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. 2020 Apr 21:22:8.
doi: 10.1186/s12575-020-00121-9. eCollection 2020.

Combination of Biodata Mining and Computational Modelling in Identification and Characterization of ORF1ab Polyprotein of SARS-CoV-2 Isolated from Oronasopharynx of an Iranian Patient

Reza Zolfaghari Emameh  1 , Hassan Nosrati  2 , Ramezan Ali Taheri  3
Affiliations

Combination of Biodata Mining and Computational Modelling in Identification and Characterization of ORF1ab Polyprotein of SARS-CoV-2 Isolated from Oronasopharynx of an Iranian Patient

Reza Zolfaghari Emameh et al. Biol Proced Online. .

Abstract

Background: Coronavirus disease 2019 (COVID-19) is an emerging zoonotic viral infection, which was started in Wuhan, China, in December 2019 and transmitted to other countries worldwide as a pandemic outbreak. Iran is one of the top ranked countries in the tables of COVID-19-infected and -mortality cases that make the Iranian patients as the potential targets for diversity of studies including epidemiology, biomedical, biodata, and viral proteins computational modelling studies.

Results: In this study, we applied bioinformatic biodata mining methods to detect CDS and protein sequences of ORF1ab polyprotein of SARS-CoV-2 isolated from oronasopharynx of an Iranian patient. Then through the computational modelling and antigenicity prediction approaches, the identified polyprotein sequence was analyzed. The results revealed that the identified ORF1ab polyprotein belongs to a part of nonstructural protein 1 (nsp1) with the high antigenicity residues in a glycine-proline or hydrophobic amino acid rich domain.

Conclusions: The results revealed that nsp1 as a virulence factor and crucial agent in spreading of the COVID-19 among the society can be a potential target for the future epidemiology, drug, and vaccine studies.

Keywords: Biodata mining; COVID-19; ORF1ab; Protein Modelling; SARS-CoV-2; nsp1.

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Conflict of interest statement

Competing InterestsThe authors declare that they have no conflict of interests.

Figures

Fig. 1
Fig. 1
Multiple sequence alignment (MSA) analysis of ORF1ab polyprotein sequence. a MSA analysis of the Iranian CDS with the CDS query from Wuhan, China (yellow highlight); b MSA analysis of the Iranian partial ORF1ab polyprotein sequence with the query protein sequence from Wuhan, China (grey highlight). Both MSA evaluations show 100% identity
Fig. 2
Fig. 2
BLAST homology search analysis of the partial ORF1ab polyprotein sequence. The homology analysis defined that 39 out of 47 amino acids of the Iranian subject protein sequence are similar to the query protein sequence (NMR entry ID: 2GDT), which belonged to nsp1 from SARS-CoV
Fig. 3
Fig. 3
Protein Modelling of the partial ORF1ab polyprotein sequence. NGL (WebGL) viewer visualized the NMR structure of entry ID: 2GDT to (a) cartoon-rainbow style and (b) spacefill-hydrophobicity style. Both models show that partial ORF1ab polyprotein from the Iranian patient and nsp1 from SARS-CoV have highly similar structures. The black amino acids are from the query and the red amino acids are from the subject protein sequences
Fig. 4
Fig. 4
Amino acids locations of the most antigenic domain of the partial ORF1ab polyprotein sequence. a Cartoon-rainbow style and b spacefill-hydrophobicity style show the location of Gly94, Pro98, and Gly101 on the surface of the subject protein, which are accessible to the human immune system. The black amino acids are from the query and the red amino acids are from the subject protein sequences. The arrows show the buried amino acids
See this image and copyright information in PMC

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