Integrated Phytochemical, Computational, and QbD Approaches in theDevelopment of Jatropha Curcas Ethosomal Gel for Antifungal Therapy

Introduction: In order to create an ethosomal gel based on Jatropha curcas that has improved antifungal activity, this study combines Quality by Design (QbD), computational modeling, and phytochemical profiling. Method: GC–MS analysis of the methanolic seed extract identified key bioactives, including NHexadecanoic acid, 9,12-Octadecadienoic acid (Z, Z), and (Z)6, (Z)9-Pentadecadien-1-ol, which exhibited strong binding affinities toward fungal CYP51 (PDB ID: 5TZ1) in molecular docking and favorable ADMET properties. Results: A Central Composite Design was used to optimize the formulation parameters (lipid concentration, ethanol content, and sonication time), resulting in ethosomes with a particle size of 154.1 ± 0.81 nm, a zeta potential of −29.6 ± 0.21 mV, and a high entrapment efficiency. Discussion: The optimized gel demonstrated sustained drug release (97 ± 0.68%) following Higuchi kinetics and superior in vitro antifungal activity against Candida albicans, Microsporum canis, and M. audouinii compared to the crude extract gel. Conclusion: Overall, the findings establish J. curcas ethosomal gel as a promising topical antifungal formulation and demonstrate the value of integrating QbD and in silico tools in herbal drug development.