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VIPERdb v3.0: a structure-based data analytics platform for viral capsids
Daniel Montiel-Garcia1,2, Nelly Santoyo-Rivera2, Phuong Ho1
1Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.
Nucleic Acids Research
|December 14, 2020
Summary
The Virus Particle Explorer database (VIPERdb) now includes advanced analytics tools and the Virus World database (VWdb) with over 181,000 viruses. This update enhances virus structure analysis and data curation for researchers.
Area of Science:
- Virology
- Structural Biology
- Bioinformatics
Background:
- VIPERdb is a long-standing curated repository of virus capsid structures and associated data.
- Continuous improvement over 20 years has led to a comprehensive resource for virus structure analysis.
- The database provides various virus-specific information and analysis tools.
Purpose of the Study:
- To introduce VIPERdb version 3.0, highlighting new data analytics tools and expanded content.
- To enhance virus structure analysis, data curation, and accessibility for the scientific community.
- To integrate a comprehensive virus catalog (VWdb) with existing structural data.
Main Methods:
- Development of new structure-based data analytics tools, including Multiple Structure-based and Sequence Alignment (MSSA).
- Implementation of an anomaly detection application for analyzing and curating structure-derived data.
- Integration of the Virus World database (VWdb) containing approximately 181,000 characterized viruses and their capsid protein sequences.
Main Results:
- VIPERdb v3.0 now houses 931 virus structures from 62 virus families.
- The Virus World database (VWdb) aggregates extensive virus data from ICTVdb and NCBI, linked to known structures.
- New tools enable identification of hot-spot residues and improved data curation within virus families.
Conclusions:
- VIPERdb v3.0 offers enhanced capabilities for virus structure analysis and data exploration.
- The integration of VWdb significantly expands the resource for studying viral diversity.
- A service-oriented data engine and machine learning interface pave the way for future data analytics applications.
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