Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/16674
Title: Metabolic fingerprinting of photosynthetic carbon-fixing algae: Revealing efficient solvent-based approach for biopharmaceutical discovery
Authors: Kaushik, Anshul
Sangtani, Rimjhim
Bala, Kiran
Keywords: Algae;Biopharmaceuticals;Diabetes;Ergost-7-en-3-ol;Hansen Solubility Parameters;Metabolic Fingerprinting;Acetone;Binding Energy;Binding Sites;Biomolecules;Carbon Dioxide;Diagnosis;Drug Discovery;Ethanol;Free Energy;Metabolism;Metabolites;Molecular Dynamics;Molecular Structure;Solubility;Solvents;Atmospheric Carbon Dioxide;Biopharmaceutical Development;Biopharmaceuticals;Bioproducts;Ergost-7-en-3-ol;Hansen Solubility Parameters;Metabolic Fingerprinting;Selection Based;Solvent Based;Solvent Selection;Algae;Medical Problems
Issue Date: 2025
Publisher: Elsevier B.V.
Citation: Kaushik, A., Sangtani, R., & Bala, K. (2025). Metabolic fingerprinting of photosynthetic carbon-fixing algae: Revealing efficient solvent-based approach for biopharmaceutical discovery. Chemical Engineering Journal, 522. https://doi.org/10.1016/j.cej.2025.167283
Abstract: Photosynthetic carbon-fixing organisms, including algae, assimilate atmospheric carbon dioxide into elemental backbone of sustainable and valuable biomass and bioproducts. Despite their promising potential, they have remained an untapped resource for biopharmaceutical development. Presently, solvent selection based on empirical polarity index or trial and error frequently leads to the exclusion of solvents capable of solubilizing unique metabolites, hampering the discovery of bioactive metabolites. In this study, the impact of solvents selected through Hansen Solubility Parameters (HSPs), namely, ethanol, chloroform, acetone, and a mixed solvent (methanol/chloroform/ethanol
2:6:2), was explored in ten freshwater indigenous microalgae and cyanobacteria species through GC–MS based metabolites fingerprinting. The identified metabolites were screened against diabetes molecular targets, Dipeptidyl peptidase-IV (DPP-IV) and Aldose Reductase, through molecular docking. Further, molecular dynamics (MD) simulations provided insights into the effects of solvation and conformational flexibility on binding free energy. Among the 131 identified metabolites, a core metabolome of 84 metabolites enriched across all solvent systems, and 47 non-overlapping metabolites, including quinic acid, 7-hydroxyflavone, and ergost-7-en-3-ol, were abundant in various solvent combinations. Acetone extraction yielded a distinct cluster from ethanol-extracted species. Further, in-silico screening identified ergost-7-en-3-ol as a promising candidate. It exhibited high binding energy and persistent molecular interactions within the binding site, making it a strong anti-diabetic drug candidate. In conclusion, the implementation of HSPs-based solvent selection, combined with comprehensive metabolic fingerprinting, offers a systematic strategy to enhance discovery from natural sources in pharmaceutical research, paving the way for groundbreaking advancements in the field. © 2025 Elsevier B.V., All rights reserved.
URI: https://dx.doi.org/10.1016/j.cej.2025.167283
https://dspace.iiti.ac.in:8080/jspui/handle/123456789/16674
ISSN: 1385-8947
Type of Material: Journal Article
Appears in Collections:Department of Biosciences and Biomedical Engineering

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