<p dir="ltr">The impacts of processing on protein structure are of broad interest to the food science community including ingredient producers, product developers, and researchers. Processing and isolation steps induce protein structural changes which occur due to temperature based, shear, and chemical inputs, leading to denatured protein with different functionalities. However, exploration of the protein folding landscape as a way to intentionally modify protein conformation is not widely understood in food science. This particularly applies to cold denaturation, which is the structural changes in protein as the result of low temperature treatments.</p><p dir="ltr">This work has two primary goals. The first was to develop understanding of protein conformations resulting from cold denaturation and its implications for food textural properties. Pea protein was selected for this work since it is a source of plant-based protein that has recently grown in popularity and contains many hydrophobic amino acids that would make is susceptible to cold denaturation. Cold denaturation was studied using physicochemical techniques including differential scanning calorimetry, Fourier transform infrared spectroscopy, zeta potential, fluorescence spectroscopy, dynamic light scattering, and rheology. These techniques are used to characterize untreated pea protein, and proteins that have been modified using different combinations of ethanol, shear forces, acidic conditions, extrusion, and temperatures below 0°C. Significant physicochemical differences are found as the result of low temperatures, driven by an increase in surface hydrophobicity and electrostatic interactions. These differences led to protein gelation through hydrophobic forces, changing the nature of gels. Similarly, the increase in protein hydrophobicity leads to more stable emulsions from these products and unique fatty extrudates.</p><p dir="ltr">A second aim of this work developed bioinformatic models to interpret physiochemical data and provide mechanistic understanding of the process, as well as predict functional properties based on protein models. Strong correlations are found for the zeta potential, secondary structure, hydrogen bonds, and surface hydrophobicity. These models are used to convert data into physicochemical energy and used to provide reasonable estimates of mechanical properties of pea protein in extrusion, gelation, and emulsification. Together, this work shows that cold denaturation may be a useful tool for food product developers creating fatty and creamy textures. It also suggests bioinformatic modeling as a tool to estimate protein functionality, which could lead to tremendous time savings in process and product design.</p>