Multivariate outputs from the experimental monitoring of biochemical processes are usually difficult to interpret applying methods based on a priori chemical models. Curve resolution methods are model-free procedures, generally known as soft-modeling methods, which obtain the concentration profiles and instrumental responses of each individual species involved in a multivariate monitored process without making any kind of external assumption. Of the curve resolution methods available, the alternating least squares (ALS) is proposed here because of its ability to operate on one or on several matrices. Furthermore, ALS allows the introduction of information related to the internal data structure and to the general features of the concentration profiles and instrumental responses through the input of suitable constraints in the iterative resolution procedure. The ALS potential is tested on several data sets coming from the multivariate spectrometric monitoring of polyuridylic (polyU), polycytidylic (polyC), and polyadenylic (polyA) protonation equilibria in dioxane/water 30% (v/v). Information concerning the evolution of the concentration profiles and the spectra of each individual species involved in the acid-base equilibria, the presence and pattern of polyelectrolyte effects, and the presence of conformational transitions associated or not with the proton uptake process is presented.
De Juan, A., Izquierdo-Ridorsa, A., Tauler, R., Fonrodona, G., & Casassas, E. (1997). A soft-modeling approach to interpret thermodynamic and conformational transitions of polynucleotides. Biophysical Journal, 73(6), 2937–2948. https://doi.org/10.1016/S0006-3495(97)78322-X