Chemical profiling of seaweeds of the Arabian Gulf by liquid chromatography-mass spectrometry and in-silico screening against MPOX

This work conducted metabolic profiling on nine brown, one red, and two green algal species collected from different sampling sites of Kuwait's coastal waters in the Arabian Gulf. Crude extracts of freeze-dried seaweed samples were prepared using solvents of different polarities by solvent extraction, namely, methanol and dichloromethane, and analysed by liquid chromatography-mass spectrometry for metabolite identification. The Principal Component Analysis scores scatter plot grouped the extracts of Codium papillatum, Chondria sp., Iyengaria stellata, Feldmannia indica, Padina boergesenii, Colpomenia sinuosa, Dictyota dichotoma, Sargassum aquifolium, S. asperifolium and S. ilicifolium together, suggesting their similar chemical profiles. However, S. ilicifolium var. acaraeocarpum and C. vagabunda were separated from the remainder of seaweed taxa by unique metabolite features. As expectable, species-specific differences in chemical profiles were observed in different seaweeds. Dereplication studies were employed to identify differential metabolites and to search for their previously reported bioactivities. The study led to the tentative identification of 22 metabolites using various annotation tools contained within the Global Natural Products Social Molecular Networking platform, most importantly MolNetEnhancer. The most prevalent chemical class annotations were "terpenoids"and "lipids and lipid-like molecules". The potential modes of action of the metabolites in certain diseases were further studied using computational approaches such as molecular docking and ligand-based pharmacophore generation. This constitutes the first metabolomics study of seaweeds from the Arabian Gulf.