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ABSTRACT
| Title |
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Screening of Potential Candidates for SARS-CoV-2 Spike Glycoprotein using Bioinformatics approach |
| Authors |
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Dhammapal Bharne |
| Keywords |
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Covid-19, orthologs, evolutionary differences, docking, binding energy |
| Issue Date |
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May 2020 |
| Abstract |
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Background: Covid-19 is a pandemic disease caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It deceased more than three lakh people and infected millions of people across the globe till date. The disease is highly contagious, spreading from person to person through direct contact or through the aerosols released by coughing or sneezing. To reduce the chain of infections, social distancing and sanitary measures are followed. Since, drugs and vaccines are under development, screening of potential candidates using bioinformatics approach may provide an instant solution to stop further deaths and spread of the disease. Methods: Orthologous proteins of SARS-CoV-2 were predicted with reciprocal best blast hit to identify the protein with large evolutionary difference. Homologous region of the evolutionary difference in 3D structure of the proteins was detected using multiple sequence alignment (MSA). The candidates from DrugBank exhibiting high binding affinities with the homologous region as well as with the entire protein structure were uncovered through docking analysis. Results: The orthologous proteins showed the surface spike glycoprotein as the protein with large evolutionary difference. The MSA detected GLN96, LEU97, GLN98, ALA99 and LEU100 amino acid sequence in the spike glycoprotein as the homologous region of evolutionary difference. Docking analysis revealed Remdesivir and TMC_310911 to exhibit the highest binding affinities with the homologous region and the entire protein respectively. Conclusions: The present study uncovers Remdesivir and TMC_310911 as the highly potential candidates for Covid-19. Further investigations may lead to prevention of infections and mortality due to the disease. |
| Page(s) |
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80-86 |
| ISSN |
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0975-9492 |
| Source |
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Vol. 11, No.05 |
| PDF |
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Download |
| DOI |
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10.21817/ijpsr/2020/v11i5/201105003 |
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