SARS-CoV-2-host proteome interactions for antiviral drug discovery

Valuable Contributions and Lessons Learned from Proteomics and Metabolomics Studies of COVID-19

The COVID-19 pandemic caused by the SARS-CoV-2 virus infected more than 775,686,716 humans and was responsible for the death of more than 7,054,093 individuals. COVID-19 has taught us that the development of vaccines, repurposing of drugs, and understanding the mechanism of a disease can be done within a short time. The COVID-19 proteomics and metabolomics has contributed to its diagnosis, understanding of its progression, host-virus interaction, disease mechanism, and also in the search of suitable anti-COVID therapeutics. Mass spectrometry based proteomics was used to find the potential biomarkers of different stages of COVID-19 including severe and nonsevere cases in the blood serum. Notably, protein-protein interaction techniques to understand host-virus interactions were also significantly useful. The single-cell proteomics studies were carried out to ascertain the changes in immune cell composition and its activation in mild COVID-19 patients versus severe COVID-19 patients using whole-blood and peripheral-blood mononuclear cells. Modern technologies were helpful to deal with the pandemic; however, there is still scope for further development. Further, attempts were made to understand the protein-protein, metabolite-metabolite, and protein-metabolite interactomes, derived from proteins and metabolite fingerprints of COVID-19 patients by reanalysis of COVID-19 public mass spectrometry based proteomics and metabolomics studies. Further, some of these interactions were supported by the literature as validations in the COVID-19 studies.

Control of nuclear localization of the nucleocapsid protein of SARS-CoV-2

The nucleocapsid (N) protein of coronaviruses is a structural protein that binds viral RNA for assembly into the mature virion, a process that occurs in the cytoplasm. Several coronavirus N proteins also localize to the nucleus. Herein, we identify that two sequences (NLSs) are required for nuclear localization of the SARS-CoV-2 N protein. Deletion or mutation of these two sequences creates an N protein that does not localize to the nucleus in HEK293T cells. Overexpression of both wild-type and NLS-mutated N proteins dysregulate a largely overlapping set of mRNAs in HEK293T cells, suggesting that these N proteins do not have direct nuclear effects on transcription. Consistent with that hypothesis, both N proteins induce nuclear localization of NF-κB p65 and dysregulate a set of previously identified NF-κB-dependent genes. The effects of N on nuclear properties are proposed to alter host cell functions that contribute to viral pathogenesis or replication.

A genome-wide arrayed CRISPR screen identifies PLSCR1 as an intrinsic barrier to SARS-CoV-2 entry that recent virus variants have evolved to resist

Interferons (IFNs) play a crucial role in the regulation and evolution of host-virus interactions. Here, we conducted a genome-wide arrayed CRISPR knockout screen in the presence and absence of IFN to identify human genes that influence Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection. We then performed an integrated analysis of genes interacting with SARS-CoV-2, drawing from a selection of 67 large-scale studies, including our own. We identified 28 genes of high relevance in both human genetic studies of Coronavirus Disease 2019 (COVID-19) patients and functional genetic screens in cell culture, with many related to the IFN pathway. Among these was the IFN-stimulated gene PLSCR1. PLSCR1 did not require IFN induction to restrict SARS-CoV-2 and did not contribute to IFN signaling. Instead, PLSCR1 specifically restricted spike-mediated SARS-CoV-2 entry. The PLSCR1-mediated restriction was alleviated by TMPRSS2 overexpression, suggesting that PLSCR1 primarily restricts the endocytic entry route. In addition, recent SARS-CoV-2 variants have adapted to circumvent the PLSCR1 barrier via currently undetermined mechanisms. Finally, we investigate the functional effects of PLSCR1 variants present in humans and discuss an association between PLSCR1 and severe COVID-19 reported recently.

Oxysterole-binding protein targeted by SARS-CoV-2 viral proteins regulates coronavirus replication

Introduction

Oxysterol-binding protein (OSBP) is known for its crucial role in lipid transport, facilitating cholesterol exchange between the Golgi apparatus and endoplasmic reticulum membranes. Despite its established function in cellular processes, its involvement in coronavirus replication remains unclear.

Methods

In this study, we investigated the role of OSBP in coronavirus replication and explored the potential of a novel OSBP-binding compound, ZJ-1, as an antiviral agent against coronaviruses, including SARS-CoV-2. We utilized a combination of biochemical and cellular assays to elucidate the interactions between OSBP and SARS-CoV-2 non-structural proteins (Nsps) and other viral proteins.

Results

Our findings demonstrate that OSBP positively regulates coronavirus replication. Moreover, treatment with ZJ-1 resulted in reduced OSBP levels and exhibited potent antiviral effects against multiple coronaviruses. Through our investigation, we identified specific interactions between OSBP and SARS-CoV-2 Nsps, particularly Nsp3, Nsp4, and Nsp6, which are involved in double-membrane vesicle formation-a crucial step in viral replication. Additionally, we observed that Nsp3 a.a.1-1363, Nsp4, and Nsp6 target vesicle-associated membrane protein (VAMP)-associated protein B (VAP-B), which anchors OSBP to the ER membrane. Interestingly, the interaction between OSBP and VAP-B is disrupted by Nsp3 a.a.1-1363 and partially impaired by Nsp6. Furthermore, we identified SARS-CoV-2 orf7a, orf7b, and orf3a as additional OSBP targets, with OSBP contributing to their stabilization.

Conclusion

Our study highlights the significance of OSBP in coronavirus replication and identifies it as a promising target for the development of antiviral therapies against SARS-CoV-2 and other coronaviruses. These findings underscore the potential of OSBP-targeted interventions in combating coronavirus infections.

Leveraging a self-cleaving peptide for tailored control in proximity labeling proteomics

Protein-protein interactions play an important biological role in every aspect of cellular homeostasis and functioning. Proximity labeling mass spectrometry-based proteomics overcomes challenges typically associated with other methods and has quickly become the current state of the art in the field. Nevertheless, tight control of proximity-labeling enzymatic activity and expression levels is crucial to accurately identify protein interactors. Here, we leverage a T2A self-cleaving peptide and a non-cleaving mutant to accommodate the protein of interest in the experimental and control TurboID setup. To allow easy and streamlined plasmid assembly, we built a Golden Gate modular cloning system to generate plasmids for transient expression and stable integration. To highlight our T2A Split/link design, we applied it to identify protein interactions of the glucocorticoid receptor and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid and non-structural protein 7 (NSP7) proteins by TurboID proximity labeling. Our results demonstrate that our T2A split/link provides an opportune control that builds upon previously established control requirements in the field.

A Cullin 5-based complex serves as an essential modulator of ORF9b stability in SARS-CoV-2 replication

The ORF9b protein, derived from the nucleocapsid's open-reading frame in both SARS-CoV and SARS-CoV-2, serves as an accessory protein crucial for viral immune evasion by inhibiting the innate immune response. Despite its significance, the precise regulatory mechanisms underlying its function remain elusive. In the present study, we unveil that the ORF9b protein of SARS-CoV-2, including emerging mutant strains like Delta and Omicron, can undergo ubiquitination at the K67 site and subsequent degradation via the proteasome pathway, despite certain mutations present among these strains. Moreover, our investigation further uncovers the pivotal role of the translocase of the outer mitochondrial membrane 70 (TOM70) as a substrate receptor, bridging ORF9b with heat shock protein 90 alpha (HSP90α) and Cullin 5 (CUL5) to form a complex. Within this complex, CUL5 triggers the ubiquitination and degradation of ORF9b, acting as a host antiviral factor, while HSP90α functions to stabilize it. Notably, treatment with HSP90 inhibitors such as GA or 17-AAG accelerates the degradation of ORF9b, leading to a pronounced inhibition of SARS-CoV-2 replication. Single-cell sequencing data revealed an up-regulation of HSP90α in lung epithelial cells from COVID-19 patients, suggesting a potential mechanism by which SARS-CoV-2 may exploit HSP90α to evade the host immunity. Our study identifies the CUL5-TOM70-HSP90α complex as a critical regulator of ORF9b protein stability, shedding light on the intricate host-virus immune response dynamics and offering promising avenues for drug development against SARS-CoV-2 in clinical settings.

Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics

The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19. In this work, we analysed missense coding variants in several SARS-CoV-2 proteins and their human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed the impact of missense variants occurring in the protein-protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities for the human viral protein complexes. We predicted a total of 26 affinity-enhancing variants from 13 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed. Occurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.

Mapping protein-protein interactions by mass spectrometry

Protein-protein interactions (PPIs) are essential for numerous biological activities, including signal transduction, transcription control, and metabolism. They play a pivotal role in the organization and function of the proteome, and their perturbation is associated with various diseases, such as cancer, neurodegeneration, and infectious diseases. Recent advances in mass spectrometry (MS)-based protein interactomics have significantly expanded our understanding of the PPIs in cells, with techniques that continue to improve in terms of sensitivity, and specificity providing new opportunities for the study of PPIs in diverse biological systems. These techniques differ depending on the type of interaction being studied, with each approach having its set of advantages, disadvantages, and applicability. This review highlights recent advances in enrichment methodologies for interactomes before MS analysis and compares their unique features and specifications. It emphasizes prospects for further improvement and their potential applications in advancing our knowledge of PPIs in various biological contexts.

A Tiny Viral Protein, SARS-CoV-2-ORF7b: Functional Molecular Mechanisms

This study presents the interaction with the human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a protein-protein interaction network analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2753 proven interactions and 1708 interactors specific to ORF7b. We used these proteins as functional seeds, and we obtained a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. By following a hub-and-spoke network architectural model, we were able to identify seven proteins that ranked high as hubs and an additional seven as bottlenecks. Through this interaction model, we identified significant GO-processes (5057 terms in 15 categories) induced in human metabolism by ORF7b. We discovered high statistical significance processes of dysregulated molecular cell mechanisms caused by acting ORF7b. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems, and the molecular mechanisms that supervise programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant Connected Component core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation and transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes within the limits of the poor knowledge that these sectors still impose.

New-onset or relapse of uveitis after rapid spreading of COVID-19 infection in China and risk factor analysis for relapse

BACKGROUND

The aim of this study was to report the clinical profile of new-onset and relapse of uveitis following rapid spreading of coronavirus disease 2019 (COVID-19) infection due to change of anti-COVID-19 policies in China and investigate potential risk factors for inflammation relapse.

METHODS

In this retrospective case-control study, patients with new-onset or a history of uveitis between December 23, 2022, and February 28, 2023, were included to assess the influence of COVID-19 infection on uveitis. Detailed information on demographic data, clinical characteristics, treatment measures, treatment response, and ocular inflammatory status before and after COVID-19 infection was collected.

RESULTS

This study included 349 patients with a history of uveitis. The uveitis relapse rate was higher (28.8%, n = 288) in those with COVID-19 infection than in patients without COVID-19 infection (14.8%, n = 61) (P = 0.024). Among the relapse cases, 50.8% experienced a relapse of anterior uveitis, while 49.2% had a relapse of uveitis involving the posterior segment. Multivariable regression analysis indicated a positive correlation between disease duration and uveitis relapse, while the last relapse exceeding one year before COVID-19 infection and the use of methotrexate during COVID-19 infection were negatively correlated with relapse of uveitis. Thirteen patients who developed new-onset uveitis following COVID-19 infection were included; among them, three (23.1%) had anterior uveitis and 10 (76.9%) had uveitis affecting the posterior segment. Regarding cases involving the posterior segment, four patients (30.8%) were diagnosed with Vogt-Koyanagi-Harada disease.

CONCLUSIONS

COVID-19 infection increases the rate of uveitis relapse. Long disease duration is a risk factor, while time since the last relapse more than 1 year and methotrexate use are protective factors against uveitis relapse.

ER-export and ARFRP1/AP-1-dependent delivery of SARS-CoV-2 Envelope to lysosomes controls late stages of viral replication

The β-coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the global COVID-19 pandemic. Coronaviral Envelope (E) proteins are pentameric viroporins that play essential roles in assembly, release, and pathogenesis. We developed a nondisruptive tagging strategy for SARS-CoV-2 E and find that, at steady state, it localizes to the Golgi and to lysosomes. We identify sequences in E, conserved across Coronaviridae, responsible for endoplasmic reticulum-to-Golgi export, and relate this activity to interaction with COP-II via SEC24. Using proximity biotinylation, we identify an ADP ribosylation factor 1/adaptor protein-1 (ARFRP1/AP-1)-dependent pathway allowing Golgi-to-lysosome trafficking of E. We identify sequences in E that bind AP-1, are conserved across β-coronaviruses, and allow E to be trafficked from Golgi to lysosomes. We show that E acts to deacidify lysosomes and, by developing a trans-complementation assay for SARS-CoV-2 structural proteins, that lysosomal delivery of E and its viroporin activity is necessary for efficient viral replication and release.

Precision nutrition to reset virus-induced human metabolic reprogramming and dysregulation (HMRD) in long-COVID

SARS-CoV-2, the etiological agent of COVID-19, is devoid of any metabolic capacity; therefore, it is critical for the viral pathogen to hijack host cellular metabolic machinery for its replication and propagation. This single-stranded RNA virus with a 29.9 kb genome encodes 14 open reading frames (ORFs) and initiates a plethora of virus-host protein-protein interactions in the human body. These extensive viral protein interactions with host-specific cellular targets could trigger severe human metabolic reprogramming/dysregulation (HMRD), a rewiring of sugar-, amino acid-, lipid-, and nucleotide-metabolism(s), as well as altered or impaired bioenergetics, immune dysfunction, and redox imbalance in the body. In the infectious process, the viral pathogen hijacks two major human receptors, angiotensin-converting enzyme (ACE)-2 and/or neuropilin (NRP)-1, for initial adhesion to cell surface; then utilizes two major host proteases, TMPRSS2 and/or furin, to gain cellular entry; and finally employs an endosomal enzyme, cathepsin L (CTSL) for fusogenic release of its viral genome. The virus-induced HMRD results in 5 possible infectious outcomes: asymptomatic, mild, moderate, severe to fatal episodes; while the symptomatic acute COVID-19 condition could manifest into 3 clinical phases: (i) hypoxia and hypoxemia (Warburg effect), (ii) hyperferritinemia ('cytokine storm'), and (iii) thrombocytosis (coagulopathy). The mean incubation period for COVID-19 onset was estimated to be 5.1 days, and most cases develop symptoms after 14 days. The mean viral clearance times were 24, 30, and 39 days for acute, severe, and ICU-admitted COVID-19 patients, respectively. However, about 25-70% of virus-free COVID-19 survivors continue to sustain virus-induced HMRD and exhibit a wide range of symptoms that are persistent, exacerbated, or new 'onset' clinical incidents, collectively termed as post-acute sequelae of COVID-19 (PASC) or long COVID. PASC patients experience several debilitating clinical condition(s) with >200 different and overlapping symptoms that may last for weeks to months. Chronic PASC is a cumulative outcome of at least 10 different HMRD-related pathophysiological mechanisms involving both virus-derived virulence factors and a multitude of innate host responses. Based on HMRD and virus-free clinical impairments of different human organs/systems, PASC patients can be categorized into 4 different clusters or sub-phenotypes: sub-phenotype-1 (33.8%) with cardiac and renal manifestations; sub-phenotype-2 (32.8%) with respiratory, sleep and anxiety disorders; sub-phenotype-3 (23.4%) with skeleto-muscular and nervous disorders; and sub-phenotype-4 (10.1%) with digestive and pulmonary dysfunctions. This narrative review elucidates the effects of viral hijack on host cellular machinery during SARS-CoV-2 infection, ensuing detrimental effect(s) of virus-induced HMRD on human metabolism, consequential symptomatic clinical implications, and damage to multiple organ systems; as well as chronic pathophysiological sequelae in virus-free PASC patients. We have also provided a few evidence-based, human randomized controlled trial (RCT)-tested, precision nutrients to reset HMRD for health recovery of PASC patients.

SARS-CoV-2 targets ribosomal RNA biogenesis

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) hinders host gene expression, curbing defenses and licensing viral protein synthesis and virulence. During SARS-CoV-2 infection, the virulence factor non-structural protein 1 (Nsp1) targets the mRNA entry channel of mature cytoplasmic ribosomes, limiting translation. We show that Nsp1 also restrains translation by targeting nucleolar ribosome biogenesis. SARS-CoV-2 infection disrupts 18S and 28S ribosomal RNA (rRNA) processing. Expression of Nsp1 recapitulates the processing defects. Nsp1 abrogates rRNA production without altering the expression of critical processing factors or nucleolar organization. Instead, Nsp1 localizes to the nucleolus, interacting with precursor-rRNA and hindering its maturation separately from the viral protein's role in restricting mature ribosomes. Thus, SARS-CoV-2 Nsp1 limits translation by targeting ribosome biogenesis and mature ribosomes. These findings revise our understanding of how SARS-CoV-2 Nsp1 controls human protein synthesis, suggesting that efforts to counter Nsp1's effect on translation should consider the protein's impact from ribosome manufacturing to mature ribosomes.

Interaction between host G3BP and viral nucleocapsid protein regulates SARS-CoV-2 replication and pathogenicity

G3BP1/2 are paralogous proteins that promote stress granule formation in response to cellular stresses, including viral infection. The nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibits stress granule assembly and interacts with G3BP1/2 via an ITFG motif, including residue F17, in the N protein. Prior studies examining the impact of the G3PB1-N interaction on SARS-CoV-2 replication have produced inconsistent findings, and the role of this interaction in pathogenesis is unknown. Here, we use structural and biochemical analyses to define the residues required for G3BP1-N interaction and structure-guided mutagenesis to selectively disrupt this interaction. We find that N-F17A mutation causes highly specific loss of interaction with G3BP1/2. SARS-CoV-2 N-F17A fails to inhibit stress granule assembly in cells, has decreased viral replication, and causes decreased pathology in vivo. Further mechanistic studies indicate that the N-F17-mediated G3BP1-N interaction promotes infection by limiting sequestration of viral genomic RNA (gRNA) into stress granules.

Drug repurposing platform for deciphering the druggable SARS-CoV-2 interactome

The coronavirus disease 2019 (COVID-19) pandemic has heavily challenged the global healthcare system. Despite the vaccination programs, the new virus variants are circulating. Further research is required for understanding of the biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and for discovery of therapeutic agents against the virus. Here, we took advantage of drug repurposing to identify if existing drugs could inhibit SARS-CoV-2 infection. We established an open high throughput platform for in vitro screening of drugs against SARS-CoV-2 infection. We screened ∼1000 drugs for their ability to inhibit SARS-CoV-2-induced cell death in the African green monkey kidney cell line (Vero-E6), analyzed how the hit compounds affect the viral N (nucleocapsid) protein expression in human cell lines using high-content microscopic imaging and analysis, determined the hit drug targets in silico, and assessed their ability to cause phospholipidosis, which can interfere with the viral replication. Duvelisib was found by in silico interaction assay as a potential drug targeting virus-host protein interactions. The predicted interaction between PARP1 and S protein, affected by Duvelisib, was further validated by immunoprecipitation. Our results represent a rapidly applicable platform for drug repurposing and evaluation of the new emerging viruses' responses to the drugs. Further in silico studies help us to discover the druggable host pathways involved in the infectious cycle of SARS-CoV-2.

Priority index for critical Covid-19 identifies clinically actionable targets and drugs

While genome-wide studies have identified genomic loci in hosts associated with life-threatening Covid-19 (critical Covid-19), the challenge of resolving these loci hinders further identification of clinically actionable targets and drugs. Building upon our previous success, we here present a priority index solution designed to address this challenge, generating the target and drug resource that consists of two indexes: the target index and the drug index. The primary purpose of the target index is to identify clinically actionable targets by prioritising genes associated with Covid-19. We illustrate the validity of the target index by demonstrating its ability to identify pre-existing Covid-19 phase-III drug targets, with the majority of these targets being found at the leading prioritisation (leading targets). These leading targets have their evolutionary origins in Amniota ('four-leg vertebrates') and are predominantly involved in cytokine-cytokine receptor interactions and JAK-STAT signaling. The drug index highlights opportunities for repurposing clinically approved JAK-STAT inhibitors, either individually or in combination. This proposed strategic focus on the JAK-STAT pathway is supported by the active pursuit of therapeutic agents targeting this pathway in ongoing phase-II/III clinical trials for Covid-19.

Identification of potential therapeutic targets for COVID-19 through a structural-based similarity approach between SARS-CoV-2 and its human host proteins

Background: The COVID-19 pandemic caused by SARS-CoV-2 has led to millions of deaths worldwide, and vaccination efficacy has been decreasing with each lineage, necessitating the need for alternative antiviral therapies. Predicting host-virus protein-protein interactions (HV-PPIs) is essential for identifying potential host-targeting drug targets against SARS-CoV-2 infection. Objective: This study aims to identify therapeutic target proteins in humans that could act as virus-host-targeting drug targets against SARS-CoV-2 and study their interaction against antiviral inhibitors. Methods: A structure-based similarity approach was used to predict human proteins similar to SARS-CoV-2 ("hCoV-2"), followed by identifying PPIs between hCoV-2 and its target human proteins. Overlapping genes were identified between the protein-coding genes of the target and COVID-19-infected patient's mRNA expression data. Pathway and Gene Ontology (GO) term analyses, the construction of PPI networks, and the detection of hub gene modules were performed. Structure-based virtual screening with antiviral compounds was performed to identify potential hits against target gene-encoded protein. Results: This study predicted 19,051 unique target human proteins that interact with hCoV-2, and compared to the microarray dataset, 1,120 target and infected group differentially expressed genes (TIG-DEGs) were identified. The significant pathway and GO enrichment analyses revealed the involvement of these genes in several biological processes and molecular functions. PPI network analysis identified a significant hub gene with maximum neighboring partners. Virtual screening analysis identified three potential antiviral compounds against the target gene-encoded protein. Conclusion: This study provides potential targets for host-targeting drug development against SARS-CoV-2 infection, and further experimental validation of the target protein is required for pharmaceutical intervention.

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and the emergence of drug resistance. Host-based antivirals are an alternative, but can cause nonspecific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR knockout (KO) screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting antiviral SL drug targets. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Our comparison of SARS-CoV-2 and influenza infection data revealed potential broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

Human-virus protein-protein interactions maps assist in revealing the pathogenesis of viral infection

Many significant viral infections have been recorded in human history, which have caused enormous negative impacts worldwide. Human-virus protein-protein interactions (PPIs) mediate viral infection and immune processes in the host. The identification, quantification, localization, and construction of human-virus PPIs maps are critical prerequisites for understanding the biophysical basis of the viral invasion process and characterising the framework for all protein functions. With the technological revolution and the introduction of artificial intelligence, the human-virus PPIs maps have been expanded rapidly in the past decade and shed light on solving complicated biomedical problems. However, there is still a lack of prospective insight into the field. In this work, we comprehensively review and compare the effectiveness, potential, and limitations of diverse approaches for constructing large-scale PPIs maps in human-virus, including experimental methods based on biophysics and biochemistry, databases of human-virus PPIs, computational methods based on artificial intelligence, and tools for visualising PPIs maps. The work aims to provide a toolbox for researchers, hoping to better assist in deciphering the relationship between humans and viruses.

EPHA2 Receptor as a Possible Therapeutic Target in Viral Infections

BACKGROUND

The receptor tyrosine kinase EphA2 plays a role in many diseases, like cancer, cataracts, and osteoporosis. Interestingly, it has also been linked to viral infections.

OBJECTIVE

Herein, current literature has been reviewed to clarify EphA2 functions in viral infections and explore its potential role as a target in antiviral drug discovery strategies.

METHODS

Research and review articles along with preprints connecting EphA2 to different viruses have been searched through PubMed and the web. Structures of complexes between EphA2 domains and viral proteins have been retrieved from the PDB database.

RESULTS

EphA2 assumes a key role in Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein Barr virus (EBV) infections by directly binding, through its ligand binding domain, viral glycoproteins. For human cytomegalovirus (HCMV), the role of EphA2 in maintaining virus latency state, through cooperation with specific viral proteins, has also been speculated. In certain cells, with high EphA2 expression levels, following ligand stimulation, receptor activation might contribute to severe symptoms accompanying a few viral infections, including lung injuries often related to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).

CONCLUSION

Since EphA2 works as a host receptor for certain viruses, it might be worth more deeply investigating known compounds targeting its extracellular ligand binding domain as antiviral therapeutics. Due to EphA2's function in inflammation, its possible correlation with SARS-CoV-2 cannot be excluded, but more experimental studies are needed in this case to undoubtedly attribute the role of this receptor in viral infections.

A Narrative Overview of Coronavirus Infection: Clinical Signs and Symptoms, Viral Entry and Replication, Treatment Modalities, and Management

The global pandemic known as coronavirus disease (COVID-19) is causing morbidity and mortality on a daily basis. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV- -2) virus has been around since December 2019 and has infected a high number of patients due to its idiopathic pathophysiology and rapid transmission. COVID-19 is now deemed a newly identified "syndrome" condition since it causes a variety of unpleasant symptoms and systemic side effects following the pandemic. Simultaneously, it always becomes potentially hazardous when new variants develop during evolution. Its random viral etiology prevents accurate and suitable therapy. Despite the fact that multiple preclinical and research studies have been conducted to combat this lethal virus, and various therapeutic targets have been identified, the precise course of therapy remains uncertain. However, just a few drugs have shown efficacy in treating this viral infection in its early stages. Currently, several medicines and vaccinations have been licensed following clinical trial research, and many countries are competing to find the most potent and effective immunizations against this highly transmissible illness. For this narrative review, we used PubMed, Google Scholar, and Scopus to obtain epidemiological data, pre-clinical and clinical trial outcomes, and recent therapeutic alternatives for treating COVID-19 viral infection. In this study, we discussed the disease's origin, etiology, transmission, current advances in clinical diagnostic technologies, different new therapeutic targets, pathophysiology, and future therapy options for this devastating virus. Finally, this review delves further into the hype surrounding the SARS-CoV-2 illness, as well as present and potential COVID-19 therapies.

Aminoacyl-tRNA synthetase interactions in SARS-CoV-2 infection

Aminoacyl-tRNA synthetases (aaRSs) are ancient enzymes that serve a foundational role in the efficient and accurate translation of genetic information from messenger RNA to proteins. These proteins play critical, non-canonical functions in a multitude of cellular processes. Multiple viruses are known to hijack the functions of aaRSs for proviral outcomes, while cells modify antiviral responses through non-canonical functions of certain synthetases. Recent findings have revealed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronaviral disease 19 (COVID-19), utilizes canonical and non-canonical functions of aaRSs, establishing a complex interplay of viral proteins, cellular factors and host aaRSs. In a striking example, an unconventional multi-aaRS complex consisting of glutamyl-prolyl-, lysyl-, arginyl- and methionyl-tRNA synthetases interact with a previously unknown RNA-element in the 3'-end of SARS-CoV-2 genomic and subgenomic RNAs. This review aims to highlight the aaRS-SARS-CoV-2 interactions identified to date, with possible implications for the biology of host aaRSs in SARS-CoV-2 infection.

Leishmania infection upregulates and engages host macrophage Argonaute 1, and system-wide proteomics reveals Argonaute 1-dependent host response

Leishmania donovani, an intracellular protozoan parasite, is the causative agent of visceral leishmaniasis, the most severe form of leishmaniasis in humans. It is becoming increasingly clear that several intracellular pathogens target host cell RNA interference (RNAi) pathways to promote their survival. Complexes of Argonaute proteins with small RNAs are core components of the RNAi. In this study, we investigated the potential role of host macrophage Argonautes in Leishmania pathogenesis. Using Western blot analysis of Leishmania donovani-infected macrophages, we show here that Leishmania infection selectively increased the abundance of host Argonaute 1 (Ago1). This increased abundance of Ago1 in infected cells also resulted in higher levels of Ago1 in active Ago-complexes, suggesting the preferred use of Ago1 in RNAi in Leishmania-infected cells. This analysis used a short trinucleotide repeat containing 6 (TNRC6)/glycine-tryptophan repeat protein (GW182) protein-derived peptide fused to Glutathione S-transferase as an affinity matrix to capture mature Ago-small RNAs complexes from the cytosol of non-infected and Leishmania-infected cells. Furthermore, Ago1 silencing significantly reduced intracellular survival of Leishmania, demonstrating that Ago1 is essential for Leishmania pathogenesis. To investigate the role of host Ago1 in Leishmania pathogenesis, a quantitative whole proteome approach was employed, which showed that expression of several previously reported Leishmania pathogenesis-related proteins was dependent on the level of macrophage Ago1. Together, these findings identify Ago1 as the preferred Argonaute of RNAi machinery in infected cells and a novel and essential virulence factor by proxy that promotes Leishmania survival.

SARS-CoV-2 and the DNA damage response

The recent coronavirus disease 2019 (COVID-19) pandemic was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is characterized by respiratory distress, multiorgan dysfunction and, in some cases, death. The virus is also responsible for post-COVID-19 condition (commonly referred to as 'long COVID'). SARS-CoV-2 is a single-stranded, positive-sense RNA virus with a genome of approximately 30 kb, which encodes 26 proteins. It has been reported to affect multiple pathways in infected cells, resulting, in many cases, in the induction of a 'cytokine storm' and cellular senescence. Perhaps because it is an RNA virus, replicating largely in the cytoplasm, the effect of SARS-Cov-2 on genome stability and DNA damage responses (DDRs) has received relatively little attention. However, it is now becoming clear that the virus causes damage to cellular DNA, as shown by the presence of micronuclei, DNA repair foci and increased comet tails in infected cells. This review considers recent evidence indicating how SARS-CoV-2 causes genome instability, deregulates the cell cycle and targets specific components of DDR pathways. The significance of the virus's ability to cause cellular senescence is also considered, as are the implications of genome instability for patients suffering from long COVID.

The REEP5/TRAM1 complex binds SARS-CoV-2 NSP3 and promotes virus replication

IMPORTANCE

Generation of virus-host protein-protein interactions (PPIs) maps may provide clues to uncover SARS-CoV-2-hijacked cellular processes. However, these PPIs maps were created by expressing each viral protein singularly, which does not reflect the life situation in which certain viral proteins synergistically interact with host proteins. Our results reveal the host-viral protein-protein interactome of SARS-CoV-2 NSP3, NSP4, and NSP6 expressed individually or in combination. Furthermore, REEP5/TRAM1 complex interacts with NSP3 at ROs and promotes viral replication. The significance of our research is identifying virus-host interactions that may be targeted for therapeutic intervention.

Dual spatially resolved transcriptomics for human host-pathogen colocalization studies in FFPE tissue sections

Technologies to study localized host-pathogen interactions are urgently needed. Here, we present a spatial transcriptomics approach to simultaneously capture host and pathogen transcriptome-wide spatial gene expression information from human formalin-fixed paraffin-embedded (FFPE) tissue sections at a near single-cell resolution. We demonstrate this methodology in lung samples from COVID-19 patients and validate our spatial detection of SARS-CoV-2 against RNAScope and in situ sequencing. Host-pathogen colocalization analysis identified putative modulators of SARS-CoV-2 infection in human lung cells. Our approach provides new insights into host response to pathogen infection through the simultaneous, unbiased detection of two transcriptomes in FFPE samples.

NME3 binds to phosphatidic acid and mediates PLD6-induced mitochondrial tethering

Mitochondria are dynamic organelles regulated by fission and fusion processes. The fusion of membranes requires elaborative coordination of proteins and lipids and is particularly crucial for the function and quality control of mitochondria. Phosphatidic acid (PA) on the mitochondrial outer membrane generated by PLD6 facilitates the fusion of mitochondria. However, how PA promotes mitochondrial fusion remains unclear. Here, we show that a mitochondrial outer membrane protein, NME3, is required for PLD6-induced mitochondrial tethering or clustering. NME3 is enriched at the contact interface of two closely positioned mitochondria depending on PLD6, and NME3 binds directly to PA-exposed lipid packing defects via its N-terminal amphipathic helix. The PA binding function and hexamerization confer NME3 mitochondrial tethering activity. Importantly, nutrient starvation enhances the enrichment efficiency of NME3 at the mitochondrial contact interface, and the tethering ability of NME3 contributes to fusion efficiency. Together, our findings demonstrate NME3 as a tethering protein promoting selective fusion between PLD6-remodeled mitochondria for quality control.

Current Perspectives in Antiviral Research

Studies on virus-host interactions are of high significance for a number of reasons [...].

Identification of motif-based interactions between SARS-CoV-2 protein domains and human peptide ligands pinpoint antiviral targets

The virus life cycle depends on host-virus protein-protein interactions, which often involve a disordered protein region binding to a folded protein domain. Here, we used proteomic peptide phage display (ProP-PD) to identify peptides from the intrinsically disordered regions of the human proteome that bind to folded protein domains encoded by the SARS-CoV-2 genome. Eleven folded domains of SARS-CoV-2 proteins were found to bind 281 peptides from human proteins, and affinities of 31 interactions involving eight SARS-CoV-2 protein domains were determined (KD ∼ 7-300 μM). Key specificity residues of the peptides were established for six of the interactions. Two of the peptides, binding Nsp9 and Nsp16, respectively, inhibited viral replication. Our findings demonstrate how high-throughput peptide binding screens simultaneously identify potential host-virus interactions and peptides with antiviral properties. Furthermore, the high number of low-affinity interactions suggest that overexpression of viral proteins during infection may perturb multiple cellular pathways.

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and development of drug resistance. Host-based antivirals, while an alternative, may lead to non-specific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR KO screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting SL drug targets of viral infections. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Comparing data from SARS-CoV-2 and influenza infections, we found possible broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

A New Cellular Interactome of SARS-CoV-2 Nucleocapsid Protein and Its Biological Implications

There is still much to uncover regarding the molecular details of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. As the most abundant protein, coronavirus nucleocapsid (N) protein encapsidates viral RNAs, serving as the structural component of ribonucleoprotein and virion, and participates in transcription, replication, and host regulations. Virus-host interaction might give clues to better understand how the virus affects or is affected by its host during infection and identify promising therapeutic candidates. Considering the critical roles of N, we here established a new cellular interactome of SARS-CoV-2 N by using a high-specific affinity purification (S-pulldown) assay coupled with quantitative mass spectrometry and immunoblotting validations, uncovering many N-interacting host proteins unreported previously. Bioinformatics analysis revealed that these host factors are mainly involved in translation regulations, viral transcription, RNA processes, stress responses, protein folding and modification, and inflammatory/immune signaling pathways, in line with the supposed actions of N in viral infection. Existing pharmacological cellular targets and the directing drugs were then mined, generating a drug-host protein network. Accordingly, we experimentally identified several small-molecule compounds as novel inhibitors against SARS-CoV-2 replication. Furthermore, a newly identified host factor, DDX1, was verified to interact and colocalize with N mainly by binding to the N-terminal domain of the viral protein. Importantly, loss/gain/reconstitution-of-function experiments showed that DDX1 acts as a potent anti-SARS-CoV-2 host factor, inhibiting the viral replication and protein expression. The N-targeting and anti-SARS-CoV-2 abilities of DDX1 are consistently independent of its ATPase/helicase activity. Further mechanism studies revealed that DDX1 impedes multiple activities of N, including the N-N interaction, N oligomerization, and N-viral RNA binding, thus likely inhibiting viral propagation. These data provide new clues to better depiction of the N-cell interactions and SARS-CoV-2 infection and may help inform the development of new therapeutic candidates.

Interaction between host G3BP and viral nucleocapsid protein regulates SARS-CoV-2 replication

G3BP1/2 are paralogous proteins that promote stress granule formation in response to cellular stresses, including viral infection. G3BP1/2 are prominent interactors of the nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the functional consequences of the G3BP1-N interaction in the context of viral infection remain unclear. Here we used structural and biochemical analyses to define the residues required for G3BP1-N interaction, followed by structure-guided mutagenesis of G3BP1 and N to selectively and reciprocally disrupt their interaction. We found that mutation of F17 within the N protein led to selective loss of interaction with G3BP1 and consequent failure of the N protein to disrupt stress granule assembly. Introduction of SARS-CoV-2 bearing an F17A mutation resulted in a significant decrease in viral replication and pathogenesis in vivo, indicating that the G3BP1-N interaction promotes infection by suppressing the ability of G3BP1 to form stress granules.

SEMtree: tree-based structure learning methods with structural equation models

MOTIVATION

With the exponential growth of expression and protein-protein interaction (PPI) data, the identification of functional modules in PPI networks that show striking changes in molecular activity or phenotypic signatures becomes of particular interest to reveal process-specific information that is correlated with cellular or disease states. This requires both the identification of network nodes with reliability scores and the availability of an efficient technique to locate the network regions with the highest scores. In the literature, a number of heuristic methods have been suggested. We propose SEMtree(), a set of tree-based structure discovery algorithms, combining graph and statistically interpretable parameters together with a user-friendly R package based on structural equation models framework.

RESULTS

Condition-specific changes from differential expression and gene-gene co-expression are recovered with statistical testing of node, directed edge, and directed path difference between groups. In the end, from a list of seed (i.e. disease) genes or gene P-values, the perturbed modules with undirected edges are generated with five state-of-the-art active subnetwork detection methods. The latter are supplied to causal additive trees based on Chu-Liu-Edmonds' algorithm (Chow and Liu, Approximating discrete probability distributions with dependence trees. IEEE Trans Inform Theory 1968;14:462-7) in SEMtree() to be converted in directed trees. This conversion allows to compare the methods in terms of directed active subnetworks. We applied SEMtree() to both Coronavirus disease (COVID-19) RNA-seq dataset (GEO accession: GSE172114) and simulated datasets with various differential expression patterns. Compared to existing methods, SEMtree() is able to capture biologically relevant subnetworks with simple visualization of directed paths, good perturbation extraction, and classifier performance.

AVAILABILITY AND IMPLEMENTATION

SEMtree() function is implemented in the R package SEMgraph, easily available at https://CRAN.R-project.org/package=SEMgraph.

Repurposing Drugs for the Treatment of COVID-19 and Its Cardiovascular Manifestations

COVID-19 is an infectious disease caused by SARS-CoV-2 leading to the ongoing global pandemic. Infected patients developed a range of respiratory symptoms, including respiratory failure, as well as other extrapulmonary complications. Multiple comorbidities, including hypertension, diabetes, cardiovascular diseases, and chronic kidney diseases, are associated with the severity and increased mortality of COVID-19. SARS-CoV-2 infection also causes a range of cardiovascular complications, including myocarditis, myocardial injury, heart failure, arrhythmias, acute coronary syndrome, and venous thromboembolism. Although a variety of methods have been developed and many clinical trials have been launched for drug repositioning for COVID-19, treatments that consider cardiovascular manifestations and cardiovascular disease comorbidities specifically are limited. In this review, we summarize recent advances in drug repositioning for COVID-19, including experimental drug repositioning, high-throughput drug screening, omics data-based, and network medicine-based computational drug repositioning, with particular attention on those drug treatments that consider cardiovascular manifestations of COVID-19. We discuss prospective opportunities and potential methods for repurposing drugs to treat cardiovascular complications of COVID-19.

DHFR Inhibitors Display a Pleiotropic Anti-Viral Activity against SARS-CoV-2: Insights into the Mechanisms of Action

During the COVID-19 pandemic, drug repurposing represented an effective strategy to obtain quick answers to medical emergencies. Based on previous data on methotrexate (MTX), we evaluated the anti-viral activity of several DHFR inhibitors in two cell lines. We observed that this class of compounds showed a significant influence on the virus-induced cytopathic effect (CPE) partly attributed to the intrinsic anti-metabolic activity of these drugs, but also to a specific anti-viral function. To elucidate the molecular mechanisms, we took advantage of our EXSCALATE platform for in-silico molecular modelling and further validated the influence of these inhibitors on nsp13 and viral entry. Interestingly, pralatrexate and trimetrexate showed superior effects in counteracting the viral infection compared to other DHFR inhibitors. Our results indicate that their higher activity is due to their polypharmacological and pleiotropic profile. These compounds can thus potentially give a clinical advantage in the management of SARS-CoV-2 infection in patients already treated with this class of drugs.

Large-scale phage-based screening reveals extensive pan-viral mimicry of host short linear motifs

Viruses mimic host short linear motifs (SLiMs) to hijack and deregulate cellular functions. Studies of motif-mediated interactions therefore provide insight into virus-host dependencies, and reveal targets for therapeutic intervention. Here, we describe the pan-viral discovery of 1712 SLiM-based virus-host interactions using a phage peptidome tiling the intrinsically disordered protein regions of 229 RNA viruses. We find mimicry of host SLiMs to be a ubiquitous viral strategy, reveal novel host proteins hijacked by viruses, and identify cellular pathways frequently deregulated by viral motif mimicry. Using structural and biophysical analyses, we show that viral mimicry-based interactions have similar binding strength and bound conformations as endogenous interactions. Finally, we establish polyadenylate-binding protein 1 as a potential target for broad-spectrum antiviral agent development. Our platform enables rapid discovery of mechanisms of viral interference and the identification of potential therapeutic targets which can aid in combating future epidemics and pandemics.

Selenoprotein S Interacts with the Replication and Transcription Complex of SARS-CoV-2 by Binding nsp7

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replicates and evades detection using ER membranes and their associated protein machinery. Among these hijacked human proteins is selenoprotein S (selenos). This selenoprotein takes part in the protein quality control, signaling, and the regulation of cytokine secretion. While the role of selenos in the viral life cycle is not yet known, it has been reported to interact with SARS-CoV-2 nonstructural protein 7 (nsp7), a viral protein essential for the replication of the virus. We set to study whether selenos and nsp7 interact directly and if they can still bind when nsp7 is bound to the replication and transcription complex of the virus. Using biochemical assays, we show that selenos binds directly to nsp7. In addition, we found that selenos can bind to nsp7 when it is in a complex with the coronavirus's minimal replication and transcription complex, comprised of nsp7, nsp8, and the RNA-dependent RNA polymerase nsp12. In addition, through crosslinking experiments, we mapped the interaction sites of selenos and nsp7 in the replication complex and showed that the hydrophobic segment of selenos is essential for binding to nsp7. This arrangement leaves an extended helix and the intrinsically disordered segment of selenos-including the reactive selenocysteine-exposed and free to potentially recruit additional proteins to the replication and transcription complex.

SARS-CoV-2 infection induces DNA damage, through CHK1 degradation and impaired 53BP1 recruitment, and cellular senescence

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Although SARS-CoV-2 was reported to alter several cellular pathways, its impact on DNA integrity and the mechanisms involved remain unknown. Here we show that SARS-CoV-2 causes DNA damage and elicits an altered DNA damage response. Mechanistically, SARS-CoV-2 proteins ORF6 and NSP13 cause degradation of the DNA damage response kinase CHK1 through proteasome and autophagy, respectively. CHK1 loss leads to deoxynucleoside triphosphate (dNTP) shortage, causing impaired S-phase progression, DNA damage, pro-inflammatory pathways activation and cellular senescence. Supplementation of deoxynucleosides reduces that. Furthermore, SARS-CoV-2 N-protein impairs 53BP1 focal recruitment by interfering with damage-induced long non-coding RNAs, thus reducing DNA repair. Key observations are recapitulated in SARS-CoV-2-infected mice and patients with COVID-19. We propose that SARS-CoV-2, by boosting ribonucleoside triphosphate levels to promote its replication at the expense of dNTPs and by hijacking damage-induced long non-coding RNAs' biology, threatens genome integrity and causes altered DNA damage response activation, induction of inflammation and cellular senescence.

Repurposing of known drugs for COVID-19 using molecular docking and simulation analysis

We selected fifty one drugs already known for their potential disease treatment roles in various studies and subjected to docking and molecular docking simulation (MDS) analyses. Five of them showed promising features that are discussed and suggested as potential candidates for repurposing for COVID-19. These top five compounds were boswellic acid, pimecrolimus, GYY-4137, BMS-345541 and triamcinolone hexacetonide that interacted with the chosen receptors 1R42, 4G3D, 6VW1, 6VXX and 7MEQ, respectively with binding energies of -9.2 kcal/mol, -9.1 kcal/mol, -10.3 kcal/mol, -10.1 kcal/mol and -8.7 kcal/mol, respectively. The MDS studies for the top 5 best complexes revealed binding features for the chosen receptor, human NF-kappa B transcription factor as an important drug target in COVID-19-based drug development strategies.

Atlas of interactions between SARS-CoV-2 macromolecules and host proteins

The proteins and RNAs of viruses extensively interact with host proteins after infection. We collected and reanalyzed all available datasets of protein-protein and RNA-protein interactions related to SARS-CoV-2. We investigated the reproducibility of those interactions and made strict filters to identify highly confident interactions. We systematically analyzed the interaction network and identified preferred subcellular localizations of viral proteins, some of which such as ORF8 in ER and ORF7A/B in ER membrane were validated using dual fluorescence imaging. Moreover, we showed that viral proteins frequently interact with host machinery related to protein processing in ER and vesicle-associated processes. Integrating the protein- and RNA-interactomes, we found that SARS-CoV-2 RNA and its N protein closely interacted with stress granules including 40 core factors, of which we specifically validated G3BP1, IGF2BP1, and MOV10 using RIP and Co-IP assays. Combining CRISPR screening results, we further identified 86 antiviral and 62 proviral factors and associated drugs. Using network diffusion, we found additional 44 interacting proteins including two proviral factors previously validated. Furthermore, we showed that this atlas could be applied to identify the complications associated with COVID-19. All data are available in the AIMaP database (https://mvip.whu.edu.cn/aimap/) for users to easily explore the interaction map.

Regdanvimab for patients with mild-to-moderate COVID-19: a retrospective cohort study and subgroup analysis of patients with the Delta variant

OBJECTIVES

To evaluate efficacy and safety of regdanvimab, a neutralizing antibody, in patients with mild-to-moderate severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) including against the Delta variant.

METHODS

A single-center, retrospective, observational cohort study in adults with confirmed coronavirus disease 2019 (COVID-19). The primary endpoint was the proportion of patients deteriorating with peripheral oxygen saturation <90% in room air, requiring supplemental oxygen therapy above high flow, or experiencing mortality due to COVID-19 up to Day 28.

RESULTS

722 patients were eligible; 418 received regdanvimab and 304 received standard of care (SoC) of whom 71.1% (297/418, regdanvimab) and 37.8% (115/304, SoC) were infected with the Delta variant. The proportion of patients with a primary endpoint event was significantly lower with regdanvimab versus SoC (3.1% vs 9.9%; difference: -6.8 [95% confidence interval: -10.9, -2.8]; P=0.0002). A similar trend was observed in the Delta variant subgroup (regdanvimab, 2.7% vs SoC, 7.0%; difference -4.3 [95% CI: -10.8, 0.2]; P=0.0827). Secondary efficacy endpoints supported primary analysis findings in the overall cohort and Delta variant subgroup. No new safety signals were identified.

CONCLUSIONS

Regdanvimab demonstrated clinical efficacy in the overall cohort and may provide a clinical benefit for patients with mild-to-moderate COVID-19, infected with the Delta variant.

Analyzing Protein Interactions by MAC-Tag Approaches

Proteomics methods such as affinity purification (AP) and proximity-dependent labeling (PL) coupled with mass spectrometry (MS) are currently commonly utilized to define interaction landscapes. BioID is one of the PL approaches, and it employs the expression of bait proteins fused to a nonspecific biotin ligase (BirA*), to induce in vivo biotinylation of proximal proteins. We developed the multiple approaches combined (MAC)-tag workflow, which allows for both AP and BioID analysis with a single construct and with almost identical protein purification and MS identification procedures. MAC-tag is a well-established method and has been widely used. Recent developed PL tags such as BioID2 and UltraID are smaller versions of BirA* with faster labeling efficiency. We therefore incorporate these tags into our system to develop MAC2-tag (containing BioID2) and MAC3-tag (containing UltraID) to overcome potential limitations of the original MAC-tag system and broaden the spectrum of applications for MAC-tags. Here, we describe a detailed procedure for the MAC-tag system workflow including cell line generation for the MAC/MAC2/MAC3-tagged protein of interest (POI), sample preparation for AP and PL protein purification, and MS analysis.

Affinity-Purification Combined with Crosslinking Mass Spectrometry for Identification and Structural Modeling of Host-Pathogen Protein-Protein Complexes

Host-pathogen protein-protein interactions are highly complex and dynamic and mediate key steps in pathogen adhesion to host, host invasion, and colonization as well as immune evasion. In bacteria, these interactions most often involve specialized virulence factors or effector proteins that specifically target central host proteins. Here, I present a mass spectrometry-based proteomics approach starting with the identification of host-pathogen interactions by affinity-purification followed by mapping the specific host-pathogen protein-protein interaction interfaces by crosslinking mass spectrometry and structural modeling of the complexes.

Significance of Catecholamine Biosynthetic/Metabolic Pathway in SARS-CoV-2 Infection and COVID-19 Severity

The SARS-CoV-2 infection was previously associated with the expression of the dopamine biosynthetic enzyme L-Dopa decarboxylase (DDC). Specifically, a negative correlation was detected between DDC mRNA and SARS-CoV-2 RNA levels in in vitro infected epithelial cells and the nasopharyngeal tissue of COVID-19 patients with mild/no symptoms. However, DDC, among other genes related to both DDC expression and SARS-CoV-2-infection (ACE2, dACE2, EPO), was upregulated in these patients, possibly attributed to an orchestrated host antiviral response. Herein, by comparing DDC expression in the nasopharyngeal swab samples of severe/critical to mild COVID-19 cases, we showed a 20 mean-fold reduction, highlighting the importance of the expression of this gene as a potential marker of COVID-19 severity. Moreover, we identified an association of SARS-CoV-2 infection with the expression of key catecholamine biosynthesis/metabolism-related genes, in whole blood samples from hospitalized patients and in cultured cells. Specifically, viral infection downregulated the biosynthetic part of the dopamine pathway (reduction in DDC expression up to 7.5 mean-fold), while enhanced the catabolizing part (increase in monoamine oxidases A and B expression up to 15 and 10 mean-fold, respectively) in vivo, irrespectively of the presence of comorbidities. In accordance, dopamine levels in the sera of severe cases were reduced (up to 3.8 mean-fold). Additionally, a moderate positive correlation between DDC and MAOA mRNA levels (r = 0.527, p < 00001) in the blood was identified upon SARS-CoV-2-infection. These observations were consistent to the gene expression data from SARS-CoV-2-infected Vero E6 and A549 epithelial cells. Furthermore, L-Dopa or dopamine treatment of infected cells attenuated the virus-derived cytopathic effect by 55% and 59%, respectively. The SARS-CoV-2 mediated suppression of dopamine biosynthesis in cell culture was, at least in part, attributed to hypoxia-like conditions triggered by viral infection. These findings suggest that L-Dopa/dopamine intake may have a preventive or therapeutic value for COVID-19 patients.

Virus-host interaction networks as new antiviral drug targets for IAV and SARS-CoV-2

Currently, SARS-CoV-2, especially the Omicron strain, is ravaging the world and even co-infecting human beings with IAV, which is a serious threat to human public health. As of yet, no specific antiviral drug has been discovered for SARS-CoV-2. This requires deeper understandings of the molecular mechanisms of SARS-CoV-2-host interaction, to explore antiviral drug targets and provide theoretical basis for developing anti-SARS-CoV-2 drugs. This article discussed IAV, which has been comprehensively studied and is expected to provide the most important reference value for the SARS-CoV-2 study apart from members of the Coronaviridae family. We wish to establish a theoretical system for the studies on virus-host interaction. Previous studies have shown that host PRRs recognize RNAs of IAV or SARS-CoV-2 and then activate innate immune signaling pathways to induce the expression of host restriction factors, such as ISGs, to ultimately inhibit viral replication. Meanwhile, viruses have also evolved various regulatory mechanisms to antagonize host innate immunity at transcriptional, translational, post-translational modification, and epigenetic levels. Besides, viruses can hijack supportive host factors for their replication. Notably, the race between host antiviral innate immunity and viral antagonism of host innate immunity forms virus-host interaction networks. Additionally, the viral replication cycle is co-regulated by proteins, ncRNAs, sugars, lipids, hormones, and inorganic salts. Given this, we updated the mappings of antiviral drug targets based on virus-host interaction networks and proposed an innovative idea that virus-host interaction networks as new antiviral drug targets for IAV and SARS-CoV-2 from the perspectives of viral immunology and systems biology.

Selenoprotein S: A versatile disordered protein

Selenoprotein S (selenos) is a small, intrinsically disordered membrane protein that is associated with various cellular functions, such as inflammatory processes, cellular stress response, protein quality control, and signaling pathways. It is primarily known for its contribution to the ER-associated degradation (ERAD) pathway, which governs the extraction of misfolded proteins or misassembled protein complexes from the ER to the cytosol for degradation by the proteasome. However, selenos's other cellular roles in signaling are equally vital, including the control of transcription factors and cytokine levels. Consequently, genetic polymorphisms of selenos are associated with increased risk for diabetes, dyslipidemia, and cardiovascular diseases, while high expression levels correlate with poor prognosis in several cancers. Its inhibitory role in cytokine secretion is also exploited by viruses. Since selenos binds multiple protein complexes, however, its specific contributions to various cellular pathways and diseases have been difficult to establish. Thus, the precise cellular functions of selenos and their interconnectivity have only recently begun to emerge. This review aims to summarize recent insights into the structure, interactome, and cellular roles of selenos.

A geometric deep learning framework for drug repositioning over heterogeneous information networks

Drug repositioning (DR) is a promising strategy to discover new indicators of approved drugs with artificial intelligence techniques, thus improving traditional drug discovery and development. However, most of DR computational methods fall short of taking into account the non-Euclidean nature of biomedical network data. To overcome this problem, a deep learning framework, namely DDAGDL, is proposed to predict drug-drug associations (DDAs) by using geometric deep learning (GDL) over heterogeneous information network (HIN). Incorporating complex biological information into the topological structure of HIN, DDAGDL effectively learns the smoothed representations of drugs and diseases with an attention mechanism. Experiment results demonstrate the superior performance of DDAGDL on three real-world datasets under 10-fold cross-validation when compared with state-of-the-art DR methods in terms of several evaluation metrics. Our case studies and molecular docking experiments indicate that DDAGDL is a promising DR tool that gains new insights into exploiting the geometric prior knowledge for improved efficacy.

Pharmacogenomics deliberations of 2-deoxy-d-glucose in the treatment of COVID-19 disease: an in silico approach

The outbreak of COVID-19 caused by the coronavirus (SARS-CoV-2) prompted number of computational and laboratory efforts to discover molecules against the virus entry or replication. Simultaneously, due to the availability of clinical information, drug-repurposing efforts led to the discovery of 2-deoxy-d-glucose (2-DG) for treating COVID-19 infection. 2-DG critically accumulates in the infected cells to prevent energy production and viral replication. As there is no clarity on the impact of genetic variations on the efficacy and adverse effects of 2-DG in treating COVID-19 using in silico approaches, we attempted to extract the genes associated with the 2-DG pathway using the Comparative Toxicogenomics Database. The interaction between selected genes was assessed using ClueGO, to identify the susceptible gene loci for SARS-CoV infections. Further, SNPs that were residing in the distinct genomic regions were retrieved from the Ensembl genome browser and characterized. A total of 80 SNPs were retrieved using diverse bioinformatics resources after assessing their (a) detrimental influence on the protein stability using Swiss-model, (b) miRNA regulation employing miRNASNP3, PolymiRTS, MirSNP databases, (c) binding of transcription factors by SNP2TFBS, SNPInspector, and (d) enhancers regulation using EnhancerDB and HaploReg reported A2M rs201769751, PARP1 rs193238922 destabilizes protein, six polymorphisms of XIAP effecting microRNA binding sites, EGFR rs712829 generates 15 TFBS, BECN1 rs60221525, CASP9 rs4645980, SLC2A2 rs5393 impairs 14 TFBS, STK11 rs3795063 altered 19 regulatory motifs. These data may provide the relationship between genetic variations and drug effects of 2-DG which may further assist in assigning the right individuals to benefit from the treatment.

Open Modification Searching of SARS-CoV-2-Human Protein Interaction Data Reveals Novel Viral Modification Sites

The outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the coronavirus 2019 disease, has led to an ongoing global pandemic since 2019. Mass spectrometry can be used to understand the molecular mechanisms of viral infection by SARS-CoV-2, for example, by determining virus-host protein-protein interactions through which SARS-CoV-2 hijacks its human hosts during infection, and to study the role of post-translational modifications. We have reanalyzed public affinity purification-mass spectrometry data using open modification searching to investigate the presence of post-translational modifications in the context of the SARS-CoV-2 virus-host protein-protein interaction network. Based on an over twofold increase in identified spectra, our detected protein interactions show a high overlap with independent mass spectrometry-based SARS-CoV-2 studies and virus-host interactions for alternative viruses, as well as previously unknown protein interactions. In addition, we identified several novel modification sites on SARS-CoV-2 proteins that we investigated in relation to their interactions with host proteins. A detailed analysis of relevant modifications, including phosphorylation, ubiquitination, and S-nitrosylation, provides important hypotheses about the functional role of these modifications during viral infection by SARS-CoV-2.