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  Original Article

  Sep 7, 2020

  The Novel Coronavirus Enigma: Phylogeny and Analyses of Coevolving Mutations Among the SARS-CoV-2 Viruses Circulating in India

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  Authors List:

  • Anindita Banerjee  
  • Rakesh Sarkar  
  • Suvrotoa Mitra  
  • Mahadeb Lo  
  • Shanta Dutta  
  • Mamta Chawla-Sarkar  

  Abstract:

  Background: The RNA genome of the emerging novel coronavirus is rapidly mutating, and its human-to-human transmission rate is increasing. Hence, temporal dissection of their evolutionary dynamics, the nature of variations among different strains, and understanding the single nucleotide polymorphisms in the endemic settings are crucial. Delineating the heterogeneous genomic constellations of this novel virus will help us understand its complex behavior in a particular geographical region. Objective: This is a comprehensive analysis of 95 Indian SARS-CoV-2 genome sequences available from the Global Initiative on Sharing All Influenza Data (GISAID) repository during the first 6 months of 2020 (January through June). Evolutionary dynamics, gene-specific phylogeny, and the emergence of the novel coevolving mutations in 9 structural and nonstructural genes among circulating SARS-CoV-2 strains across 12 different Indian states were analyzed. Methods: A total of 95 SARS-CoV-2 nucleotide sequences submitted from India were downloaded from the GISAID database. Molecular Evolutionary Genetics Analysis, version X software was used to construct the 9 phylogenetic dendrograms based on nucleotide sequences of the SARS-CoV-2 genes. Analyses of the coevolving mutations were done in comparison to the prototype SARS-CoV-2 from Wuhan, China. The secondary structure of the RNA-dependent RNA polymerase/nonstructural protein NSP12 was predicted with respect to the novel A97V mutation. Results: Phylogenetic analyses revealed the evolution of “genome-type clusters” and adaptive selection of “L”-type SARS-CoV-2 strains with genetic closeness to the bat severe acute respiratory syndrome–like coronaviruses. These strains were distant to pangolin or Middle East respiratory syndrome–related coronavirus strains. With regard to the novel coevolving mutations, 2 groups have been seen circulating in India at present, the “major group” (66/95, 69.4%) and the “minor group” (21/95, 22.1%) , harboring 4 and 5 coexisting mutations, respectively. The “major group” mutations fall in the A2a clade. All the minor group mutations, except 11083G>T (L37F, NSP6 gene), were unique to the Indian isolates. Conclusions: This study highlights the rapidly evolving SARS-CoV-2 virus and the cocirculation of multiple clades and subclades. This comprehensive study is a potential resource for monitoring the novel mutations in the viral genome, interpreting changes in viral pathogenesis, and designing vaccines or other therapeutics.

  • JMIR Bioinformatics Biotechnol 2020;1(1):e20735

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  Tutorial

  Jun 19, 2020

  Molecular Docking Using Chimera and Autodock Vina Software for Nonbioinformaticians

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  Authors List:

  • Sania Safdar Butt  
  • Yasmin Badshah  
  • Maria Shabbir  
  • Mehak Rafiq  

  Abstract:

  In the field of drug discovery, many methods of molecular modeling have been employed to study complex biological and chemical systems. Experimental strategies are integrated with computational approaches for the identification, characterization, and development of novel drugs and compounds. In modern drug designing, molecular docking is an approach that explores the confirmation of a ligand within the binding site of a macromolecule. To date, many software and tools for docking have been employed. AutoDock Vina (in UCSF [University of California, San Francisco] Chimera) is one of the computationally fastest and most accurate software employed in docking. In this paper, a sequential demonstration of molecular docking of the ligand fisetin with the target protein Akt has been provided, using AutoDock Vina in UCSF Chimera 1.12. The first step involves target protein ID retrieval from the protein database, the second step involves visualization of the protein structure in UCSF Chimera, the third step involves preparation of the target protein for docking, the fourth step involves preparation of the ligand for docking, the fifth step involves docking of the ligand and the target protein as Mol.2 files in Chimera by using AutoDock Vina, and the final step involves interpretation and analysis of the docking results. By following the guidelines and steps outlined in this paper, researchers with no previous background in bioinformatics research can perform computational docking in an easier and more user-friendly manner.

  • JMIR Bioinformatics Biotechnol 2020;1(1):e14232

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  Original Article

  Jun 19, 2020

  Structural Basis for Designing Multiepitope Vaccines Against COVID-19 Infection: In Silico Vaccine Design and Validation

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  Authors List:

  • Sukrit Srivastava  
  • Sonia Verma  
  • Mohit Kamthania  
  • Rupinder Kaur  
  • Ruchi Kiran Badyal  
  • Ajay Kumar Saxena  
  • Ho-Joon Shin  
  • Michael Kolbe  
  • Kailash C Pandey  

  Abstract:

  Background: The novel coronavirus disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to the ongoing 2019-2020 pandemic. SARS-CoV-2 is a positive-sense single-stranded RNA coronavirus. Effective countermeasures against SARS-CoV-2 infection require the design and development of specific and effective vaccine candidates. Objective: To address the urgent need for a SARS-CoV-2 vaccine, in the present study, we designed and validated one cytotoxic T lymphocyte (CTL) and one helper T lymphocyte (HTL) multi-epitope vaccine (MEV) against SARS-CoV-2 using various in silico methods. Methods: Both designed MEVs are composed of CTL and HTL epitopes screened from 11 Open Reading Frame (ORF), structural and nonstructural proteins of the SARS-CoV-2 proteome. Both MEVs also carry potential B-cell linear and discontinuous epitopes as well as interferon gamma–inducing epitopes. To enhance the immune response of our vaccine design, truncated (residues 10-153) Onchocerca volvulus activation-associated secreted protein-1 was used as an adjuvant at the N termini of both MEVs. The tertiary models for both the designed MEVs were generated, refined, and further analyzed for stable molecular interaction with toll-like receptor 3. Codon-biased complementary DNA (cDNA) was generated for both MEVs and analyzed in silico for high level expression in a mammalian (human) host cell line. Results: In the present study, we screened and shortlisted 38 CTL, 33 HTL, and 12 B cell epitopes from the 11 ORF protein sequences of the SARS-CoV-2 proteome. Moreover, the molecular interactions of the screened epitopes with their respective human leukocyte antigen allele binders and the transporter associated with antigen processing (TAP) complex were positively validated. The shortlisted screened epitopes were utilized to design two novel MEVs against SARS-CoV-2. Further molecular models of both MEVs were prepared, and their stable molecular interactions with toll-like receptor 3 were positively validated. The codon-optimized cDNAs of both MEVs were also positively analyzed for high levels of overexpression in a human cell line. Conclusions: The present study is highly significant in terms of the molecular design of prospective CTL and HTL vaccines against SARS-CoV-2 infection with potential to elicit cellular and humoral immune responses. The epitopes of the designed MEVs are predicted to cover the large human population worldwide (96.10%). Hence, both designed MEVs could be tried in vivo as potential vaccine candidates against SARS-CoV-2.

  • JMIR Bioinformatics Biotechnol 2020;1(1):e19371

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