Venom-Derived Enzyme Inhibitors Modulate Key Cancer Pathways, Showing Promise as Anticancer Agents.

Cancer remains a leading cause of mortality, with existing therapies often limited by efficacy, resistance, and systemic toxicity. There's a critical need for novel therapeutic agents that can selectively target tumor-specific pathways with high precision. Animal venoms, an extraordinary biochemical reservoir, offer a unique source of highly potent and selective molecules. These natural compounds, particularly peptides and proteins, possess specific architectures and binding affinities that allow them to modulate critical enzymes involved in tumor progression, metastasis, and angiogenesis, representing a promising avenue for drug discovery.

This comprehensive review synthesized existing literature on venom-derived enzyme inhibitors, analyzing their chemical diversity, structure-activity relationships (SAR), molecular targets, and mechanistic pathways as emerging anticancer agents. It examined how these natural peptides and proteins selectively modulate critical cancer-associated enzymes. The review also explored the transformative role of modern computational approaches, including deep learning algorithms, molecular docking, and molecular dynamics simulations, in accelerating the discovery pipeline and guiding rational drug design for these complex molecules.

Venom-derived peptides and proteins exhibit exceptional binding affinity and structural rigidity, often enforced by conserved disulfide networks, enabling selective modulation of critical cancer-associated enzymes. These targets include matrix metalloproteinases, phospholipases A2, serine proteases, and kinases.

Inhibiting these specific targets successfully disrupts tumour angiogenesis, extracellular matrix remodelling, and metastatic dissemination, while simultaneously inducing apoptosis through unique pathways like reactive oxygen species generation. Modern computational methods, such as deep learning algorithms, molecular docking, and molecular dynamics simulations, are significantly accelerating the discovery process by rapidly mapping intricate peptide-receptor interactions and guiding rational drug design, improving the efficiency of identifying potent candidates.