Polyprotein 1ab Research Articles

Classification, replication, and transcription of Nidovirales.

Nidovirales is one order of RNA virus, with the largest single-stranded positive sense RNA genome enwrapped with membrane envelope. It comprises four families (Arterividae, Mesoniviridae, Roniviridae, and Coronaviridae) and has been circulating in humans and animals for almost one century, posing great threat to livestock and poultry，as well as to public health. Nidovirales shares similar life cycle: attachment to cell surface, entry, primary translation of replicases, viral RNA replication in cytoplasm, translation of viral proteins, virion assembly, budding, and release. The viral RNA synthesis is the critical step during infection, including genomic RNA (gRNA) replication and subgenomic mRNAs (sg mRNAs) transcription. gRNA replication requires the synthesis of a negative sense full-length RNA intermediate, while the sg mRNAs transcription involves the synthesis of a nested set of negative sense subgenomic intermediates by a discontinuous strategy. This RNA synthesis process is mediated by the viral replication/transcription complex (RTC), which consists of several enzymatic replicases derived from the polyprotein 1a and polyprotein 1ab and several cellular proteins. These replicases and host factors represent the optimal potential therapeutic targets. Hereby, we summarize the Nidovirales classification, associated diseases, "replication organelle," replication and transcription mechanisms, as well as related regulatory factors.

Regression Algorithms in Predicting the SARS-CoV-2 Replicase Polyprotein 1ab Inhibitor: A Comparative Study

Due to its extensive steps and trials, drug discovery is a long and expensive process. In the last decade, as also hard pressed by the COVID-19 pandemic, the screening process could be assisted with the advancement in computational technology including the application of Machine Learning. The classification task in Machine Learning has become one of the major approaches for drug discovery. Unfortunately, this practice uses discretized labels that might lead to the loss of quantitative properties that could be meaningful. Therefore, in this paper, we aim to compare various Machine Learning regression algorithms in predicting inhibitory bioactivity, specifically the IC50 value, with the SARS-CoV-2 Replicase Polyprotein 1ab as the target. With 1,138 non-duplicated data downloaded from the ChEMBL database that was engineered into four dataset variances, 42 regression algorithms were utilized for the prediction. We found that there are computational challenges to the use of regression algorithms in predicting bioactivity, for only a handful and a specific dataset variance that returned valid performance parameters upon testing. The three that yielded the highest counts of valid performance parameters are the Histogram Gradient Boosting Regressor (HGBR), Light Gradient Boosting Machine Regressor (LGBR), and Random Forest Regression (RFR). Further statistical analyses show that there is no significant difference between these three algorithms, except for the time taken for training and testing the model, where the LGBR excels. Therefore, these three algorithms should be primarily considered for the study with the same nature.

A Machine Learning Approach to Identify Potential miRNA-Gene Regulatory Network Contributing to the Pathogenesis of SARS-CoV-2 Infection.

Worldwide, many lives have been lost in the recent outbreak of coronavirus disease. The pathogen responsible for this disease takes advantage of the host machinery to replicate itself and, in turn, causes pathogenesis in humans. Human miRNAs are seen to have a major role in the pathogenesis and progression of viral diseases. Hence, an in-silico approach has been used in this study to uncover the role of miRNAs and their target genes in coronavirus disease pathogenesis. This study attempts to perform the miRNA seq data analysis to identify the potential differentially expressed miRNAs. Considering only the experimentally proven interaction databases TarBase, miRTarBase, and miRecords, the target genes of the miRNAs have been identified from the mirNET analytics platform. The identified hub genes were subjected to gene ontology and pathway enrichment analysis using EnrichR. It is found that a total of 9 miRNAs are deregulated, out of which 2 were upregulated (hsa-mir-3614-5p and hsa-mir-3614-3p) and 7 were downregulated (hsa-mir-17-5p, hsa-mir-106a-5p, hsa-mir-17-3p, hsa-mir-181d-5p, hsa-mir-93-3p, hsa-mir-28-5p, and hsa-mir-100-5p). These miRNAs help us to classify the diseased and healthy control patients accurately. Moreover, it is also found that crucial target genes (UBC and UBB) of 4 signature miRNAs interact with viral replicase polyprotein 1ab of SARS-Coronavirus. As a result, it is noted that the virus hijacks key immune pathways like various cancer and virus infection pathways and molecular functions such as ubiquitin ligase binding and transcription corepressor and coregulator binding.

A Mouse-Adapted Model of HCoV-OC43 and Its Usage to the Evaluation of Antiviral Drugs.

The human coronavirus OC43 (HCoV-OC43) is one of the most common causes of common cold but can lead to fatal pneumonia in children and elderly. However, the available animal models of HCoV-OC43 did not show respiratory symptoms that are insufficient to assist in screening antiviral agents for respiratory diseases. In this study, we adapted the HCoV-OC43 VR-1558 strain by serial passage in suckling C57BL/6 mice and the resulting mouse-adapted virus at passage 9 (P9) contained 8 coding mutations in polyprotein 1ab, spike (S) protein, and nucleocapsid (N) protein. Pups infected with the P9 virus significantly lost body weight and died within 5 dpi. In cerebral and pulmonary tissues, the P9 virus replication induced the production of G-CSF, IFN-γ, IL-6, CXCL1, MCP-1, MIP-1α, RANTES, IP-10, MIP-1β, and TNF-α, as well as pathological alterations including reduction of neuronal cells and typical symptoms of viral pneumonia. We found that the treatment of arbidol hydrochloride (ARB) or Qingwenjiere Mixture (QJM) efficiently improved the symptoms and decreased n gene expression, inflammatory response, and pathological changes. Furthermore, treating with QJM or ARB raised the P9-infected mice’s survival rate within a 15 day observation period. These findings suggested that the new mouse-adapted HCoV-OC43 model is applicable and reproducible for antiviral studies of HCoV-OC43.

Thermodynamic analysis of SL1 1x2 internal loop in SARS‐CoV‐2

SARS‐CoV‐2 utilizes a positive‐sense single stranded RNA as its genomic material. This single stranded mRNA hijacks the host cell’s ribosome to translate its own proteins. Upon infection of a host cell, SARS‐CoV‐2 produces polyprotein 1ab which is then cleaved into 16 non‐structural proteins. Non‐structural protein 1 (Nsp1) inhibits host cell translation by binding to the 40S ribosomal subunit. Stem loop 1(SL1) in the 5’‐UTR of the mRNA mediates the binding of Nsp1 to the ribosome. SARS‐CoV‐2 specifically contains a 1x2 internal loop within the SL1 that is not seen in other coronaviruses. In this study, we are examining the thermodynamic properties of the 1x2 internal loop of SL1. UV‐visible thermal melts and isothermal titration calorimetry (ITC) were performed on various DNA and RNA constructs containing the 1x2 internal loop in SL1 in the presence of 1 M KCl or 10 mM magnesium chloride at two different pHs. Initial results show additional base pairing at lower pH in 1 M KCl buffer, indicating the formation of an A+•C base pair.

Molecular Docking Studies of Natural Polyphenolic Compounds with COVID19 Viral Proteins Responsible for Antibiotic Resistance in Viral Pathogens to Prevent Virus Assembly: In Silico Computational Study

In order to distinguish possible hits that can inhibit the COVID-19 effects, virtual screening of natural polyphenols (PPs) was carried out by molecular docking (MD) and simulations in silico ADMET and drug like forecasts. Considering the medical relevance literature released, 4 phytochemicals (PC’s) have been chosen with analogous PPs to scan the possible inhibitors for the replicase polyprotein 1ab therapeutic protein targets. The experiments in silico computing showed the efficacy of PPs such as ellagitana against the COVID-19 target proteins.The protein-ligand interaction analysis found that the proteins in the target proteins associate these PC’s with the amino acid residues. The central structure of these possible hits can then be used to further optimise COVID-19 drug design. Also, medicinal plants that contain these PCs can be used to produce appropriate therapeutic approaches for conventional therapies like Strawberry (Fragaria x ananassa), Kiwi fruit (Actinidia chinensis), Litchi (Litchi chinensis) and Durian fruit (Durio zibethinus).

Semi-Supervised Pipeline for Autonomous Annotation of SARS-CoV-2 Genomes.

SARS-CoV-2 genomic sequencing efforts have scaled dramatically to address the current global pandemic and aid public health. However, autonomous genome annotation of SARS-CoV-2 genes, proteins, and domains is not readily accomplished by existing methods and results in missing or incorrect sequences. To overcome this limitation, we developed a novel semi-supervised pipeline for automated gene, protein, and functional domain annotation of SARS-CoV-2 genomes that differentiates itself by not relying on the use of a single reference genome and by overcoming atypical genomic traits that challenge traditional bioinformatic methods. We analyzed an initial corpus of 66,000 SARS-CoV-2 genome sequences collected from labs across the world using our method and identified the comprehensive set of known proteins with 98.5% set membership accuracy and 99.1% accuracy in length prediction, compared to proteome references, including Replicase polyprotein 1ab (with its transcriptional slippage site). Compared to other published tools, such as Prokka (base) and VAPiD, we yielded a 6.4- and 1.8-fold increase in protein annotations. Our method generated 13,000,000 gene, protein, and domain sequences—some conserved across time and geography and others representing emerging variants. We observed 3362 non-redundant sequences per protein on average within this corpus and described key D614G and N501Y variants spatiotemporally in the initial genome corpus. For spike glycoprotein domains, we achieved greater than 97.9% sequence identity to references and characterized receptor binding domain variants. We further demonstrated the robustness and extensibility of our method on an additional 4000 variant diverse genomes containing all named variants of concern and interest as of August 2021. In this cohort, we successfully identified all keystone spike glycoprotein mutations in our predicted protein sequences with greater than 99% accuracy as well as demonstrating high accuracy of the protein and domain annotations. This work comprehensively presents the molecular targets to refine biomedical interventions for SARS-CoV-2 with a scalable, high-accuracy method to analyze newly sequenced infections as they arise.

Natural Polyphenols Inhibit the Dimerization of the SARS-CoV-2 Main Protease: The Case of Fortunellin and Its Structural Analogs.

3CL-Pro is the SARS-CoV-2 main protease (MPro). It acts as a homodimer to cleave the large polyprotein 1ab transcript into proteins that are necessary for viral growth and replication. 3CL-Pro has been one of the most studied SARS-CoV-2 proteins and a main target of therapeutics. A number of drug candidates have been reported, including natural products. Here, we employ elaborate computational methods to explore the dimerization of the 3CL-Pro protein, and we formulate a computational context to identify potential inhibitors of this process. We report that fortunellin (acacetin 7-O-neohesperidoside), a natural flavonoid O-glycoside, and its structural analogs are potent inhibitors of 3CL-Pro dimerization, inhibiting viral plaque formation in vitro. We thus propose a novel basis for the search of pharmaceuticals as well as dietary supplements in the fight against SARS-CoV-2 and COVID-19.

Genome-wide comparison of coronaviruses derived from veterinary animals: A canine and feline perspective

Feline- and canine-derived coronaviruses (FCoVs and CCoVs) are widespread among dog and cat populations. This study was to understand the route of disease origin and viral transmission in veterinary animals and in human through comparative pan-genomic analysis of coronavirus sequences, especially retrieved from genomes of FCoV and CCoV. Average nucleotide identity based on complete genomes might clustered CoV strains according to their infected host, with an exception of type II of CCoV (accession number KC175339) that was clustered closely to virulent FCoVs. In contrast, the hierarchical clustering based on gene repertories retrieved from pan-genome analysis might divided the examined coronaviruses into host-independent clusters, and formed obviously the cluster of Alphacoronaviruses into sub-clusters of feline–canine, only feline, feline–canine–human coronavirus. Also, functional analysis of genomic subsets might help to divide FCoV and CCoV pan-genomes into (i) clusters of core genes encoding spike, membrane, nucleocapsid proteins, and ORF1ab polyprotein; (ii) clusters of core-like genes encoding nonstructural proteins; (iii) clusters of accessory genes encoding the ORF1A; and (iv) two singleton genes encoding nonstructural protein and polyprotein 1ab. Seven clusters of gene repertories were categorized as common to the FCoV and/or CCoV genomes including pantropic and high virulent strains, illustrating that distinct core-like genes/accessory genes concerning to their pathogenicity should be exploited in further biotype analysis of new isolate. In conclusion, the phylogenomic analyses have allowed the identification of trends in the viral genomic data, especially in developing a specific control measures against coronavirus disease, such as the selection of good markers for differentiating new species from common and/or pantropic isolates.

Coronavirus replication–transcription complex: Vital and selective NMPylation of a conserved site in nsp9 by the NiRAN-RdRp subunit

RNA-dependent RNA polymerases (RdRps) of the Nidovirales (Coronaviridae, Arteriviridae, and 12 other families) are linked to an amino-terminal (N-terminal) domain, called NiRAN, in a nonstructural protein (nsp) that is released from polyprotein 1ab by the viral main protease (Mpro). Previously, self-GMPylation/UMPylation activities were reported for an arterivirus NiRAN-RdRp nsp and suggested to generate a transient state primed for transferring nucleoside monophosphate (NMP) to (currently unknown) viral and/or cellular biopolymers. Here, we show that the coronavirus (human coronavirus [HCoV]-229E and severe acute respiratory syndrome coronavirus 2) nsp12 (NiRAN-RdRp) has Mn2+-dependent NMPylation activity that catalyzes the transfer of a single NMP to the cognate nsp9 by forming a phosphoramidate bond with the primary amine at the nsp9 N terminus (N3825) following Mpro-mediated proteolytic release of nsp9 from N-terminally flanking nsps. Uridine triphosphate was the preferred nucleotide in this reaction, but also adenosine triphosphate, guanosine triphosphate, and cytidine triphosphate were suitable cosubstrates. Mutational studies using recombinant coronavirus nsp9 and nsp12 proteins and genetically engineered HCoV-229E mutants identified residues essential for NiRAN-mediated nsp9 NMPylation and virus replication in cell culture. The data corroborate predictions on NiRAN active-site residues and establish an essential role for the nsp9 N3826 residue in both nsp9 NMPylation in vitro and virus replication. This residue is part of a conserved N-terminal NNE tripeptide sequence and shown to be the only invariant residue in nsp9 and its homologs in viruses of the family Coronaviridae The study provides a solid basis for functional studies of other nidovirus NMPylation activities and suggests a possible target for antiviral drug development.

Structural phylogenetic analysis reveals lineage-specific RNA repetitive structural motifs in all coronaviruses and associated variations in SARS-CoV-2.

In many single-stranded (ss) RNA viruses, the cis-acting packaging signal that confers selectivity genome packaging usually encompasses short structured RNA repeats. These structural units, termed repetitive structural motifs (RSMs), potentially mediate capsid assembly by specific RNA–protein interactions. However, general knowledge of the conservation and/or the diversity of RSMs in the positive-sense ssRNA coronaviruses (CoVs) is limited. By performing structural phylogenetic analysis, we identified a variety of RSMs in nearly all CoV genomic RNAs, which are exclusively located in the 5′-untranslated regions (UTRs) and/or in the inter-domain regions of poly-protein 1ab coding sequences in a lineage-specific manner. In all alpha- and beta-CoVs, except for Embecovirus spp, two to four copies of 5′-gUUYCGUc-3′ RSMs displaying conserved hexa-loop sequences were generally identified in Stem-loop 5 (SL5) located in the 5′-UTRs of genomic RNAs. In Embecovirus spp., however, two to eight copies of 5′-agc-3′/guAAu RSMs were found in the coding regions of non-structural protein (NSP) 3 and/or NSP15 in open reading frame (ORF) 1ab. In gamma- and delta-CoVs, other types of RSMs were found in several clustered structural elements in 5′-UTRs and/or ORF1ab. The identification of RSM-encompassing structural elements in all CoVs suggests that these RNA elements play fundamental roles in the life cycle of CoVs. In the recently emerged SARS-CoV-2, beta-CoV-specific RSMs are also found in its SL5, displaying two copies of 5′-gUUUCGUc-3′ motifs. However, multiple sequence alignment reveals that the majority of SARS-CoV-2 possesses a variant RSM harboring SL5b C241U, and intriguingly, several variations in the coding sequences of viral proteins, such as Nsp12 P323L, S protein D614G, and N protein R203K-G204R, are concurrently found with such variant RSM. In conclusion, the comprehensive exploration for RSMs reveals phylogenetic insights into the RNA structural elements in CoVs as a whole and provides a new perspective on variations currently found in SARS-CoV-2.

Exploiting cheminformatic and machine learning to navigate the available chemical space of potential small molecule inhibitors of SARS-CoV-2

The current life-threatening and tenacious pandemic eruption of coronavirus disease in 2019 (COVID-19) has posed a significant global hazard concerning high mortality rate, economic meltdown, and everyday life distress. The rapid spread of COVID-19 demands countermeasures to combat this deadly virus. Currently, there are no drugs approved by the FDA to treat COVID-19. Therefore, discovering small molecule therapeutics for treating COVID-19 infection is essential. So far, only a few small molecule inhibitors are reported for coronaviruses. There is a need to expand the small chemical space of coronaviruses inhibitors by adding potent and selective scaffolds with anti-COVID activity. In this context, the huge antiviral chemical space already available can be analysed using cheminformatic and machine learning to unearth new scaffolds. We created three specific datasets called “antiviral dataset” (N = 38,428) “drug-like antiviral dataset” (N = 20,963) and “anticorona dataset” (N = 433) for this purpose. We analyzed the 433 molecules of “anticorona dataset” for their scaffold diversity, physicochemical distributions, principal component analysis, activity cliffs, R-group decomposition, and scaffold mapping. The scaffold diversity of the “anticorona dataset” in terms of Murcko scaffold analysis demonstrates a thorough representation of diverse chemical scaffolds. However, physicochemical descriptor analysis and principal component analysis demonstrated negligible drug-like features for the “anticorona dataset” molecules. The “antiviral dataset” and “drug-like antiviral dataset” showed low scaffold diversity as measured by the Gini coefficient. The hierarchical clustering of the “antiviral dataset” against the “anticorona dataset” demonstrated little molecular similarity. We generated a library of frequent fragments and polypharmacological ligands targeting various essential viral proteins such as main protease, helicase, papain-like protease, and replicase polyprotein 1ab. Further structural and chemical features of the “anticorona dataset” were compared with SARS-CoV-2 repurposed drugs, FDA-approved drugs, natural products, and drugs currently in clinical trials. Using machine learning tool DCA (DMax Chemistry Assistant), we converted the “anticorona dataset” into an elegant hypothesis with significant functional biological relevance. Machine learning analysis uncovered that FDA approved drugs, Tizanidine HCl, Cefazolin, Raltegravir, Azilsartan, Acalabrutinib, Luliconazole, Sitagliptin, Meloxicam (Mobic), Succinyl sulfathiazole, Fluconazole, and Pranlukast could be repurposed as effective drugs for COVID-19. Fragment-based scaffold analysis and R-group decomposition uncovered pyrrolidine and the indole molecular scaffolds as the potent fragments for designing and synthesizing the novel drug-like molecules for targeting SARS-CoV-2. This comprehensive and systematic assessment of small-molecule viral therapeutics' entire chemical space realised critical insights to potentially privileged scaffolds that could aid in enrichment and rapid discovery of efficacious antiviral drugs for COVID-19.

Geranii Herba as a Potential Inhibitor of SARS-CoV-2 Main 3CLpro, Spike RBD, and Regulation of Unfolded Protein Response: An In Silico Approach

Background: Since the first patient identified with SARS-CoV-2 symptoms in December 2019, the trend of a spreading coronavirus disease 2019 (COVID-19) infection has remained to date. As for now, there is an urgent need to develop novel drugs or vaccines for the SARS-CoV-2 virus. Methods: Polyphenolic compounds have potential as drug candidates for various diseases, including viral infections. In this study, polyphenolic compounds contained in Geranii Herba were chosen for an in silico approach. The SARS-CoV-2 receptor-binding domain (RBD), 3CLpro (Replicase polyprotein 1ab), and the cell surface receptor glucose-regulated protein 78 (GRP78) were chosen as target proteins. Results: Based on the molecular docking analysis, ellagic acid, gallic acid, geraniin, kaempferitrin, kaempferol, and quercetin showed significant binding interactions with the target proteins. Besides, the molecular dynamic simulation studies support Geranii Herba’s inhibition efficiency on the SARS-CoV-2 RBD. We assume that the active compounds in Geranii Herba might inhibit SARS-CoV-2 cell entry through the ACE2 receptor and inhibit the proteolytic process. Besides, these compounds may help to regulate the cell signaling under the unfolded protein response in endoplasmic reticulum stress through the binding with GRP78 and avoid the SARS-CoV-2 interaction. Conclusions: Hence, the compounds present in Geranii Herba could be used as possible drug candidates for the prevention/treatment of SARS-CoV-2 infection.

Reprofiling of approved drugs against SARS-CoV-2 main protease: an in-silico study

Given the COVID-19 pandemic, currently, there are many drugs in clinical trials against this virus. Among the excellent drug targets of SARS-CoV-2 are its proteases (Nsp3 and Nsp5) that plays vital role in polyprotein processing giving rise to functional nonstructural proteins, essential for viral replication and survival. Nsp5 (also known as Mpro) hydrolyzes replicase polyprotein (1ab) at eleven different sites. For targeting Mpro, we have employed drug repurposing approach to identify potential inhibitors of SARS-CoV-2 in a shorter time span. Screening of approved drugs through docking reveals Hyaluronic acid and Acarbose among the top hits which are showing strong interactions with catalytic site residues of Mpro. We have also performed docking of drugs Lopinavir, Ribavirin, and Azithromycin on SARS-CoV-2 Mpro. Further, binding of these compounds (Hyaluronic acid, Acarbose, and Lopinavir) is validated by extensive molecular dynamics simulation of 500 ns where these drugs show stable binding with Mpro. We believe that the high-affinity binding of these compounds will help in designing novel strategies for structure-based drug discovery against SARS-CoV-2. Communicated by Ramaswamy H. Sarma

Abstract S05-01: Profound CD8 T-cell responses towards SARS-CoV-2 OFR1ab in COVID-19 patients

Abstract While there is accumulating evidence on the antibody response against SARS-CoV-2, we are only beginning to acquire knowledge regarding the SARS-CoV-2 specific CD8 T-cell response. Therefore, it is an urgent matter to gain a deeper insight into the virus specific CD8 T-cell response to both assist vaccine design and provide tools to evaluate the vaccine-induced T-cell responses. To address this issue, we have analyzed samples from 20 COVID-19 patients for CD8 T-cell recognition of 500 predicted SARS-CoV-2-derived epitopes restricted to 10 of the most common HLA-A and HLA-B alleles. For each HLA allele, the top 50 epitopes were selected based on predicted binding affinity and likelihood of successful proteasomal processing. In addition, SARS-CoV-2 epitope predictions shared by the science community were considered. To probe for CD8 T-cell recognition of the selected epitopes, we made use of our in-house technology based on multiplexing of peptide HLA (pHLA) multimers conjugated to fluorescent dyes. Our data demonstrated that CD8 T-cell reactivity against SARS-CoV-2 was common. Remarkably, a substantial fraction of the observed CD8 T-cell responses were directed towards the ORF1ab polyprotein 1ab. These CD8 T-cell responses were frequently of a profound magnitude. In particular, a CD8 T-cell response towards a potentially immunodominant epitope (TTDPSFLGRY) restricted to the HLA-A*01:01 allele was found in all patients positive for this allele. Interestingly, the fraction of SARS-CoV-2 specific CD8 T cells expressing the inhibitory receptor NKG2A was higher as compared to bulk CD8 T cells. In conclusion, the fact that a major part of the identified SARS-CoV-2 specific CD8 T-cell response is directed against a part of the viral genome that is not included in the majority of vaccine candidates currently in development may potentially influence their clinical activity and toxicity profile. Citation Format: Anastasia Gangaev, Steven L. Ketelaars, Sanne Patiwael, Anna Dopler, Olga I. Isaeva, Kelly Hoefakker, Sara De Biasi, Cristina Mussini, Giovanni Guaraldi, Massimo Girardis, Cami M.P. Talavera Ormeno, Paul J.M. Hekking, Neubury M. Lardy, Mireille Toebes, Robert Balderas, Ton N. Schumacher, Huib Ovaa, Andrea Cossarizza, Pia Kvistborg. Profound CD8 T-cell responses towards SARS-CoV-2 OFR1ab in COVID-19 patients [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr S05-01.

An exclusive 42 amino acid signature in pp1ab protein provides insights into the evolutive history of the 2019 novel human-pathogenic coronavirus (SARS-CoV-2).

The city of Wuhan, Hubei province, China, was the origin of a severe pneumonia outbreak in December 2019, attributed to a novel coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS‐CoV‐2]), causing a total of 2761 deaths and 81109 cases (25 February 2020). SARS‐CoV‐2 belongs to genus Betacoronavirus, subgenus Sarbecovirus. The polyprotein 1ab (pp1ab) remains unstudied thoroughly since it is similar to other sarbecoviruses. In this short communication, we performed phylogenetic‐structural sequence analysis of pp1ab protein of SARS‐CoV‐2. The analysis showed that the viral pp1ab has not changed in most isolates throughout the outbreak time, but interestingly a deletion of 8 aa in the virulence factor nonstructural protein 1 was found in a virus isolated from a Japanese patient that did not display critical symptoms. While comparing pp1ab protein with other betacoronaviruses, we found a 42 amino acid signature that is only present in SARS‐CoV‐2 (AS‐SCoV2). Members from clade 2 of sarbecoviruses have traces of this signature. The AS‐SCoV2 located in the acidic‐domain of papain‐like protein of SARS‐CoV‐2 and bat‐SL‐CoV‐RatG13 guided us to suggest that the novel 2019 coronavirus probably emerged by genetic drift from bat‐SL‐CoV‐RaTG13. The implication of this amino acid signature in papain‐like protein structure arrangement and function is something worth to be explored.

Crystallization of SARS Coronavirus 3CL Protease to Identify Inhibitor Targets

The SARS coronavirus has been identified as the pathogen responsible for the 2003 outbreak of severe acute respiratory syndrome (SARS). This highly contagious virus, which most likely originated in Southern China, has since been found in over 32 countries, affecting about 8,500 people, and killed over 900 patients. Due to SARS ease of transmission through aerosols and the virus's high mortality rate (~10%), its reemergence is recognized as a looming threat to global health.However, neither a vaccine nor effective treatment exists to combat the illness in the event of another outbreak. The virus's 3 Chymotrypsin‐like main protease, is a major target for inhibitor studies, as it is crucial to viral replication through its proteolytic processing of polyprotein 1ab (pp1ab) at 11 different cleavage sites.This project worked to optimize the crystallization conditions for the SARS 3CL protease for use in X‐ray fragment based screening to identify possible inhibitors. The results of this step in the drug discovery study for the SARS‐CoV can be used as a basis for pioneering new scaffolds for inhibitor studies in other coronaviruses.Support or Funding InformationFunding from NSF DBI “REU Site: Molecular and Biochemical Analysis of Proteins” to Purdue University, Purdue College of Biochemistry, and the Purdue College of AgricultureThis abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Isolation and genetic analysis of a nidovirus from crucian carp (Carassius auratus).

A nidovirus was isolated from crucian carp (Carassius auratus). The complete genome of the crucian carp nidovirus (CCNV) is 25,971 nt long and has five open reading frames, encoding the polyprotein 1ab (pp1ab), spike glycoprotein (S), membrane protein (M), and nucleocapsid protein (N). CCNV has the highest similarity to Chinook salmon nidovirus (CSNV). However, the CCNV HB93 pp1ab protein sequence has three long fragment deletions compared with the CSNV. Phylogenetic analysis based on the complete genome sequence showed that CCNV HB93 clusters with CSNV, indicating that CCNV represents a second species in the new genus Oncotshavirus within the new family Tobaniviridae in the order Nidovirales.

Discovery of a novel nidovirus in cattle with respiratory disease.

The family Coronaviridae represents a diverse group of vertebrate RNA viruses, all with genomes greater than 26,000 nt. Here, we report the discovery and genetic characterization of a novel virus present in cattle with respiratory disease. Phylogenetic characterization of this virus revealed that it clusters within the subfamily Torovirinae, in the family Coronaviridae. The complete genome consists of only 20,261 nt and represents the smallest reported coronavirus genome. We identified seven ORFs, including the canonical nidovirus ORF1a and ORF1b. Analysis of polyprotein 1ab revealed that this virus, tentatively named bovine nidovirus (BoNV), shares the highest homology with the recently described python-borne nidoviruses and contains several conserved nidovirus motifs, but does not encode the NendoU or O-MT domains that are present in other viruses within the family Coronaviridae. In concert with its reduced genome, the atypical domain architecture indicates that this virus represents a unique lineage within the order Nidovirales.

Novel divergent nidovirus in a python with pneumonia.

The order Nidovirales contains large, enveloped viruses with a non-segmented positive-stranded RNA genome. Nidoviruses have been detected in man and various animal species, but, to date, there have been no reports of nidovirus in reptiles. In the present study, we describe the detection, characterization, phylogenetic analyses and disease association of a novel divergent nidovirus in the lung of an Indian python (Python molurus) with necrotizing pneumonia. Characterization of the partial genome (>33 000 nt) of this virus revealed several genetic features that are distinct from other nidoviruses, including a very large polyprotein 1a, a putative ribosomal frameshift signal that was identical to the frameshift signal of astroviruses and retroviruses and an accessory ORF that showed some similarity with the haemagglutinin-neuraminidase of paramyxoviruses. Analysis of genome organization and phylogenetic analysis of polyprotein 1ab suggests that this virus belongs to the subfamily Torovirinae. Results of this study provide novel insights into the genetic diversity within the order Nidovirales.