Daisy: An integrated repeat protein curation service

TL;DR

Daisy is a web service that streamlines the identification, classification, and curation of protein tandem repeats by integrating multiple databases and algorithms, thereby accelerating research in repeat protein analysis.

Contribution

It introduces an integrated platform combining databases and algorithms for repeat protein curation, enhancing efficiency and accuracy over manual methods.

Findings

Supports PDB and AlphaFold entries for repeat identification

Uses HMM library searches for sequence classification

Accelerates repeat unit detection with integrated tools

Abstract

Tandem repeats in proteins identification, classification and curation is a complex process that requires manual processing from experts, processing power and time. There are recent and relevant advances applying machine learning for protein structure prediction and repeat classification that are useful for this process. However, no service contemplates required databases and software to supplement researching on repeat proteins. In this publication we present Daisy, an integrated repeat protein curation web service. This service can process Protein Data Bank (PDB) and the AlphaFold Database entries for tandem repeats identification. In addition, it uses an algorithm to search a sequence against a library of Pfam hidden Markov model (HMM). Repeat classifications are associated with the identified families through RepeatsDB. This prediction is considered for enhancing the ReUPred algorithm execution and hastening the repeat units identification process. The service can also operate every associated PDB and AlphaFold structure with a UniProt proteome registry. Availability: The Daisy web service is freely accessible at daisy.bioinformatica.org.