A database of flavivirus RNA structures with a search algorithm for pseudoknots and triple base interactions

Area of Science:

• Virology
• Bioinformatics
• Molecular Biology

Background:

• Flavivirus genus includes significant human pathogens like Zika and dengue viruses.
• Flavivirus RNA genomes possess crucial structures in their 3' untranslated regions (3'UTRs).
• Identifying these 3'UTR structures is challenging due to sequence and topological diversity, hindering research on flavivirus replication and antiviral development.

Purpose of the Study:

• To develop a computational algorithm for identifying structured patterns in RNA sequences, including secondary structures, pseudoknots, and triple base interactions.
• To construct a database of Flavivirus 3'UTR structures using developed structural descriptors and search algorithms.
• To validate the approach by identifying specific RNA domains in insect-specific flaviviruses.

Main Methods:

• Development of a structured pattern search algorithm for RNA sequences.
• Creation of structural descriptors to capture the diversity of conserved Flavivirus 3'UTR structures.
• Construction of the Leiden Flavivirus RNA Structure Database.

Main Results:

• Successfully developed and implemented an algorithm for structured RNA pattern searching.
• Built a comprehensive database of Flavivirus 3'UTR structures.
• Identified exoribonuclease Xrn1-resistant RNA domains in insect-specific flaviviruses, validating the algorithm's effectiveness.

Conclusions:

• The developed algorithm and database provide a valuable resource for flavivirus research.
• This approach facilitates the identification of functionally important RNA structures in Flavivirus 3'UTRs.
• The findings contribute to a better understanding of flavivirus replication and the development of novel antiviral strategies.