Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

CoronaVIR

General information

URL: https://webs.iiitd.edu.in/raghava/coronavir
Full name: Computational Resources on Novel Coronavirus (SARS-CoV-2 or COVID-19)
Description: A Web-Based Platform on Coronavirus Disease-19 to Maintain Predicted Diagnostic, Drug, and Vaccine Candidates
Year founded: 2020
Last update:
Version:
Accessibility:
Accessible
Country/Region: India

Classification & Tag

Data type:
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Indraprastha Institute of Information Technology
Address: Department of Computational Biology, Indraprastha Institute of Information Technology, Okhla Industrial Estate, Phase III, New Delhi 110020, India
City: New Delhi
Province/State:
Country/Region: India
Contact name (PI/Team): Gajendra P.S. Raghava
Contact email (PI/Helpdesk): raghava@iiitd.ac.in

Publications

33136473
A Web-Based Platform on Coronavirus Disease-19 to Maintain Predicted Diagnostic, Drug, and Vaccine Candidates. [PMID: 33136473]
Sumeet Patiyal, Dilraj Kaur, Harpreet Kaur, Neelam Sharma, Anjali Dhall, Sukriti Sahai, Piyush Agrawal, Lubna Maryam, Chakit Arora, Gajendra P S Raghava

A web-based resource CoronaVIR (https://webs.iiitd.edu.in/raghava/coronavir/) has been developed to maintain the predicted and existing information on coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We have integrated multiple modules, including "Genomics," "Diagnosis," "Immunotherapy," and "Drug Designing" to understand the holistic view of this pandemic medical disaster. The genomics module provides genomic information of different strains of this virus to understand genomic level alterations. The diagnosis module includes detailed information on currently-in-use diagnostics tests as well as five novel universal primer sets predicted using tools. The Immunotherapy module provides information on epitope-based potential vaccine candidates (e.g., LQLPQGTTLPKGFYA, VILLNKHIDAYKTFPPTEPKKDKKKK, EITVATSRTLS, GKGQQQQGQTV, SELVIGAVILR) predicted using state-of-the-art software and resources in the field of immune informatics. These epitopes have the potential to activate both adaptive (e.g., B cell and T cell) and innate (e.g., vaccine adjuvants) immune systems as well as suitable for all strains of SARS-CoV-2. Besides, we have also predicted potential candidates for siRNA-based therapy and RNA-based vaccine adjuvants. The drug designing module maintains information about potential drug targets, tertiary structures, and potential drug molecules. These potential drug molecules were identified from FDA-approved drugs using the docking-based approach. We also compiled information from the literature and Internet on potential drugs, repurposing drugs, and monoclonal antibodies. To understand host-virus interaction, we identified cell-penetrating peptides in the virus. In this study, state-of-the-art techniques have been used for predicting the potential candidates for diagnostics and therapeutics.

Monoclon Antib Immunodiagn Immunother. 2020:() | 17 Citations (from Europe PMC, 2025-12-13)

Ranking

All databases:
3075/6895 (55.417%)
Health and medicine:
773/1738 (55.581%)
Gene genome and annotation:
958/2021 (52.647%)
Literature:
274/577 (52.686%)
3075
Total Rank
17
Citations
3.4
z-index

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Record metadata

Created on: 2020-11-08
Curated by:
Yuxin Qin [2023-09-26]
Yuxin Qin [2023-09-14]
Lin Liu [2021-03-24]
Qiang Du [2020-11-24]
Chang Liu [2020-11-08]