RESUMEN
Predicting the interfacial properties of peptides is important for replacing oil-derived surfactants in cosmetics, oil, and agricultural applications. This work validated experimentally the estimations of surface tension at the critical micelle concentration (STCMC) of six peptides performed through a random forest (RF) model in a previous contribution. In silico interfacial tensions of the peptides were obtained in the system decane-water, and dilational experiments were applied to elucidate the foaming potential. The RF model accurately classified the peptides into high and low potential to reduce the STCMC. The simulations at the decane-water interface correctly identified peptides with high, intermediate, and low interfacial properties, and the dilational rheology allowed the estimation of the possible potential of three peptides to produce foams. This study sets the basis for identifying surface-active peptides, but future work is necessary to improve the estimations and the correlation between dilational properties and foam stabilization.