RECENT ADVANCES IN STRUCTURE AND FUNCTION OF FOOD PROTEINS - QSAR APPROACH

QSAR (quantitative structure-activity relationship), widely used in ch emistry with hydrophobic, electronic, and steric parameters as structu ral factors, was found to be appropriate for use with food proteins, d espite the difficulty, due to the complexity in macromolecular structu re, in defining the steric terms. Emulsifying ability was closely rela ted to hydrophobicity, and incorporation of solubility to hydrophobici ty as factors improved the R2 of regression analysis. Foaming activity required both hydrophobicity and other factors pertaining to the adso rption of proteins at the interface in order to obtain adequate foam l amella strength. Hydrophobicity as well as other factors relating to t he intermolecular interactions, for example, Ca and SH are involved in thermally induced gelation. For breadmaking, although no extensive QS AR work had been carried out, the important function of high molecular glutenin subunits was confirmed, and, notably, the critical function of hydrophobicity in breadmaking also was demonstrated. PLS (partial l east-squares regression) and neural networks classify more correctly t han other multivariate techniques, thereby yielding higher r2 values i n modeling and prediction. However, multiple regression analysis and P CR (principal component regression) also were found to be effective fo r modeling because the information useful in elucidating the mechanism of protein function could be readily obtained. A characteristic prope rty of unsupervised learning techniques, especially PCS (principal com ponent similarity analysis), in identifying influential factors in the function mechanisms was demonstrated.