MOTIVATION: Antimicrobial peptides (AMPs) are promising molecules to treat infectious diseases caused by multi-drug resistance pathogens, some types of cancer, and other conditions. Computer-aided strategies are efficient tools for the high-throughput screening of AMPs.
RESULTS: This report highlights StarPep Toolbox, an open-source and user-friendly software to study the bioactive chemical space of AMPs using complex network-based representations, clustering, and similarity-searching models. The novelty of this research lies in the combination of network science and similarity-searching techniques, distinguishing it from conventional methods based on machine learning and other computational approaches. The network-based representation of the AMP chemical space presents promising opportunities for peptide drug repurposing, development, and optimization. This approach could serve as a baseline for the discovery of a new generation of therapeutics peptides.
AVAILABILITY AND IMPLEMENTATION: All underlying code and installation files are accessible through GitHub (https://github.com/Grupo-Medicina-Molecular-y-Traslacional/StarPep) under the Apache 2.0 license.
HuellaProfundice en los temas de investigación de 'StarPep Toolbox: an open-source software to assist chemical space analysis of bioactive peptides and their functions using complex networks'. En conjunto forman una huella única.
Prensa/Medios de comunicación
Universidad San Francisco de Quito (USFQ) Reports Findings in Bioinformatics (StarPep Toolbox: An Open-Source Software to Assist Chemical Space Analysis of Bioactive Peptides and Their Functions using Complex Networks)
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