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Genomic variance of the 2019-nCoV coronavirus.

ABSTRACT: There is a rising global concern for the recently emerged novel coronavirus (2019-nCoV). Full genomic sequences have been released by the worldwide scientific community in the last few weeks to understand the evolutionary origin and molecular characteristics of this virus. Taking advantage of all the genomic information currently available, we constructed a phylogenetic tree including also representatives of other coronaviridae, such as Bat coronavirus (BCoV) and severe acute respiratory syndrome. We confirm high sequence similarity (>99%) between all sequenced 2019-nCoVs genomes available, with the closest BCoV sequence sharing 96.2% sequence identity, confirming the notion of a zoonotic origin of 2019-nCoV. Despite the low heterogeneity of the 2019-nCoV genomes, we could identify at least two hypervariable genomic hotspots, one of which is responsible for a Serine/Leucine variation in the viral ORF8-encoded protein. Finally, we perform a full proteomic comparison with other coronaviridae, identifying key aminoacidic differences to be considered for antiviral strategies deriving from previous anti-coronavirus approaches.

SUBMITTER: Ceraolo C

PROVIDER: S-EPMC7166773 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Genomic variance of the 2019-nCoV coronavirus.

Ceraolo Carmine C Giorgi Federico M FM

Journal of medical virology 20200219 5

There is a rising global concern for the recently emerged novel coronavirus (2019-nCoV). Full genomic sequences have been released by the worldwide scientific community in the last few weeks to understand the evolutionary origin and molecular characteristics of this virus. Taking advantage of all the genomic information currently available, we constructed a phylogenetic tree including also representatives of other coronaviridae, such as Bat coronavirus (BCoV) and severe acute respiratory syndrom ...[more]

PMID: 32027036

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Project description:The emergence of 2019 novel coronavirus (2019-nCoV) is of global concern and might have emerged from RNA recombination among existing coronaviruses. CoV spike (S) protein which is crucial for receptor binding, membrane fusion via conformational changes, internalization of the virus, host tissue tropism and comprises crucial targets for vaccine development, remain largely uncharacterized. Therefore, the present study has been planned to determine the sequence variation, structural and antigenic divergence of S glycoprotein which may be helpful for the management of 2019-nCoV infection. The sequences of spike glycoprotein of 2019-nCoV and SARS coronavirus (SARS-CoV) were used for the comparison. The sequence variations were determined using EMBOSS Needle pairwise sequence alignment tools. The variation in glycosylation sites was predicted by NetNGlyc 1.0 and validated by N-GlyDE server. Antigenicity was predicted by NetCTL 1.2 and validated by IEDB Analysis Resource server. The structural divergence was determined by using SuperPose Version 1.0 based on cryo-EM structure of the SARS coronavirus spike glycoprotein. Our data suggests that 2019-nCoV is newly spilled coronavirus into humans in China is closely related to SARS-CoV, which has only 12.8% of difference with SARS-CoV in S protein and has 83.9% similarity in minimal receptor-binding domain with SARS-CoV. Addition of a novel glycosylation sites were observed in 2019-nCoV. In addition, antigenic analysis proposes that great antigenic differences exist between both the viral strains, but some of the epitopes were found to be similar between both the S proteins. In spite of the variation in S protein amino acid composition, we found no significant difference in their structures. Collectively, for the first time our results exhibit the emergence of human 2019-nCoV is closely related to predecessor SARS-CoV and provide the evidence that 2019-nCoV uses various novel glycosylation sites as SARS-CoV and may have a potential to become pandemic owing its antigenic discrepancy. Further, demonstration of novel Cytotoxic T lymphocyte epitopes may impart opportunities for the development of peptide based vaccine for the prevention of 2019-nCoV.

Project description:A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence about its activity on the virus. It is of high significance to develop a drug that can combat the virus effectively to save valuable human lives. It usually takes a much longer time to develop a drug using traditional methods. For 2019-nCoV, it is now better to rely on some alternative methods such as deep learning to develop drugs that can combat such a disease effectively since 2019-nCoV is highly homologous to SARS-CoV. In the present work, we first collected virus RNA sequences of 18 patients reported to have 2019-nCoV from the public domain database, translated the RNA into protein sequences, and performed multiple sequence alignment. After a careful literature survey and sequence analysis, 3C-like protease is considered to be a major therapeutic target and we built a protein 3D model of 3C-like protease using homology modeling. Relying on the structural model, we used a pipeline to perform large scale virtual screening by using a deep learning based method to accurately rank/identify protein-ligand interacting pairs developed recently in our group. Our model identified potential drugs for 2019-nCoV 3C-like protease by performing drug screening against four chemical compound databases (Chimdiv, Targetmol-Approved_Drug_Library, Targetmol-Natural_Compound_Library, and Targetmol-Bioactive_Compound_Library) and a database of tripeptides. Through this paper, we provided the list of possible chemical ligands (Meglumine, Vidarabine, Adenosine, D-Sorbitol, D-Mannitol, Sodium_gluconate, Ganciclovir and Chlorobutanol) and peptide drugs (combination of isoleucine, lysine and proline) from the databases to guide the experimental scientists and validate the molecules which can combat the virus in a shorter time.

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Genomic variance of the 2019-nCoV coronavirus.

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Genomic variance of the 2019-nCoV coronavirus.

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