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Updated: Jan 28, 2026

Assays for the Identification of Novel Antivirals against Bluetongue Virus
Published on: October 11, 2013
AntiVPP 1.0: A portable tool for prediction of antiviral peptides
Jorge Félix Beltrán Lissabet1, Lisandra Herrera Belén1, Jorge G Farias1
1Universidad de La Frontera, Department of Chemical Engineering, Faculty of Engineering and Science, Temuco, Chile.
Abstract:
Viruses are worldwide pathogens with a high impact on the human population. Despite the constant efforts to fight viral infections, there is a need to discover and design new drug candidates. Antiviral peptides are molecules with confirmed activity and constitute excellent alternatives for the treatment of viral infections. In the present study, we developed AntiVPP 1.0, an accurate bioinformatic tool that uses the Random Forest algorithm for antiviral peptide predictions. The model of AntiVPP 1.0 for antiviral peptide predictions uses several features of 1088 peptides for training and validation. During the validation of the model we achieved the TPR = 0.87, SPC = 0.97, ACC = 0.93 and MCC = 0.87 performance measures, which were indicative of a robust model. AntiVPP 1.0 is a fast, accurate and intuitive software focused on the assessment of antiviral peptides candidates. AntiVPP 1.0 is available at https://github.com/bio-coding/AntiVPP.
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