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Open Access

ARTICLE

In Silico Prioritization of Plant Growth Regulators as Candidate Modulators of Microalgal Lipid Biosynthesis for Biofuel Production

Hanane Oucif1,2,*, Miloud Benaissa1,2, Leila Saddikioui3, Nadia Y. Asfouri3, Meriem F. Meliani1, Zineb Belhamra1,2, Djilali Baghdadi1,2
1 Department of Biological Sciences, Faculty of Natural and Life Sciences, Ahmed Zabana University of Relizane, Relizane, Algeria
2 Laboratory of Environment and Sustainable Development, Ahmed Zabana University of Relizane, Relizane, Algeria
3 Higher School of Biological Sciences of Oran, BP 1042 Saim Mohamed, Cité Emir Abdelkader, Oran, Algeria
* Corresponding Author: Hanane Oucif. Email: email
(This article belongs to the Special Issue: Plant Growth Regulators (PGRs) and Plant Stress)

Phyton-International Journal of Experimental Botany https://doi.org/10.32604/phyton.2026.080926

Received 18 February 2026; Accepted 18 May 2026; Published online 03 June 2026

Abstract

Enhancing lipid productivity in microalgae is a critical goal for advancing sustainable biofuel production. Among emerging strategies, the supplementation of plant growth regulators (PGRs) has gained attention as a potential approach for modulating microalgal metabolism. This in silico study evaluated the predicted binding of sixty-five PGRs from 11 chemical classes to five microalgal enzymes associated with lipid biosynthesis, (FabD, KASII, FabG, FATA, and GPAT) using an integrative computational workflow combining virtual screening, molecular docking, molecular dynamics (MD) simulations, and density functional theory (DFT) calculations. Structure-based screening identified fifty-eight compounds with docking scores below −5.0 kcal/mol, consistent with candidate interactions at catalytically relevant regions. Strigolactones and cytokinins emerged as particularly promising families, with several members showing comparatively strong predicted binding affinities. Five phytohormones (STGA, STG, OROB, ZOG, and DHZMP) were prioritized for detailed analysis. MD simulations over 100 ns supported the persistence of predicted protein-ligand complexes, while DFT descriptors provided complementary electronic characterization of these ligands. Together, these computational results highlight a subset of PGRs as candidate binders of key enzymes in fatty acid and TAG biosynthesis pathways. These hypothesis-generating findings require experimental validation to assess their biological relevance and potential contribution to strategies aimed at improving microalgal lipid productivity for biofuel applications.

Keywords

Lipid; microalgae; plant growth regulator; candidate binders; computational

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