Pariset: A primary dataset for therapeutic algal peptides focus on antihypertensive, antioxidative, antibacterial, antihyperglycemic, and anticancer activities

Background Algal peptides have diverse applications in medicine and industry; however, no integrated study focused on dataset preparation of algae-derived peptides. This study was conducted to curate sequence-determined peptides extracted from algae to launch a dedicated dataset. Results In this context, an advanced search was performed in PubMed using terms related to algae and peptides. Relevant articles were curated, analyzed, and features, including peptide name, source, amino acid sequence, molecular weight, origin (natural, synthetic, or in silico designed), half-maximal inhibitory concentration, half-maximal effective concentration, minimum inhibitory concentration, algal taxonomy, and biological activity, were curated and discussed. Consequently, the dataset Pariset was developed as a comprehensive reference for algal peptides. Pariset contains 115 unique peptide sequences derived from 14 algal genera and collected from 17 articles indexed in PubMed. The highest number of peptides was derived from Pyropia pseudolinearis . Among the curated peptides, 24 showed no specific biological activity, while the remaining peptides exhibited antihypertensive (n = 54), antioxidative (n = 29), antibacterial (n = 3), antihyperglycemic (n = 4), and anticancer (n = 4) activities. Conclusions The establishment of Pariset aims to facilitate research on therapeutic algal peptides by providing an organized and accessible dataset. This resource is expected to support advancements in algal biotechnology and enable the development of novel peptide-based therapeutics by leveraging existing data on algae-derived peptides.