Animal Venoms as Peptide Libraries for the Discovery of Antiglioblastoma Agents.

Abstract

Glioblastoma is one of the most aggressive and widely recognized types of brain tumors, characterized by significant cellular and molecular diversity and an inherently aggressive nature. The treatment remains highly challenging, with limited effectiveness and persistently low survival rates. For this reason, researchers are continuously expanding the chemical space of anticancer agents by exploring complex sources such as animal venoms and incorporating in silico tools to accelerate discovery. Indeed, venoms serve as libraries of proteins and peptides, providing a rich source of novel chemical structures for glioblastoma therapy. Some review articles have examined the mechanisms by which venom-derived peptides target glioblastoma cell lines; nevertheless, key structural insights and computational analyses remain underexplored. In this era of artificial intelligence (AI) and advancements in in silico approaches, our review documented the antiglioblastoma properties of venom peptides and underscores the value of computational methods in peptide-based drug development. To this end, a comprehensive search was conducted in PubMed, Elsevier, Springer, Lilacs, Google Scholar, and SciELO databases. Furthermore, in silico analyses were conducted to evaluate the anticancer potential, hemolytic activity, toxicity, and blood-brain barrier (BBB) penetrating properties of venom-derived peptides. In total, 26 unique sequences were identified, with their structural properties and mechanisms of cell death comprehensively characterized. The development of peptide-based anticancer drugs remains in its early stages, with minimal advancement toward preclinical evaluation using in vivo models. The advancement of AI models offers opportunities to accelerate peptide discovery. However, our case study revealed divergences among AI-based predictions, as well as discrepancies between computational and experimental findings, underscoring the need for further model refinement and validation through experimental data integration. In summary, venoms remain promising peptide libraries that offer valuable natural molecular templates. These peptides require chemical optimization to enhance their stability and BBB permeability. Such advances could enable selective targeting within the glioblastoma niche and support the development of more effective therapies.