African swine fever virus pCP312R interacts with host RPS27A to shut off host protein translation and promotes viral replication.

African swine fever virus (ASFV) severely threatens the global economy and food security. ASFV encodes >150 genes, but the functions of most of them have yet to be characterized in detail. Here we explored the function of the ASFV CP312R gene and found that CP312R plays an essential role in ASFV replication. Knockout of the CP312R gene terminated viral replication and CP312R knockdown substantially suppressed ASFV infection in vitro. Furthermore, we resolved the crystal structure of pCP312R to 2.3 Å resolution and found that pCP312R has the potential to bind nucleic acids. LC-MS analysis and co-immunoprecipitation assay revealed that pCP312R interacts with RPS27A, a component of the 40S ribosomal subunit. Confocal microscopy showed the interaction between pCP312R and RPS27A leaded to a modification in the subcellular localization of this host protein, which suppresses host protein translation. Renilla-Glo luciferase assay and Ribopuromycylation analysis evidenced that knockout of RPS27A completely aborted the shutoff activity of pCP312R, and trans-complementation of RPS27A recovered pCP312R shutoff activity in RPS27A-knockout cells. Our findings shed light on the function of ASFV CP312R gene in virus infection, which triggers inhibition of host protein synthesis.

Potyviral Helper-Component Protease: Multifaced Functions and Interactions with Host Proteins.

The best-characterized functional motifs of the potyviral Helper-Component protease (HC-Pro) responding for aphid transmission, RNA silencing suppression, movement, symptom development, and replication are gathered in this review. The potential cellular protein targets of plant virus proteases remain largely unknown despite their multifunctionality. The HC-Pro catalytic domain, as a cysteine protease, autoproteolytically cleaves the potyviral polyproteins in the sequence motif YXVG/G and is not expected to act on host targets; however, 146 plant proteins in the Viridiplantae clade containing this motif were searched in the UniProtKB database and are discussed. On the other hand, more than 20 interactions within the entire HC-Pro structure are known. Most of these interactions with host targets (such as the 20S proteasome, methyltransferase, transcription factor eIF4E, and microtubule-associated protein HIP2) modulate the cellular environments for the benefit of virus accumulation or contribute to symptom severity (interactions with MinD, Rubisco, ferredoxin) or participate in the suppression of RNA silencing (host protein VARICOSE, calmodulin-like protein). On the contrary, the interaction of HC-Pro with triacylglycerol lipase, calreticulin, and violaxanthin deepoxidase seems to be beneficial for the host plant. The strength of these interactions between HC-Pro and the corresponding host protein vary with the plant species. Therefore, these interactions may explain the species-specific sensitivity to potyviruses.

Spatiotemporal binding of cyclophilin A and CPSF6 to capsid regulates HIV-1 nuclear entry and integration.

Human immunodeficiency virus type 1 (HIV-1) capsid, which is the target of the antiviral lenacapavir, protects the viral genome and binds multiple host proteins to influence intracellular trafficking, nuclear import, and integration. Previously, we showed that capsid binding to cleavage and polyadenylation specificity factor 6 (CPSF6) in the cytoplasm is competitively inhibited by cyclophilin A (CypA) binding and regulates capsid trafficking, nuclear import, and infection. Here we determined that a capsid mutant with increased CypA binding affinity had significantly reduced nuclear entry and mislocalized integration. However, disruption of CypA binding to the mutant capsid restored nuclear entry, integration, and infection in a CPSF6-dependent manner. Furthermore, relocalization of CypA expression from the cell cytoplasm to the nucleus failed to restore mutant HIV-1 infection. Our results clarify that sequential binding of CypA and CPSF6 to HIV-1 capsid is required for optimal nuclear entry and integration targeting, informing antiretroviral therapies that contain lenacapavir.

Porcine alveolar macrophages host proteins interacting with African swine fever virus p72.

Introduction: African swine fever virus (ASFV) is a highly contagious virus that spreads rapidly and has a mortality rate of up to 100% in domestic pigs, leading to significant economic losses in the pig industry. The major capsid protein p72 of ASFV plays a critical role in viral invasion and immune evasion. Methods: In this study, we used yeast two-hybrid screening to identify host proteins interacting with p72 in porcine alveolar macrophages (PAMs) and verified these proteins using confocal microscopy and immunoprecipitation techniques. Results and Discussion: We validated 13 proteins that interact with p72, including CD63, B2M, YTHDF2, FTH1, SHFL, CDK5RAP3, VIM, PELO, TIMP2, PHYH, C1QC, CMAS, and ERCC1. Enrichment analysis and protein-protein interaction network analysis of these interacting proteins revealed their involvement in virus attachment, invasion, replication, assembly, and immune regulation. These findings provide new insights into the function of p72 and valuable information for future research on the interaction between ASFV and host proteins.

Clinical usefulness of a host signature based on TRAIL, IP10, and CRP (MeMed BV) as infection biomarkers in intensive care units' patients. A retrospective observational study.

INTRODUCTION: Infection complications are common in intensive care unit patients, and early detection remains a diagnostic challenge. Procalcitonin (PCT) and C-reactive protein (CRP) are commonly used biomarkers. A novel diagnostic approach focuses on the host immune response. One of the approaches, the MMBV index, is based on measuring in a blood sample three parameters: (i) tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), (ii) interferon-γ-induced protein-10 (IP10), and (iii) CRP. This study aimed to evaluate the usefulness of MMBV as an infection biomarker in an ICU cohort. PATIENTS AND METHODS: Forty-six patients treated in the University Clinical Center in Gdansk ICU were enrolled in the study, and their clinical data were retrospectively analyzed. In total, 91 MMBV results were analyzed. RESULTS: Most of the patients had high MMBV values, suggesting bacterial etiology. A weak correlation between PCT and MMBV was observed, and no correlation between parameter changes was noted. There was a correlation between CRP/MMBV and between changes in CRP / changes in MMBV. CONCLUSION: It seems that MMBV is not valuable for ICU patients neither in diagnosing nor monitoring infection. Higher MMBV values may predict unfavorable treatment outcomes.

RVvictor: Virus RNA-directed molecular interactions for RNA virus infection.

RNA viruses are major human pathogens that cause seasonal epidemics and occasional pandemic outbreaks. Due to the nature of their RNA genomes, it is anticipated that virus's RNA interacts with host protein (INTPRO), messenger RNA (INTmRNA), and non-coding RNA (INTncRNA) to perform their particular functions during their transcription and replication. In other words, thus, it is urgently needed to have such valuable data on virus RNA-directed molecular interactions (especially INTPROs), which are highly anticipated to attract broad research interests in the fields of RNA virus translation and replication. In this study, a new database was constructed to describe the virus RNA-directed interaction (INTPRO, INTmRNA, INTncRNA) for RNA virus (RVvictor). This database is unique in a) unambiguously characterizing the interactions between viruses RNAs and host proteins, b) providing, for the first time, the most systematic RNA-directed interaction data resources in providing clues to understand the molecular mechanisms of RNA viruses' translation, and replication, and c) in RVvictor, comprehensive enrichment analysis is conducted for each virus RNA based on its associated target genes/proteins, and the enrichment results were explicitly illustrated using various graphs. We found significant enrichment of a suite of pathways related to infection, translation, and replication, e.g., HIV infection, coronavirus disease, regulation of viral genome replication, and so on. Due to the devastating and persistent threat posed by the RNA virus, RVvictor constructed, for the first time, a possible network of cross-talk in RNA-directed interaction, which may ultimately explain the pathogenicity of RNA virus infection. The knowledge base might help develop new anti-viral therapeutic targets in the future. It's now free and publicly accessible at: https://idrblab.org/rvvictor/.

Machine Learning Methods for Virus-Host Protein-Protein Interaction Prediction.

The attachment of a virion to a respective cellular receptor on the host organism occurring through the virus-host protein-protein interactions (PPIs) is a decisive step for viral pathogenicity and infectivity. Therefore, a vast number of wet-lab experimental techniques are used to study virus-host PPIs. Taking the great number and enormous variety of virus-host PPIs and the cost as well as labor of laboratory work, however, computational approaches toward analyzing the available interaction data and predicting previously unidentified interactions have been on the rise. Among them, machine-learning-based models are getting increasingly more attention with a great body of resources and tools proposed recently.In this chapter, we first provide the methodology with major steps toward the development of a virus-host PPI prediction tool. Next, we discuss the challenges involved and evaluate several existing machine-learning-based virus-host PPI prediction tools. Finally, we describe our experience with several ensemble techniques as utilized on available prediction results retrieved from individual PPI prediction tools. Overall, based on our experience, we recognize there is still room for the development of new individual and/or ensemble virus-host PPI prediction tools that leverage existing tools.

High-sensitivity profiling of SARS-CoV-2 noncoding region-host protein interactome reveals the potential regulatory role of negative-sense viral RNA.

A deep understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-host interactions is crucial to developing effective therapeutics and addressing the threat of emerging coronaviruses. The role of noncoding regions of viral RNA (ncrRNAs) has yet to be systematically scrutinized. We developed a method using MS2 affinity purification coupled with liquid chromatography-mass spectrometry and designed a diverse set of bait ncrRNAs to systematically map the interactome of SARS-CoV-2 ncrRNA in Calu-3, Huh7, and HEK293T cells. Integration of the results defined the core ncrRNA-host protein interactomes among cell lines. The 5' UTR interactome is enriched with proteins in the small nuclear ribonucleoproteins family and is a target for the regulation of viral replication and transcription. The 3' UTR interactome is enriched with proteins involved in the stress granules and heterogeneous nuclear ribonucleoproteins family. Intriguingly, compared with the positive-sense ncrRNAs, the negative-sense ncrRNAs, especially the negative-sense of 3' UTR, interacted with a large array of host proteins across all cell lines. These proteins are involved in the regulation of the viral production process, host cell apoptosis, and immune response. Taken together, our study depicts the comprehensive landscape of the SARS-CoV-2 ncrRNA-host protein interactome and unveils the potential regulatory role of the negative-sense ncrRNAs, providing a new perspective on virus-host interactions and the design of future therapeutics. Given the highly conserved nature of UTRs in positive-strand viruses, the regulatory role of negative-sense ncrRNAs should not be exclusive to SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic affecting millions of lives. During replication and transcription, noncoding regions of the viral RNA (ncrRNAs) may play an important role in the virus-host interactions. Understanding which and how these ncrRNAs interact with host proteins is crucial for understanding the mechanism of SARS-CoV-2 pathogenesis. We developed the MS2 affinity purification coupled with liquid chromatography-mass spectrometry method and designed a diverse set of ncrRNAs to identify the SARS-CoV-2 ncrRNA interactome comprehensively in different cell lines and found that the 5' UTR binds to proteins involved in U1 small nuclear ribonucleoprotein, while the 3' UTR interacts with proteins involved in stress granules and the heterogeneous nuclear ribonucleoprotein family. Interestingly, negative-sense ncrRNAs showed interactions with a large number of diverse host proteins, indicating a crucial role in infection. The results demonstrate that ncrRNAs could serve diverse regulatory functions.

Monkeypox virus: phylogenomics, host-pathogen interactome and mutational cascade.

While the world is still recovering from the Covid-19 pandemic, monkeypox virus (MPXV) awaits to cause another global outbreak as a challenge to all of mankind. However, the Covid-19 pandemic has taught us a lesson to speed up the pace of viral genomic research for the implementation of preventive and treatment strategies. One of the important aspects of MPXV that needs immediate insight is its evolutionary lineage based on genomic studies. Utilizing high-quality isolates from the GISAID (Global Initiative on Sharing All Influenza Data) database, primarily sourced from Europe and North America, we employed a SNP-based whole-genome phylogeny method and identified four major clusters among 628 MPXV isolates. Our findings indicate a distinct evolutionary lineage for the first MPXV isolate, and a complex epidemiology and evolution of MPXV strains across various countries. Further analysis of the host-pathogen interaction network revealed key viral proteins, such as E3, SPI-2, K7 and CrmB, that play a significant role in regulating the network and inhibiting the host's cellular innate immune system. Our structural analysis of proteins E3 and CrmB revealed potential disruption of stability due to certain mutations. While this study identified a large number of mutations within the new outbreak clade, it also reflected that we need to move fast with the genomic analysis of newly detected strains from around the world to develop better prevention and treatment methods.

PSMB4 Degrades the Porcine Reproductive and Respiratory Syndrome Virus Nsp1α Protein via the Autolysosome Pathway and Induces the Production of Type I Interferon.

Porcine reproductive and respiratory syndrome virus (PRRSV) causes respiratory disease in pigs of all ages and reproductive failure in sows, resulting in great economic losses to the swine industry. In this work, we identified the interaction between PSMB4 and PRRSV Nsp1α by yeast two-hybrid screening. The PSMB4-Nsp1α interaction was further confirmed by coimmunoprecipitation, glutathione S-transferase (GST) pulldown, and laser confocal experiments. The PCPα domain (amino acids 66 to 166) of Nsp1α and the C-terminal domain (amino acids 250 to 264) of PSMB4 were shown to be critical for the PSMB4-Nsp1α interaction. PSMB4 overexpression reduced PRRSV replication, whereas PSMB4 knockdown elicited opposing effects. Mechanistically, PSMB4 targeted K169 in Nsp1α for K63-linked ubiquitination and targeted Nsp1α for autolysosomal degradation by interacting with LC3 to enhance the activation of the lysosomal pathway. Meanwhile, we found that PSMB4 activated the NF-κB signaling pathway to produce type I interferons by downregulating the expression of IκBα and p-IκBα. In conclusion, our data revealed a new mechanism of PSMB4-mediated restriction of PRRSV replication, whereby PSMB4 was found to induce Nsp1α degradation and type I interferon expression, in order to impede the replication of PRRSV. IMPORTANCE In the swine industry, PRRSV is a continuous threat, and the current vaccines are not effective enough to block it. This study determined that PSMB4 plays an antiviral role against PRRSV. PSMB4 was found to interact with PRRSV Nsp1α, mediate K63-linked ubiquitination of Nsp1α at K169, and thus trigger its degradation via the lysosomal pathway. Additionally, PSMB4 activated the NF-κB signaling pathway to produce type I interferons by downregulating the expression of IκBα and p-IκBα. This study extends our understanding of the proteasome subunit PSMB4 against PRRSV replication and will contribute to the development of new antiviral strategies.

Molecular insight into the specific interactions of the SARS-Coronavirus-2 nucleocapsid with RNA and host protein.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) nucleocapsid protein is the most abundantly expressed viral protein during infection where it targets both RNA and host proteins. However, identifying how a single viral protein interacts with so many different targets remains a challenge, providing the impetus here for identifying the interaction sites through multiple methods. Through a combination of nuclear magnetic resonance (NMR), electron microscopy, and biochemical methods, we have characterized nucleocapsid interactions with RNA and with three host proteins, which include human cyclophilin-A, Pin1, and 14-3-3τ. Regarding RNA interactions, the nucleocapsid protein N-terminal folded domain preferentially interacts with smaller RNA fragments relative to the C-terminal region, suggesting an initial RNA engagement is largely dictated by this N-terminal region followed by weaker interactions to the C-terminal region. The nucleocapsid protein forms 10 nm ribonuclear complexes with larger RNA fragments that include 200 and 354 nucleic acids, revealing its potential diversity in sequestering different viral genomic regions during viral packaging. Regarding host protein interactions, while the nucleocapsid targets all three host proteins through its serine-arginine-rich region, unstructured termini of the nucleocapsid protein also engage host cyclophilin-A and host 14-3-3τ. Considering these host proteins play roles in innate immunity, the SARS-CoV-2 nucleocapsid protein may block the host response by competing interactions. Finally, phosphorylation of the nucleocapsid protein quenches an inherent dynamic exchange process within its serine-arginine-rich region. Our studies identify many of the diverse interactions that may be important for SARS-CoV-2 pathology during infection.

Host Desmin Interacts with RABV Matrix Protein and Facilitates Virus Propagation.

Microfilaments and microtubules, two crucial structures of cytoskeletal networks, are usurped by various viruses for their entry, egress, and/or intracellular trafficking, including the Rabies virus (RABV). Intermediate filaments (IFs) are the third major component of cytoskeletal filaments; however, little is known about the role of IFs during the RABV infection. Here, we identified the IF protein desmin as a novel host interactor with the RABV matrix protein, and we show that this physical interaction has a functional impact on the virus lifecycle. We found that the overexpression of desmin facilitates the RABV infection by increasing the progeny virus yield, and the suppression of endogenous desmin inhibits virus replication. Furthermore, we used confocal microscopy to observe that the RABV-M co-localizes with desmin in IF bundles in the BHK-21 cells. Lastly, we found that mice challenged with RABV displayed an enhanced expression of desmin in the brains of infected animals. These findings reveal a desmin/RABV-M interaction that positively regulates the virus infection and suggests that the RABV may utilize cellular IFs as tracks for the intracellular transport of viral components and efficient budding.

Identification of SARS-CoV-2 Main Protease (Mpro) Cleavage Sites Using Two-Dimensional Electrophoresis and In Silico Cleavage Site Prediction.

The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays a crucial role in its life cycle. The Mpro-mediated limited proteolysis of the viral polyproteins is necessary for the replication of the virus, and cleavage of the host proteins of the infected cells may also contribute to viral pathogenesis, such as evading the immune responses or triggering cell toxicity. Therefore, the identification of host substrates of the viral protease is of special interest. To identify cleavage sites in cellular substrates of SARS-CoV-2 Mpro, we determined changes in the HEK293T cellular proteome upon expression of the Mpro using two-dimensional gel electrophoresis. The candidate cellular substrates of Mpro were identified by mass spectrometry, and then potential cleavage sites were predicted in silico using NetCorona 1.0 and 3CLP web servers. The existence of the predicted cleavage sites was investigated by in vitro cleavage reactions using recombinant protein substrates containing the candidate target sequences, followed by the determination of cleavage positions using mass spectrometry. Unknown and previously described SARS-CoV-2 Mpro cleavage sites and cellular substrates were also identified. Identification of target sequences is important to understand the specificity of the enzyme, as well as aiding the improvement and development of computational methods for cleavage site prediction.

Association of viral load with TRAIL, IP-10, CRP biomarker signature and disease severity in children with respiratory tract infection or fever without source: A prospective, multicentre cohort study.

BACKGROUND: To investigate the association of viral load (VL) with (i) tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), interferon gamma-induced protein-10, C-reactive protein, and a combinatorial score (BV score), and (ii) clinical severity. STUDY DESIGN: In this prospective, multicentre cohort substudy, children with respiratory tract infection or fever without source were enrolled. VL for influenza virus, rhinovirus, respiratory syncytial virus, and adenovirus was measured from nasopharyngeal swabs. The reference standard diagnosis was established based on expert panel adjudication. RESULTS: Of 1140 recruited patients, 333 had a virus monodetection. VL for the aggregated data set correlated with TRAIL and IP-10 levels, with the length of oxygen therapy, and inversely with the BV score. At a single viral level, only the influenza VL yielded a correlation with TRAIL, IP-10 levels, and the BV score. Children with a viral reference standard diagnosis had significantly higher VL than those with bacterial infection (p = 0.0005). Low TRAIL (incidence rate ratio [IRR] 0.6, 95% confidence interval [CI] 0.39-0.91) and young age (IRR 0.62, 95% CI 0.49-0.79) were associated with a longer hospital stay, while young age (IRR 0.33, 95% CI 0.18-0.61), low TRAIL (IRR 0.25, 95% CI 0.08-0.76), and high VL (IRR 1.16, 95% CI 1.00-1.33) were predictive of longer oxygen therapy. CONCLUSION: These findings indicate that VL correlates with biomarkers and may serve as a complementary tool pertaining to disease severity.

MP-VHPPI: Meta predictor for viral host protein-protein interaction prediction in multiple hosts and viruses.

Viral-host protein-protein interaction (VHPPI) prediction is essential to decoding molecular mechanisms of viral pathogens and host immunity processes that eventually help to control the propagation of viral diseases and to design optimized therapeutics. Multiple AI-based predictors have been developed to predict diverse VHPPIs across a wide range of viruses and hosts, however, these predictors produce better performance only for specific types of hosts and viruses. The prime objective of this research is to develop a robust meta predictor (MP-VHPPI) capable of more accurately predicting VHPPI across multiple hosts and viruses. The proposed meta predictor makes use of two well-known encoding methods Amphiphilic Pseudo-Amino Acid Composition (APAAC) and Quasi-sequence (QS) Order that capture amino acids sequence order and distributional information to most effectively generate the numerical representation of complete viral-host raw protein sequences. Feature agglomeration method is utilized to transform the original feature space into a more informative feature space. Random forest (RF) and Extra tree (ET) classifiers are trained on optimized feature space of both APAAC and QS order separate encoders and by combining both encodings. Further predictions of both classifiers are utilized to feed the Support Vector Machine (SVM) classifier that makes final predictions. The proposed meta predictor is evaluated over 7 different benchmark datasets, where it outperforms existing VHPPI predictors with an average performance of 3.07, 6.07, 2.95, and 2.85% in terms of accuracy, Mathews correlation coefficient, precision, and sensitivity, respectively. To facilitate the scientific community, the MP-VHPPI web server is available at https://sds_genetic_analysis.opendfki.de/MP-VHPPI/.

Corrigendum: Advancement in the development of therapeutics against Zika virus infection.

[This corrects the article DOI: 10.3389/fcimb.2022.946957.].

Molecular insights on bioactive compounds againstCovid-19: A Network pharmacological and computational study.

BACKGROUND: Network pharmacology based identification of phytochemicals in the form of cocktails against off-targets can play a significant role in inhibition of SARS_CoV2 viral entry and its propagation. This study includes network pharmacology, virtual screening, docking and molecular dynamics to investigate the distinct antiviral mechanisms of effective phytochemicals against SARS_CoV2. METHODS: SARS_CoV2 human-protein interaction network was explored from the BioGRID database and analysed using Cytoscape. Further analysis was performed to explore biological function, protein-phytochemical/drugs network and up-down regulation of pathological host target proteins. This lead to understand the antiviral mechanism of phytochemicals against SARS_CoV2. The network was explored through g:Profiler, EnrichR, CTD, SwissTarget, STITCH, DrugBank, BindingDB, STRING and SuperPred. Virtual screening of phytochemicals against potential antiviral targets such as M-Pro, NSP1, Receptor binding domain, RNA binding domain, and ACE2 discloses the effective interaction between them. Further, the binding energy calculations through simulation of the docked complex explains the efficiency and stability of the interactions. RESULTS: The network analysis identified quercetin, genistein, luteolin, eugenol, berberine, isorhamnetin and cinnamaldehyde to be interacting with host proteins ACE2, DPP4, COMT, TUBGCP3, CENPF, BRD2 and HMOX1 which are involved in antiviral mechanisms such as viral entry, viral replication, host immune response, and antioxidant activity. Thus indicating that herbal cocktails can effectively tackle the viral hijacking of the crucial biological functions of human host. Further exploration through Virtual screening, docking and molecular dynamics recognizes the effective interaction of phytochemicals such as punicalagin, scutellarin, and solamargine with their respective potential targets. CONCLUSION: This work illustrates probable strategy for identification of phytochemical based cocktails and off-targets which are effective against SARS_CoV 2.

The Landscape of Virus-Host Protein-Protein Interaction Databases.

Knowledge of virus-host interactomes has advanced exponentially in the last decade by the use of high-throughput screening technologies to obtain a more comprehensive landscape of virus-host protein-protein interactions. In this article, we present a systematic review of the available virus-host protein-protein interaction database resources. The resources covered in this review are both generic virus-host protein-protein interaction databases and databases of protein-protein interactions for a specific virus or for those viruses that infect a particular host. The databases are reviewed on the basis of the specificity for a particular virus or host, the number of virus-host protein-protein interactions included, and the functionality in terms of browse, search, visualization, and download. Further, we also analyze the overlap of the databases, that is, the number of virus-host protein-protein interactions shared by the various databases, as well as the structure of the virus-host protein-protein interaction network, across viruses and hosts.

Seneca Valley Virus 3C pro Cleaves Heterogeneous Nuclear Ribonucleoprotein K to Facilitate Viral Replication.

Seneca Valley virus (SVV) has emerged as an important pathogen that is associated with idiopathic vesicular infection in pigs, causing a potential threat to the global swine industry. The heterogeneous nuclear ribonucleoprotein K (hnRNP K) that shuttles between the nucleus and cytoplasm plays an important role in viral infection. In this study, we observed that infection with SVV induced cleavage, degradation, and cytoplasmic redistribution of hnRNP K in cultured cells, which was dependent on the activity of viral 3Cpro protease. Also, the 3Cpro induced degradation of hnRNP K via the caspase pathway. Further studies demonstrated that SVV 3Cpro cleaved hnRNP K at residue Q364, and the expression of the cleavage fragment hnRNP K (aa.365-464) facilitates viral replication, which is similar to full-length hnRNP K, whereas hnRNP K (aa.1-364) inhibits viral replication. Additionally, hnRNP K interacts with the viral 5' untranslated region (UTR), and small interfering RNA (siRNA)-mediated knockdown of hnRNP K results in significant inhibition of SVV replication. Overall, our results demonstrated that the hnRNP K positively regulates SVV replication in a protease activity-dependent fashion in which the cleaved C-terminal contributes crucially to the upregulation of SVV replication. This finding of the role of hnRNP K in promoting SVV propagation provides a novel antiviral strategy to utilize hnRNP K as a potential target for therapy.

Advancement in the Development of Therapeutics Against Zika Virus Infection.

Zika virus (ZIKV), a re-emerging arbovirus, causes teratogenic effects on the fetus and normal nerve functions, resulting in harmful autoimmune responses, which call for the development of therapeutics against ZIKV infection. In this review, we introduce the pathogenesis of ZIKV infection and summarize the advancement in the development of therapeutics against ZIKV infection. It provides guidance for the development of effective therapeutics against ZIKV infection.