SIREs 3.0, an improved RNA prediction tool for iron-responsive elements

Abstract

Iron-responsive elements (IREs) are cis-acting regulatory RNA motifs that bind to iron regulatory proteins (IRP1 and IRP2), playing an essential role in the post-transcriptional regulation of genes involved in iron metabolism. Disruptions in this IRP/IRE regulatory system have been linked to several human diseases. SIREs (searching for IREs) is a web-server tool designed to predict IREs in nucleotide sequences. Here, we present SIREs 3.0 webserver, an improved new version built on a Flask-based framework, replacing the previous Perl backend to improve interconnectivity with other services. This upgrade introduces three novel input methods—batch, transcript, and gene modes—to cover researchers’ needs, from large-scale analysis to single-gene queries. By integrating with NCBI and Ensembl APIs, SIREs 3.0 fetches genomic data to improve predictions with novel features, such as the location of the IREs in the transcript. Other novelties include novel IRE motifs based on in vivo verified data, broadening the scope of IRE detection. The scoring system has been refined with empirical data and enhanced graphical representations of predicted IREs have been added to the output. The interface is now more responsive and accessible across all devices.