and few orthologs. We previously determined experimentally the structure of ORF8 using the single anomalous dispersion (SAD) phasing method, having been unable to find an MR solution to the crystallographic phase problem. Following a report of an accurate prediction of the ORF8 structure, we assessed whether the predicted model would have succeeded as an MR search model. A phase problem solution was found, and the resulting structure was refined, yielding structural parameters equivalent to the original experimental solution.

Can We AlphaFold Our Way Out of the Next Pandemic?

The announcement of the outstanding performance of AlphaFold 2 in the CASP 14 protein structure prediction competition came at the end of a long year defined by the COVID-19 pandemic. With an infectious organism dominating the world stage, the developers of Alphafold 2 were keen to play their part, accurately predicting novel structures of two proteins from SARS-CoV-2. In their blog post of December 2020, they highlighted this contribution, writing "we've also seen signs that protein structure prediction could be useful in future pandemic response efforts". So, what role does structural biology play in guiding vaccine immunogen design and what might be the contribution of AlphaFold 2?