Immunoinformatics Study of SARS-CoV-2 Nucleocapsid Phosphoprotein Identifies Promising Epitopes with Mutational Implications.

The SARS-CoV-2 is rapidly evolving and new mutations are being reported from different parts of the world. In this study, we investigated the variations occurring in the nucleocapsid phosphoprotein (N-protein) of SARS-CoV-2 from India. We used several in silico prediction tools to characterise N-protein including IEDB webserver for B cell epitope prediction, Vaxijen 2.0 and AllergenFP v.1.0 for antigenicity and allergenicity prediction of epitopes, CLUSTAL Omega for mutation identification and PONDR webserver for disorder prediction, PROVEAN score for protein function and iMutantsuite for protein stability prediction. Our results show that 81 mutations have occurred in this protein among Indian SARS-CoV-2 isolates. Subsequently, we characterized the N-protein epitopes to identify seven most promising peptides. We mapped these mutations with seven N-protein epitopes to identify the loss of antigenicity in two of them, suggesting that the mutations occurring in the SARS-CoV-2 genome contribute to the alteration in the properties of epitopes. Altogether, our data strongly indicates that N-protein is gaining several mutations in its B cell epitope regions that might alter protein function.

Recombinant highly antigenic truncated fusion-based protein as a diagnostic antigen for anti-SARS-CoV-2 nucleocapsid antibody ELISA.

Among the main structural protein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), nucleocapsid phosphoprotein (NP) exhibits high immunogenicity and is the most abundant viral protein produced and shed during infection. Detection of antibodies against NP may help assess the number of individuals exposed to SARS-COV-2 or vaccinated against it. Based on these findings and other structural and antigenic evaluations, we designed a recombinant truncated fusion NP-based protein for application in an immunoassay for detecting immunoglobulins in patients who have recovered from COVID-19. In this research, we aligned the NPs from SARS-CoV and SARS-CoV-2 and selected highly antigenic parts of the SARS-CoV-2 sequences based on in-silico studies. The protein was expressed under optimum conditions in the bacterial host BL21 and purified by nickel immobilized metal affinity chromatography. Moreover, the purity level was assessed by SDS-PAGE and Western blotting whereas the folding of the protein was evaluated by circular dichroism. Ultimately, we used the purified recombinant protein in ELISA development in which 42 samples from convalescent patients were compared with 20 samples of the past 2019 patients who had attended laboratories for various clinical check-ups. The sensitivity and specificity were determined as 71% and 90%, respectively, in the optimum cut-off point measured by the receiver operating characteristic curve.

Assessment of Immunogenic and Antigenic Properties of Recombinant Nucleocapsid Proteins of Five SARS-CoV-2 Variants in a Mouse Model.

COVID-19 cases caused by new variants of highly mutable SARS-CoV-2 continue to be identified worldwide. Effective control of the spread of new variants can be achieved through targeting of conserved viral epitopes. In this regard, the SARS-CoV-2 nucleocapsid (N) protein, which is much more conserved than the evolutionarily influenced spike protein (S), is a suitable antigen. The recombinant N protein can be considered not only as a screening antigen but also as a basis for the development of next-generation COVID-19 vaccines, but little is known about induction of antibodies against the N protein via different SARS-CoV-2 variants. In addition, it is important to understand how antibodies produced against the antigen of one variant can react with the N proteins of other variants. Here, we used recombinant N proteins from five SARS-CoV-2 strains to investigate their immunogenicity and antigenicity in a mouse model and to obtain and characterize a panel of hybridoma-derived monoclonal anti-N antibodies. We also analyzed the variable epitopes of the N protein that are potentially involved in differential recognition of antiviral antibodies. These results will further deepen our knowledge of the cross-reactivity of the humoral immune response in COVID-19.

Cross-Reactivity of SARS-CoV-2 Nucleocapsid-Binding Antibodies and Its Implication for COVID-19 Serology Tests.

The emergence of the new coronavirus SARS-CoV-2 in late 2019 led to the global pandemic COVID-19, causing a profound socioeconomic crisis. Adequate diagnostic tools need to be developed to control the ongoing spread of infection. Virus-specific humoral immunity in COVID-19 patients and those vaccinated with specific vaccines has been characterized in numerous studies, mainly using Spike protein-based serology tests. However, Spike protein and specifically its receptor-binding domain (RBD) are mutation-prone, suggesting the reduced sensitivity of the validated serology tests in detecting antibodies raised to variants of concern (VOC). The viral nucleocapsid (N) protein is more conserved compared to Spike, but little is known about cross-reactivity of the N-specific antibodies between the ancestral B.1 virus and different VOCs. Here, we generated recombinant N phosphoproteins from different SARS-CoV-2 strains and analyzed the magnitude of N-specific antibodies in COVID-19 convalescent sera using an in-house N-based ELISA test system. We found a strong positive correlation in the magnitude of anti-N (B.1) antibodies and antibodies specific to various VOCs in COVID-19-recovered patients, suggesting that the N-binding antibodies are highly cross-reactive, and the most immunogenic epitopes within this protein are not under selective pressure. Overall, our study suggests that the RBD-based serology tests should be timely updated to reflect the constantly evolving nature of the SARS-CoV-2 Spike protein, whereas the validated N-based test systems can be used for the analysis of sera from COVID-19 patients regardless of the strain that caused the infection.

Design of siRNA molecules for silencing of membrane glycoprotein, nucleocapsid phosphoprotein, and surface glycoprotein genes of SARS-CoV2.

The global COVID-19 pandemic caused by SARS-CoV2 infected millions of people and resulted in more than 4 million deaths worldwide. Apart from vaccines and drugs, RNA silencing is a novel approach for treating COVID-19. In the present study, siRNAs were designed for the conserved regions targeting three structural genes, M, N, and S, from forty whole-genome sequences of SARS-CoV2 using four different software, RNAxs, siDirect, i-Score Designer, and OligoWalk. Only siRNAs which were predicted in common by all the four servers were considered for further shortlisting. A multistep filtering approach has been adopted in the present study for the final selection of siRNAs by the usage of different online tools, viz., siRNA scales, MaxExpect, DuplexFold, and SMEpred. All these web-based tools consider several important parameters for designing functional siRNAs, e.g., target-site accessibility, duplex stability, position-specific nucleotide preference, inhibitory score, thermodynamic parameters, GC content, and efficacy in cleaving the target. In addition, a few parameters like GC content and dG value of the entire siRNA were also considered for shortlisting of the siRNAs. Antisense strands were subjected to check for any off-target similarities using BLAST. Molecular docking was carried out to study the interactions of guide strands with AGO2 protein. A total of six functional siRNAs (two for each gene) have been finally selected for targeting M, N, and S genes of SARS-CoV2. The siRNAs have not shown any off-target effects, interacted with the domain(s) of AGO2 protein, and were efficacious in cleaving the target mRNA. However, the siRNAs designed in the present study need to be tested in vitro and in vivo in the future.

Spatial structure of Np of novel coronavirus Wuhan-Hu-1 strain and prediction of its B-cell epitope.

Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) is a newly discovered infectious coronavirus, which can cause Coronavirus Disease 2019 (COVID-19). The outbreak of the disease has caused severe impact both at home and abroad. Compared with the other three structural proteins encoded by SARS-CoV-2, Nucleocapsid phosphoprotein (Np) is more conservative and plays an important role in pathogen diagnosis, vaccine design, and treatment. This paper aims to predict the spatial structure of Np in Wuhan-Hu-1 strain and its B-cell epitope,and lay a foundation for the development of epitope vaccine and related monoclonal antibody of SARS-CoV-2. In this study, the Neighbor-joining method in MEGA5.05 was used to construct a phylogenetic tree based on the base sequence of Np of SARS-CoV-2 strain. The SARS-CoV-2 Wuhan-Hu-1 strain was used as the research object, and parameters such as hydrophilicity index, flexible region, surface possibility, and antigenic index were analyzed and predicted by the Protean module in the DNAStar software, combined with the spatial structure simulated by the Phyre2 online tool, so as to comprehensively predict the dominant B-cell epitopes of Np of Wuhan-Hu-1. Results show that the gene sequences of Np of SARS-CoV-2 isolated from different regions were highly similar (99.6%-100%). The amino acid sequence of Np in Wuhan-Hu-1 strain was 419 aa.The spatial structure of Np in Wuhan-Hu-1 strain was fairly regular. It contained only a small amount of α-helixes, while most of the structures were β-sheets, β-turns, and random coils. Results of multi-parameter comprehensive analysis showed that the possible antigenic epitope regions of B-cell were located in the amino acid regions of 52-9,9-5,3-9,6-5,9-4,0-6,4-6,7-7,3-9,7-3,9-5,3-9,7-3,9-5,9-401,and 403-411. The results of this study can provide theoretical information for the development of epitope vaccine, rapid diagnostic reagents, and monoclonal antibodies with respect to SARS-CoV-2, and offer new strategies for COVID-19 treatments. (English) [ FROM AUTHOR] 新型冠状病毒(Severe Acute Respiratory Syndrome Coronavirus 2, SARS-CoV-2)是最新发现的一种可侵染人体的β属冠状病毒, 该病毒入侵机体可引发新型冠状病毒肺炎(Coronavirus Disease 2019, COVID-19), 该疫情的暴发在国内甚至国际上造成了严重影响。核衣壳蛋白(Nucleocapsid phosphoprotein, Np)相较于病毒编码的其它三种结构蛋白保守性更强, 在病原诊断, 疫苗设计和治疗等方面占据重要地位。预测Wuhan-Hu-1 Np的空间结构及其B细胞抗原表位, 为开发SARS-CoV-2的表位疫苗和相关单抗奠定基础。采用MEGA5.05中的Neighbor-joining法构建基于SARS-CoV-2 Np的碱基序列的系统发生树；以SARS-CoV-2 Wuhan-Hu-1株为研究对象, 其柔性区段, 亲水性指数, 抗原指数和蛋白质表面可能性等参数由DNAStar软件中的Protean模块进行分析预测, 结合Phyre2在线工具模拟的空间结构, 综合预测Wuhan-Hu-1 Np的B细胞优势抗原表位。结果发现:不同地区SARS-CoV-2 Np的碱基序列高度相似(99.6%-100%), Wuhan-Hu-1 Np氨基酸序列长419 aa, 其空间构型相对规则, 仅含少量α-螺旋而多见β-折叠, β-转角和无规则卷曲结构；多参数综合分析结果指示, 可能的B细胞抗原表位位于52~59, 69~75, 83~89, 106~115, 119~124, 130~136, 154~166, 217~227, 243~249, 267~273, 299~315, 333~339, 347~363, 379~385, 389~401, 403~411氨基酸区段。本研究旨在为开发SARS-CoV-2表位疫苗, 快速诊断试剂, 单克隆抗体等提供理论信息, 为医治COVID-19给予一些新策略. (Chinese) [ FROM AUTHOR] Copyright of Chinese Journal of Bioinformatics is the property of Bioinformatics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

In-silico design of a multi-epitope for developing sero-diagnosis detection of SARS-CoV-2 using spike glycoprotein and nucleocapsid antigens.

COVID-19 is a pandemic disease caused by novel corona virus, SARS-CoV-2, initially originated from China. In response to this serious life-threatening disease, designing and developing more accurate and sensitive tests are crucial. The aim of this study is designing a multi-epitope of spike and nucleocapsid antigens of COVID-19 virus by bioinformatics methods. The sequences of nucleotides obtained from the NCBI Nucleotide Database. Transmembrane structures of proteins were predicted by TMHMM Server and the prediction of signal peptide of proteins was performed by Signal P Server. B-cell epitopes' prediction was performed by the online prediction server of IEDB server. Beta turn structure of linear epitopes was also performed using the IEDB server. Conformational epitope prediction was performed using the CBTOPE and eventually, eight antigenic epitopes with high physicochemical properties were selected, and then, all eight epitopes were blasted using the NCBI website. The analyses revealed that α-helices, extended strands, ß-turns, and random coils were 28.59%, 23.25%, 3.38%, and 44.78% for S protein, 21.24%, 16.71%, 6.92%, and 55.13% for N Protein, respectively. The S and N protein three-dimensional structure was predicted using the prediction I-TASSER server. In the current study, bioinformatics tools were used to design a multi-epitope peptide based on the type of antigen and its physiochemical properties and SVM method (Machine Learning) to design multi-epitopes that have a high avidity against SARS-CoV-2 antibodies to detect infections by COVID-19.

Development of a Smartphone-Based Nanozyme-Linked Immunosorbent Assay for Quantitative Detection of SARS-CoV-2 Nucleocapsid Phosphoprotein in Blood.

Since December 2019, a novel coronavirus (SARS-CoV-2) has resulted in a global pandemic of coronavirus disease (COVID-19). Although viral nucleic acid test (NAT) has been applied predominantly to detect SARS-CoV-2 RNA for confirmation diagnosis of COVID-19, an urgent need for alternative, rapid, and sensitive immunoassays is required for primary screening of virus. In this study, we developed a smartphone-based nanozyme-linked immunosorbent assay (SP-NLISA) for detecting the specific nucleocapsid phosphoprotein (NP) of SARS-CoV-2 in 37 serum samples from 20 COVID-19 patients who were diagnosed by NAT previously. By using SP-NLISA, 28/37 (75.7%) serum samples were detected for NP antigens and no cross-reactivity with blood donors' control samples collected from different areas of China. In a control assay using the conventional enzyme-linked immunosorbent assay (ELISA), only 7/37 (18.91%) serum samples were detected for NP antigens and no cross-reactivity with control samples. SP-NLISA could be used for rapid detection of SARS-CoV-2 NP antigen in primary screening of SARS-CoV-2 infected individuals.

Virtual screening and dynamics of potential inhibitors targeting RNA binding domain of nucleocapsid phosphoprotein from SARS-CoV-2.

The emergence of the coronavirus disease-2019 pandemic has led to an outbreak in the world. The SARS-CoV-2 is seventh and latest in coronavirus family with unique exonucleases for repairing any mismatches in newly transcribed genetic material. Therefore, drugs with novel additional mechanisms are required to simultaneously target and eliminate the virus. Thus, a newly deciphered N protein is taken as a target that belongs to SARS-CoV-2. They play a vital role in RNA transcription, viral replication and new virion formation. This study used virtual screening, molecular modeling and docking of the 8987 ligands from Asinex and PubChem databases against this novel target protein. Three hotspot sites having DScore ≥1 (Site 1, Site 2 and Site 3) for ligand binding were selected. Subsequently, high throughput screening, standard precision and extra precision docking process and molecular dynamics concluded three best drugs from two libraries. Two antiviral moieties from Asinex databases (5817 and 6799) have docking scores of -10.29 and -10.156; along with their respective free binding energies (ΔG bind) of -51.96 and -64.36 on Site 3. The third drug, Zidovudine, is from PubChem database with docking scores of -9.75 with its binding free energies (ΔG bind) of -59.43 on Site 3. The RMSD and RMSF were calculated for all the three drugs through molecular dynamics simulation studies for 50 ns. Zidovudine shows a very stable interaction with fluctuation starting at 2.4 Å on 2 ns and remained stable at 3 Å from 13 to 50 ns. Thus, paving the way for further biological validation as a potential treatment.Communicated by Ramaswamy H. Sarma.

Docking study of chloroquine and hydroxychloroquine interaction with RNA binding domain of nucleocapsid phospho-protein - an in silico insight into the comparative efficacy of repurposing antiviral drugs.

Recent outbreak of novel Coronavirus disease () pandemic around the world is associated with severe acute respiratory syndrome. The death toll associated with the pandemic is increasing day by day. SARS-CoV-2 is an enveloped virus and its N terminal domain (NTD) of Nucleocapsid protein (N protein) binds to the viral (+) sense RNA and results in virus ribonucleoprotien complex, essential for the virus replication. The N protein is composed of a serine-rich linker region sandwiched between NTD and C terminal (CTD). These terminals play a role in viral entry and its processing post entry. The NTD of SARS-CoV-2 N protein forms orthorhombic crystals and binds to the viral genome. Therefore, there is always a quest to target RNA binding domain of nucleocapsid phosphoprotein (NTD-N-protein which in turn may help in controlling diseases caused by SARS-CoV-2 in humans. The role of Chloroquine and Hydroxychloroquine as potential treatments for is still under debate globally because of some side effects associated with it. This study involves the In silico interactions of Chloroquine and Hydroxychloroquine with the NTD-N-protein of SARS-CoV-2. With the help of various computational methods, we have explored the potential role of both of these antiviral drugs for the treatment of patients by comparing the efficacy of both of the drugs to bind to NTD-N-protein. In our research Hydroxychloroquine exhibited potential inhibitory effects of NTD-N-protein with binding energy -7.28 kcal/mol than Chloroquine (-6.30 kcal/mol) at SARS-CoV-2 receptor recognition of susceptible cells. The outcomes of this research strongly appeal for in vivo trials of Hydroxychloroquine for the patients infected with . Furthermore, the recommended doses of Hydroxychloroquine may reduce the chances of catching to the healthcare workers and staff who are in contact with or delivering direct care to coronavirus patients as long as they have not been diagnosed with . We further hypothesize that the comparative NTD-N-protein -drug docking interactions may help to understand the comparative efficacy of other candidate repurposing drugs until discovery of a proper vaccine.Communicated by Ramaswamy H. Sarma.

Indian Ethnomedicinal Phytochemicals as Promising Inhibitors of RNA-Binding Domain of SARS-CoV-2 Nucleocapsid Phosphoprotein: An In Silico Study.

SARS-CoV-2, an etiological agent of COVID-19, has been the reason for the unexpected global pandemic, causing severe mortality and imposing devastative effects on public health. Despite extensive research work put forward by scientist around globe, so far, no suitable drug or vaccine (safe, affordable, and efficacious) has been identified to treat SARS-CoV-2. As an alternative way of improvising the COVID-19 treatment strategy, that is, strengthening of host immune system, a great deal of attention has been given to phytocompounds from medicinal herbs worldwide. In a similar fashion, the present study deliberately focuses on the phytochemicals of three Indian herbal medicinal plants viz., Mentha arvensis, Coriandrum sativum, and Ocimum sanctum for their efficacy to target well-recognized viral receptor protein through molecular docking and dynamic analyses. Nucleocapsid phosphoprotein (N) of SARS-CoV-2, being a pivotal player in replication, transcription, and viral genome assembly, has been recognized as one of the most attractive viral receptor protein targets for controlling the viral multiplication in the host. Out of 127 phytochemicals screened, nine (linarin, eudesmol, cadinene, geranyl acetate, alpha-thujene, germacrene A, kaempferol-3-O-glucuronide, kaempferide, and baicalin) were found to be phenomenal in terms of exhibiting high binding affinity toward the catalytic pocket of target N-protein. Further, the ADMET prediction analysis unveiled the non-tumorigenic, noncarcinogenic, nontoxic, non-mutagenic, and nonreproductive nature of the identified bioactive molecules. Furthermore, the data of molecular dynamic simulation validated the conformational and dynamic stability of the docked complexes. Concomitantly, the data of the present study validated the anti-COVID efficacy of the bioactives from selected medicinal plants of Indian origin.

Determination of human COVID-19 total antibodies in serum using a time-resolved fluorescence immunoassay.

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world. Antibody detection plays an important role in the diagnosis of COVID-19. Here, we established a new time-resolved fluorescence immunoassay (TRFIA) to determine COVID-19 total antibodies. A double-antigen sandwich TRFIA was optimized and established: recombinant nucleocapsid phosphoprotein (N protein) and spike protein (S protein) of COVID-19 immobilized on 96-well plates captured human COVID-19 antibodies and then banded together with the N/S proteins labeled with europium(III) (Eu3+ ) chelates, and finally, time-resolved fluorometry was used to measure the fluorescence values. We successfully established a TRFIA method for the detection of human COVID-19 total antibodies, and the cutoff value was 2.02. There was no cross-reactivity with the negative reference of the National Reference Panel for IgM and IgG antibodies to COVID-19. The CV of the precision assay was 3.19%, and the assay could be stored stably for 15 days at 37°C. Compared with that of the colloidal gold method and chemiluminescence method, the sensitivity of the TRFIA method was higher, and the false positive/negative rate was lower. This established TRFIA has high sensitivity, accuracy, and specificity, which indicates that this method provides a new detection method for the high-throughput routine diagnosis of COVID-19.

Molecular insight into the genomic variation of SARS-CoV-2 strains from current outbreak.

Coronavirus disease 2019 (COVID-19) is the newly emerging viral disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The epidemic sparked in December 2019 at Wuhan city, China that causes a large global outbreak and a major public health catastrophe. Till now, more than 129 million positive cases have been reported in which more than 2.81 million were dead, surveyed by Johns Hopkins University, USA. The diverse symptoms of COVID-19 and an increased number of positive cases throughout the world hypothesize that this virus assembles more variants that are preventing the pursuit of its adequate treatment as well as the development of the vaccine. In this study, 715 SARS-CoV-2 genomes were retrieved from the gisaid and NCBI viral resources involving 39 countries and 164 different types of variants were identified based on 108 Single Nucleotide Polymorphisms (SNPs) in which the ancestral type of SARS-CoV-2 was found as the most frequent and the most prevalent in China. Moreover, variant type A104 was identified as the most frequent in the USA and A52 in Japan. The study also recognized the most common SNPs such as 241, 3037, 8782, 11083, 14408, 23403, and 28144 as well as variants regarding base-pair, C > T. A total of 65 non-synonymous SNPs were recognized which were mostly located in nucleocapsid phosphoprotein, Non-structural protein 3(Nsp3), and spike glycoprotein encoding gene. Molecular divergence analysis revealed that this virus was phylogenetically related to Yunnan 2013 bat strain. This study indicates SARS-CoV-2 frequently alters their genetic material, which mostly affects the nucleocapsid phosphoprotein, and spike glycoprotein-encoding gene and makes it very challenging to develop SARS-Cov-2 vaccine and antibody-mediated rapid diagnostic kit.

Molecular docking and dynamics studies of curcumin with COVID-19 proteins.

Coronavirus disease 2019 (COVID-19) is caused by a Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2), which is a positive-strand RNA virus. The SARS-CoV-2 genome and its association to SAR-CoV-1 vary from ca. 66 to 96% depending on the type of betacoronavirideae family members. With several drugs, viz. chloroquine, hydroxychloroquine, ivermectin, artemisinin, remdesivir, azithromycin considered for clinical trials, there has been an inherent need to find distinctive antiviral mechanisms of these drugs. Curcumin, a natural bioactive molecule has been shown to have therapeutic potential for various diseases, and its effect on COVID-19 is also currently being explored. In this study, we show the binding potential of curcumin targeted to a variety of SARS-CoV-2 proteins, viz. spike glycoproteins (PDB ID: 6VYB), nucleocapsid phosphoprotein (PDB ID: 6VYO), spike protein-ACE2 (PDB ID: 6M17) along with nsp10 (PDB ID: 6W4H) and RNA dependent RNA polymerase (PDB ID: 6M71) structures. Furthermore, representative docking complexes were validated using molecular dynamics simulations and mechanistic studies at 100 ns was carried on nucleocapsid and nsp10 proteins with curcumin complexes which resulted in stable and efficient binding energies and correlated with that of docked binding energies of the complexes. Both the docking and simulation studies indicate that curcumin has the potential as an antiviral against COVID-19.

Genetic characterization of structural and open reading Fram-8 proteins of SARS-CoV-2 isolates from different countries.

Since December 2019, a severe pandemic of pneumonia, COVID-19 associated with a novel coronavirus (SARS-CoV-2), have emerged in Wuhan, China and spreading throughout the world. As RNA viruses have a high mutation rate therefore we wanted to identify whether this virus is also prone to mutations. For this reason we selected four major structural (Spike protein (S), Envelope protein (E), Membrane glycoprotein (M), Nucleocapsid phosphoprotein (N)) and ORF8 protein of 100 different SARS-CoV-2 isolates of fifteen countries from NCBI database and compared these to the reference sequence, Wuhan NC_045512.2, which was the first isolate of SARS-CoV-2 that was sequenced. By multiple sequence alignment of amino acids, we observed substitutions and deletion in S protein at 13 different sites in the isolates of five countries (China, USA, Finland, India and Australia) as compared to the reference sequence. Similarly, alignment of N protein revealed substitutions at three different sites in isolates of China, Spain and Japan. M protein exhibits substitution only in one isolates from USA, however, no mutation was observed in E protein of any isolate. Interestingly, in ORF8 substitution of Leucine, a nonpolar to Serine a polar amino acid at same position (aa84 L to S) in 23 isolates of five countries i.e. China, USA, Spain, Taiwan and India were observed, which may affect the conformation of peptides. Thus, we observed several mutations in the isolates thereafter the first sequencing of SARS-CoV-2 isolate, NC_045512.2, which suggested that this virus might be a threat to the whole world and therefore further studies are needed to characterize how these mutations in different proteins affect the functionality and pathogenesis of SARS-CoV-2.

Identification and molecular characterization of mutations in nucleocapsid phosphoprotein of SARS-CoV-2.

SARS-CoV-2 genome encodes four structural proteins that include the spike glycoprotein, membrane protein, envelope protein and nucleocapsid phosphoprotein (N-protein). The N-protein interacts with viral genomic RNA and helps in packaging. As SARS-CoV-2 spread to almost all countries worldwide within 2-3 months, it also acquired mutations in its RNA genome. Therefore, this study was conducted with an aim to identify the variations present in N-protein of SARS-CoV-2. Here, we analysed 4,163 reported sequence of N-protein from United States of America (USA) and compared them with the first reported sequence from Wuhan, China. Our study identified 107 mutations that reside all over the N-protein. Further, we show the high rate of mutations in intrinsically disordered regions (IDRs) of N-protein. Our study show 45% residues of IDR2 harbour mutations. The RNA-binding domain (RBD) and dimerization domain of N-protein also have mutations at key residues. We further measured the effect of these mutations on N-protein stability and dynamicity and our data reveals that multiple mutations can cause considerable alterations. Altogether, our data strongly suggests that N-protein is one of the mutational hotspot proteins of SARS-CoV-2 that is changing rapidly and these mutations can potentially interferes with various aspects of N-protein functions including its interaction with RNA, oligomerization and signalling events.

A computational approach to design potential siRNA molecules as a prospective tool for silencing nucleocapsid phosphoprotein and surface glycoprotein gene of SARS-CoV-2.

An outbreak, caused by an RNA virus, SARS-CoV-2 named COVID-19 has become pandemic with a magnitude which is daunting to all public health institutions in the absence of specific antiviral treatment. Surface glycoprotein and nucleocapsid phosphoprotein are two important proteins of this virus facilitating its entry into host cell and genome replication. Small interfering RNA (siRNA) is a prospective tool of the RNA interference (RNAi) pathway for the control of human viral infections by suppressing viral gene expression through hybridization and neutralization of target complementary mRNA. So, in this study, the power of RNA interference technology was harnessed to develop siRNA molecules against specific target genes namely, nucleocapsid phosphoprotein gene and surface glycoprotein gene. Conserved sequence from 139 SARS-CoV-2 strains from around the globe was collected to construct 78 siRNA that can inactivate nucleocapsid phosphoprotein and surface glycoprotein genes. Finally, based on GC content, free energy of folding, free energy of binding, melting temperature, efficacy prediction and molecular docking analysis, 8 siRNA molecules were selected which are proposed to exert the best action. These predicted siRNAs should effectively silence the genes of SARS-CoV-2 during siRNA mediated treatment assisting in the response against SARS-CoV-2.

In silico screening of hundred phytocompounds of ten medicinal plants as potential inhibitors of nucleocapsid phosphoprotein of COVID-19: an approach to prevent virus assembly.

Currently, there is no specific treatment to cure COVID-19. Many medicinal plants have antiviral, antioxidant, antibacterial, antifungal, anticancer, wound healing etc. Therefore, the aim of the current study was to screen for potent inhibitors of N-terminal domain (NTD) of nucleocapsid phosphoprotein of SARS-CoV-2. The structure of NTD of RNA binding domain of nucleocapsid phosphoprotein of SARS coronavirus 2 was retrieved from the Protein Data Bank (PDB 6VYO) and the structures of 100 different phytocompounds were retrieved from Pubchem. The receptor protein and ligands were prepared using Schrodinger's Protein Preparation Wizard. Molecular docking was done by using the Schrodinger's maestro 12.0 software. Drug likeness and toxicity of active phytocompounds was predicted by using Swiss adme, admetSAR and protox II online servers. Molecular dynamic simulation of the best three protein- ligand complexes (alizarin, aloe-emodin and anthrarufin) was performed to study the interaction stability. We have identified three potential active sites (named as A, B, C) on receptor protein for efficient binding of the phytocompounds. We found that, among 100 phytocompounds, emodin, aloe-emodin, anthrarufin, alizarine, and dantron of Rheum emodi showed good binding affinity at all the three active sites of RNA binding domain of nucleocapsid phosphoprotein of COVID-19.The binding energies of emodin, aloe-emodin, anthrarufin, alizarine, and dantron were -8.299, -8.508, -8.456, -8.441, and -8.322 Kcal mol-1 respectively (site A), -7.714, -6.433, -6.354, -6.598, and -6.99 Kcal mol-1 respectively (site B), and -8.299, 8.508, 8.538, 8.841, and 8.322 Kcal mol-1 respectively (site C). All the active phytocompounds follows the drug likeness properties, non-carcinogenic, and non-toxic. Theses phytocompounds (alone or in combination) could be developed into effective therapy against COVID-19. From MD simulation data, we found that all three complexes of 6VYO with alizarin, aloe-emodin and anthrarufin were stable up to 50 ns. These phytocompounds can be tested further for in vitro or in vivo and used as a potential drug to cure SARS-CoV-2 infection.Communicated by Ramaswamy H. Sarma.

Structural insights into the mechanism of RNA recognition by the N-terminal RNA-binding domain of the SARS-CoV-2 nucleocapsid phosphoprotein.

The emergence of recent SARS-CoV-2 has become a global health issue. This single-stranded positive-sense RNA virus is continuously spreading with increasing morbidities and mortalities. The proteome of this virus contains four structural and sixteen nonstructural proteins that ensure the replication of the virus in the host cell. However, the role of phosphoprotein (N) in RNA recognition, replicating, transcribing the viral genome, and modulating the host immune response is indispensable. Recently, the NMR structure of the N-terminal domain of the Nucleocapsid Phosphoprotein has been reported, but its precise structural mechanism of how the ssRNA interacts with it is not reported yet. Therefore, here, we have used an integrated computational pipeline to identify the key residues, which play an essential role in RNA recognition. We generated multiple variants by using an alanine scanning strategy and performed an extensive simulation for each system to signify the role of each interfacial residue. Our analyses suggest that residues T57A, H59A, S105A, R107A, F171A, and Y172A significantly affected the dynamics and binding of RNA. Furthermore, per-residue energy decomposition analysis suggests that residues T57, H59, S105 and R107 are the key hotspots for drug discovery. Thus, these residues may be useful as potential pharmacophores in drug designing.

State-of-the-art tools to identify druggable protein ligand of SARS-CoV-2.

INTRODUCTION: The SARS-CoV-2 (previously 2019-nCoV) outbreak in Wuhan, China and other parts of the world affects people and spreads coronavirus disease 2019 (COVID-19) through human-to-human contact, with a mortality rate of > 2%. There are no approved drugs or vaccines yet available against SARS-CoV-2. MATERIAL AND METHODS: State-of-the-art tools based on in-silico methods are a cost-effective initial approach for identifying appropriate ligands against SARS-CoV-2. The present study developed the 3D structure of the envelope and nucleocapsid phosphoprotein of SARS-CoV-2, and molecular docking analysis was done against various ligands. RESULTS: The highest log octanol/water partition coefficient, high number of hydrogen bond donors and acceptors, lowest non-bonded interaction energy between the receptor and the ligand, and high binding affinity were considered for the best ligand for the envelope (mycophenolic acid: log P = 3.00; DG = -10.2567 kcal/mol; pKi = 7.713 µM) and nucleocapsid phosphoprotein (1-[(2,4-dichlorophenyl)methyl]pyrazole-3,5-dicarboxylic acid: log P = 2.901; DG = -12.2112 kcal/mol; pKi = 7.885 µM) of SARS-CoV-2. CONCLUSIONS: The study identifies the most potent compounds against the SARS-CoV-2 envelope and nucleocapsid phosphoprotein through state-of-the-art tools based on an in-silico approach. A combination of these two ligands could be the best option to consider for further detailed studies to develop a drug for treating patients infected with SARS-CoV-2, COVID-19.