Computational approaches to Spirulina platensis growth with urea-derived nanonutrients: thermodynamic properties, energetic profiles, molecular docking and POM analysis of pharmacophore sites

Abstract

This research investigated the influence of urea-derived nanonutrients on Spirulina culture, focusing on improving algal biomass productivity through computational approaches and thermodynamic and energetic analyses. These approaches integrated advanced numerical modeling tools, including the evaluation of symmetry groups, physicochemical parameters, and molecular descriptors, coupled with statistical analyses such as linear regression, Principal Component Analysis (PCA), and Principal Component Regression (PCR). Four derivative compounds were studied: urea, methylurea, tetramethylurea, and cyanoguanidine. The results demonstrated that incorporating these derivatives into the culture medium significantly increased Spirulina productivity. Cyanoguanidine particularly stood out, improving biomass productivity by more than 25% compared to the reference medium. This performance was attributed to its superior electronic properties, such as high electronegativity and strong electron affinity, which promote optimized nitrogen assimilation. In comparison, methylurea and tetramethylurea, although showing some efficiency, showed slightly lower productivity due to their more complex structure, requiring additional enzymatic steps. Molecular docking simulations confirmed that cyanoguanidine possessed the highest affinity for the target protein, thus improving nitrogen assimilation efficiency. This work highlights the importance of selecting suitable urea derivatives to maximize biomass production, while opening promising prospects for the development of more sustainable and economically viable algal bioprocesses at large scale. POM analysis confirmed the crucial role of metal transport to plant, via in situ formation of bidentate-metal complexes of cyanoguanidine metabolites.