Bioprospecting identifies new sources of compounds with actual or potential economic value that come from biodiversity. An analysis was performed regarding bioprospecting purposes in ten genotypes of Sechium spp., through a meta-analysis of 20 information sources considering different variables: five morphological, 19 biochemical, anti-proliferative activity of extracts on five malignant cell lines, and 188 polymorphic bands of amplified fragment length polymorphisms, were used in order to identify the most relevant variables for the design of genetic interbreeding. Significant relationships between morphological and biochemical characters and anti-proliferative activity in cell lines were obtained, with five principal components for principal component analysis (SAS/ETS); variables were identified with a statistical significance (< 0.7 and Pearson values ≥ 0.7), with 80.81% of the accumulation of genetic variation and 110 genetic bands. Thirty-nine (39) variables were recovered using NTSYSpc software where 30 showed a Pearson correlation (> 0.5) and nine variables (< 0.05), Finally, using a cladistics analysis approach highlighted 65 genetic bands, in addition to color of the fruit, presence of thorns, bitter flavor, piriform and oblong shape, and also content of chlorophylls a and b, presence of cucurbitacins, and the IC₅₀ effect of chayote extracts on the four cell lines.

Molecular docking has emerged as a pivotal computational approach in agri-food research, offering a rapid and targeted means to discover bioactive molecules for crop protection and food safety. Its ability to predict and visualize interactions between natural or synthetic compounds and specific biological targets provides valuable opportunities to address urgent agricultural challenges, including climate change and the rise in resistant crop pathogens. By enabling the in silico screening of diverse chemical entities, this technique facilitates the identification of molecules with antimicrobial and antifungal properties, specifically designed to interact with critical enzymatic pathways in plant pathogens. Recent advancements, such as the integration of molecular dynamics simulations and artificial intelligence-enhanced scoring functions, have significantly improved docking accuracy by addressing limitations like protein flexibility and solvent effects. These technological improvements have accelerated the discovery of eco-friendly biopesticides and multifunctional nutraceutical agents. Promising developments include nanoparticle-based delivery systems that enhance the stability and efficacy of bioactive molecules. Despite its potential, molecular docking still faces challenges related to incomplete protein structures, variability in scoring algorithms, and limited experimental validation in agricultural contexts. This work highlights these limitations while outlining current trends and future prospects to guide its effective application in agri-food biotechnology.

The online version contains supplementary material available at 10.1038/s41598-026-45401-8.