Abstract
Anti-arboviral peptides are biomolecules capable of interfering with key stages of the arboviral lifecycle. We present a dataset compiling 270 peptides composed of standard amino acids with reported activity against arboviruses, along with their lengths, sequences, target specificities, peptide entry mechanisms, and interaction mechanisms. The dataset was structured to support the training of machine learning models designed to identify anti-arboviral peptides. Therefore, it facilitates the development and validation of predictive tools against arboviruses. As a carefully assembled and expert-reviewed resource, this dataset aims to serve as a reference standard for evaluating new prediction models or comparing them with automatically compiled peptide datasets. This resource provides a comprehensive overview of the antiviral mechanisms currently being explored and can serve as a foundation for designing next-generation peptides targeting arboviral infections.