Secondary structural studies of bovine caseins: temperature dependence of β-casein structure as analyzed by circular dichroism and FTIR spectroscopy and correlation with micellization

Abstract

To obtain a molecular basis for the similarities and dissimilarities in the functional, chemical, and biochemical properties between β-casein and the other caseins, three-dimensional models have been presented. Secondary structural prediction algorithms and molecular modeling techniques were used to predict β-casein structure. The secondary structure of bovine β-casein was re-examined using Fourier transform infrared and circular dichroism spectroscopies to test these predictions. Both methods predict a range of secondary structures for β-casein (28–32% turns, 32–34% extended) at 25°C. These elements were highly stable from 5 to 70°C as viewed by circular dichroism. More flexible conformational elements, tentatively identified as loops, helix and short segments of polyproline II, were influenced by temperature, increasing with elevated temperatures. Another view is that as temperature decreases, these elements are lost (cold denaturation). Several distinct transitions were observed by circular dichroism at 10, 33 and 41°C, and another transition, extrapolated to occur at 78°C. Calculations from analytical ultracentrifugation indicate that the 10, 33 and 41°C transitions occur primarily in the monomeric form of the protein. As β-casein polymers are formed, and increase in size, the transitions at higher temperature may reflect changes in the more flexible conformational elements as they adjust to changes in surface charge during polymer formation. The transition at 10°C may represent an actual general conformational change or cold denaturation. Over the range of temperatures studied, the sheet and turn areas remain relatively constant, perhaps forming a supporting hydrophobic core for the monomers within the micelle-like polymer. This interpretation is in accord with the known properties of β-casein, and those predicted from molecular modeling.