tetano
Editor, Senior Moderator
Comput Biol Med
. 2020 Dec 1;128:104158.
doi: 10.1016/j.compbiomed.2020.104158. Online ahead of print.
Next-generation computational tools and resources for coronavirus research: From detection to vaccine discovery
Rajiv Kangabam[SUP] 1 [/SUP], Susrita Sahoo[SUP] 2 [/SUP], Arpan Ghosh[SUP] 3 [/SUP], Riya Roy[SUP] 1 [/SUP], Yumnam Silla[SUP] 4 [/SUP], Namrata Misra[SUP] 3 [/SUP], Mrutyunjay Suar[SUP] 5 [/SUP]
Affiliations
Abstract
The COVID-19 pandemic has affected 215 countries and territories around the world with 60,187,347 coronavirus cases and 17,125,719 currently infected patients confirmed as of the November 25, 2020. Currently, many countries are working on developing new vaccines and therapeutic drugs for this novel virus strain, and a few of them are in different phases of clinical trials. The advancement in high-throughput sequence technologies, along with the application of bioinformatics, offers invaluable knowledge on genomic characterization and molecular pathogenesis of coronaviruses. Recent multi-disciplinary studies using bioinformatics methods like sequence-similarity, phylogenomic, and computational structural biology have provided an in-depth understanding of the molecular and biochemical basis of infection, atomic-level recognition of the viral-host receptor interaction, functional annotation of important viral proteins, and evolutionary divergence across different strains. Additionally, various modern immunoinformatic approaches are also being used to target the most promiscuous antigenic epitopes from the SARS-CoV-2 proteome for accelerating the vaccine development process. In this review, we summarize various important computational tools and databases available for systematic sequence-structural study on coronaviruses. The features of these public resources have been comprehensively discussed, which may help experimental biologists with predictive insights useful for ongoing research efforts to find therapeutics against the infectious COVID-19 disease.
Keywords: COVID-19; Computational tools; Coronavirus; Databases; Genomic; SARS-CoV-2
. 2020 Dec 1;128:104158.
doi: 10.1016/j.compbiomed.2020.104158. Online ahead of print.
Next-generation computational tools and resources for coronavirus research: From detection to vaccine discovery
Rajiv Kangabam[SUP] 1 [/SUP], Susrita Sahoo[SUP] 2 [/SUP], Arpan Ghosh[SUP] 3 [/SUP], Riya Roy[SUP] 1 [/SUP], Yumnam Silla[SUP] 4 [/SUP], Namrata Misra[SUP] 3 [/SUP], Mrutyunjay Suar[SUP] 5 [/SUP]
Affiliations
- PMID: 33301953
- PMCID: PMC7705366
- DOI: 10.1016/j.compbiomed.2020.104158
Abstract
The COVID-19 pandemic has affected 215 countries and territories around the world with 60,187,347 coronavirus cases and 17,125,719 currently infected patients confirmed as of the November 25, 2020. Currently, many countries are working on developing new vaccines and therapeutic drugs for this novel virus strain, and a few of them are in different phases of clinical trials. The advancement in high-throughput sequence technologies, along with the application of bioinformatics, offers invaluable knowledge on genomic characterization and molecular pathogenesis of coronaviruses. Recent multi-disciplinary studies using bioinformatics methods like sequence-similarity, phylogenomic, and computational structural biology have provided an in-depth understanding of the molecular and biochemical basis of infection, atomic-level recognition of the viral-host receptor interaction, functional annotation of important viral proteins, and evolutionary divergence across different strains. Additionally, various modern immunoinformatic approaches are also being used to target the most promiscuous antigenic epitopes from the SARS-CoV-2 proteome for accelerating the vaccine development process. In this review, we summarize various important computational tools and databases available for systematic sequence-structural study on coronaviruses. The features of these public resources have been comprehensively discussed, which may help experimental biologists with predictive insights useful for ongoing research efforts to find therapeutics against the infectious COVID-19 disease.
Keywords: COVID-19; Computational tools; Coronavirus; Databases; Genomic; SARS-CoV-2