The distribution, spatial clustering, and density of trapdoor spiders in two California coastal dune ecosystems

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  The distribution, spatial clustering, and density of trapdoor spiders in two California coastal dune ecosystems Abstract Coastal dune ecosystems support endemic trapdoor spiders, yet population data for these species are limited. We conducted the first coastal dune trapdoor spider population estimation surveys at Moss Landing State Beach (California) and for Aptostichus stephencolberti Bond 2008 at Sunset State Beach using randomly selected 1m 2 quadrats across ~26,000 m 2 per site. Burrow densities were similar between sites (Sunset: 0.287 burrows/m 2 ; Moss: 0.453 burrows/m 2 ), yielding estimated population sizes of ~35,206 and ~30,959 individuals, respectively. However, spatial analyses revealed contrasting patterns of burrow distribution. At Sunset State Beach, burrow presence was strongly associated with vegetation and occurred closer to plants, despite vegetation being randomly distributed. In contrast, no vegetation–burrow association was detected at Moss Landing, alth...

Venom-Derived Enzyme Inhibitors as Anticancer Agents: Structure–Activity Relationships, Molecular Targets and Mechanistic Insights

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Venom-Derived Enzyme Inhibitors as Anticancer Agents: Structure–Activity Relationships, Molecular Targets and Mechanistic Insights

Abstract

Animal venoms represent an extraordinary, yet largely untapped, biochemical reservoir for oncological drug discovery. This review provides a comprehensive analysis of venom-derived enzyme inhibitors as emerging anticancer agents, emphasizing their chemical diversity, structure–activity relationships (SAR), molecular targets, and mechanistic pathways. Venom-derived peptides and proteins exhibit exceptional binding affinity and structural rigidity, characteristics frequently enforced by conserved disulfide networks. This specific architecture allows them to selectively modulate critical cancer-associated enzymes, including matrix metalloproteinases, phospholipases A2, serine proteases, and kinases. Inhibiting these highly specific targets successfully disrupts tumour angiogenesis, extracellular matrix remodelling, and metastatic dissemination, while simultaneously inducing apoptosis through unique pathways such as reactive oxygen species generation. Modern computational approaches, encompassing deep learning algorithms, molecular docking, and molecular dynamics simulations, are substantially accelerating and transforming the discovery pipeline by rapidly mapping intricate peptide–receptor interactions and guiding rational drug design. Translating these potent molecules into clinical therapeutics remains heavily challenged by pharmacokinetic instability, rapid proteolytic degradation, and systemic toxicity. The integration of computationally optimized scaffolds with advanced targeted delivery platforms, such as nanocarriers and liposomal encapsulation, offers a highly viable strategy to overcome these barriers, ultimately paving the way for next-generation, venom-inspired cancer therapies.

Ogundele, A. V., Nongthombam, G. S., Nwagu, A. D., Silva, H. H., & Fabiyi, O. A. (2026). Venom-Derived Enzyme Inhibitors as Anticancer Agents: Structure–Activity Relationships, Molecular Targets and Mechanistic Insights. Molecules, 31(13), 2398. https://doi.org/10.3390/molecules31132398