DBCOVP: A database of coronavirus virulent glycoproteins

Sahoo, Susrita; Mahapatra, Soumya Ranjan; Parida, Bikram Kumar; Rath, Satyajit; Dehury, Budheswar; Raina, Vishakha; Mohakud, Nirmal Kumar; Misra, Namrata; Suar, Mrutyunjay

doi:10.1016/j.compbiomed.2020.104131

Cited by 21 publications

(9 citation statements)

References 41 publications

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“…The result of this indicated that more than 80% of the world's population was covered by all the predicted epitopes and the HLA alleles that bind them, which is essential for a vaccine candidate since the emerging SARS-CoV-2 strain has affected people all over the world. The predicted epitopes' 3D structure was determined, and a docking technique was used to study the binding interaction with the most conserved HLA allele [ 44 ].…”

Section: Covid-19 Vaccine Development Computational Toolsmentioning

confidence: 99%

COVID-19 Vaccines: Computational tools and Development

Osamor

Ikeakanam

Bishung

et al. 2023

Informatics in Medicine Unlocked

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Section: Covid-19 Vaccine Development Computational Toolsmentioning

confidence: 99%

COVID-19 Vaccines: Computational tools and Development

Osamor

Ikeakanam

Bishung

et al. 2023

Informatics in Medicine Unlocked

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“…In another example of an immunoinformatics approach (Panda et al, 2020), virtual drug screening of existing antiviral compounds with the goal of "repurposing" current pharmaceutical drugs enabled the rapid identification of an polymerase inhibitor, PC786, with the mechanism of binding illustrated by the molecular docking simulations performed in silico, and could then be used to guide the design of T-cell and B-cell epitopes against SARS-CoV-2 for vaccine production. Recently, efforts have been made to compile databases (Sahoo et al, 2021) of the structural glycoproteins of beta coronaviruses (such as SARS-CoV-2) and the T-cell and B-cell epitopes for each protein, with built-in tools to help researchers perform similarity search, cross genome comparison, phylogenetic analysis and multiple sequence alignment to help speed up vaccine research and development. Using such techniques, it is now possible to rapidly design a multi-epitope construct (Mahapatra et al, 2020) for the purpose of designing peptide-based vaccines against pathogens such as SARS-CoV-2, without having to rely on expensive, timeconsuming traditional methods such as mouse models of infection.…”

Section: Outlook and Future Research Directionsmentioning

confidence: 99%

Graphene, Carbon Nanotube and Plasmonic Nanosensors for Detection of Viral Pathogens: Opportunities for Rapid Testing in Pandemics like COVID-19

Bardhan

Jansen

Belcher

2021

Front. Nanotechnol.

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With the emergence of global pandemics such as the Black Death (Plague), 1918 influenza, smallpox, tuberculosis, HIV/AIDS, and currently the COVID-19 outbreak caused by the SARS-CoV-2 virus, there is an urgent, pressing medical need to devise methods of rapid testing and diagnostics to screen a large population of the planet. The important considerations for any such diagnostic test include: 1) high sensitivity (to maximize true positive rate of detection); 2) high specificity (to minimize false positives); 3) low cost of testing (to enable widespread adoption, even in resource-constrained settings); 4) rapid turnaround time from sample collection to test result; and 5) test assay without the need for specialized equipment. While existing testing methods for COVID-19 such as RT-PCR (real-time reverse transcriptase polymerase chain reaction) offer high sensitivity and specificity, they are quite expensive – in terms of the reagents and equipment required, the laboratory expertise needed to run and interpret the test data, and the turnaround time. In this review, we summarize the recent advances made using carbon nanotubes for sensors; as a nanotechnology-based approach for diagnostic testing of viral pathogens; to improve the performance of the detection assays with respect to sensitivity, specificity and cost. Carbon nanomaterials are an attractive platform for designing biosensors due to their scalability, tunable functionality, photostability, and unique opto-electronic properties. Two possible approaches for pathogen detection using carbon nanomaterials are discussed here: 1) optical sensing, and 2) electrochemical sensing. We explore the chemical modifications performed to add functionality to the carbon nanotubes, and the physical, optical and/or electronic considerations used for testing devices or sensors fabricated using these carbon nanomaterials. Given this progress, it is reason to be cautiously optimistic that nanosensors based on carbon nanotubes, graphene technology and plasmonic resonance effects can play an important role towards the development of accurate, cost-effective, widespread testing capacity for the world’s population, to help detect, monitor and mitigate the spread of disease outbreaks.

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“…The Database of COronavirus Virulent glycoProteins (DBCOVP; covp.immt.res.in/ accessed on 21 July 2021) is a manually curated web server that is a complete repository of structural virulent glycoproteins, viz., nucleocapsid, membrane, envelope, and spike proteins from the 137 coronaviruses strain belonging to betacoronavirus genera [ 22 ]. At present, the DBCOVP harbors 185 protein sequences (47 spike proteins, 43 envelope proteins, 46 membrane proteins, 49 nucleocapsid proteins) from the human, bat, murine, bovine, rat, rabbit, equine, hedgehog species belonging to five subgenuses of the betacoronavirus, viz., Embecovirus , Sarbecovirus , Merbecovirus , Hibecovirus , and Nobecovirus .…”

Section: Computation Approaches and Online Databases: Scope For The Pre-validationsmentioning

confidence: 99%

Next-Generation Bioinformatics Approaches and Resources for Coronavirus Vaccine Discovery and Development—A Perspective Review

et al. 2021

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COVID-19 is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To fight this pandemic, which has caused a massive death toll around the globe, researchers are putting efforts into developing an effective vaccine against the pathogen. As genome sequencing projects for several coronavirus strains have been completed, a detailed investigation of the functions of the proteins and their 3D structures has gained increasing attention. These high throughput data are a valuable resource for accelerating the emerging field of immuno-informatics, which is primarily aimed toward the identification of potential antigenic epitopes in viral proteins that can be targeted for the development of a vaccine construct eliciting a high immune response. Bioinformatics platforms and various computational tools and databases are also essential for the identification of promising vaccine targets making the best use of genomic resources, for further experimental validation. The present review focuses on the various stages of the vaccine development process and the vaccines available for COVID-19. Additionally, recent advances in genomic platforms and publicly available bioinformatics resources in coronavirus vaccine discovery together with related immunoinformatics databases and advances in technology are discussed.

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DBCOVP: A database of coronavirus virulent glycoproteins

Cited by 21 publications

References 41 publications

COVID-19 Vaccines: Computational tools and Development

COVID-19 Vaccines: Computational tools and Development

Graphene, Carbon Nanotube and Plasmonic Nanosensors for Detection of Viral Pathogens: Opportunities for Rapid Testing in Pandemics like COVID-19

Next-Generation Bioinformatics Approaches and Resources for Coronavirus Vaccine Discovery and Development—A Perspective Review

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