Quantitative and qualitative analysis of type II antifreeze protein structure and function

Some cold water marine fishes avoid cellular damage because of freezing by expressing antifreeze proteins (AFPs) that bind to ice and inhibit its grow th; one such protein is the globular type III AFP from eel pout. Despite se veral studies, the mechanism of ice binding remains unclear because of the difficulty in modeling the AFP-ice interaction. To further explore the mech anism, we have determined the x-ray crystallographic structure of 10 type I II AFP mutants and combined that information with 7 previously determined s tructures to mainly analyze specific AFP-ice interactions such as hydrogen bonds. Quantitative assessment of binding was performed using a neural netw ork with properties of the structure as input and predicted antifreeze acti vity as output. Using the cross-validation method, a correlation coefficien t of 0.60 was obtained between measured and predicted activity, indicating successful learning and good predictive power. A large loss in the predicti ve power of the neural network occurred after properties related to the hyd rophobic surface were left out, suggesting that van der Waal's interactions make a significant contribution to ice binding. By combining the analysis of the neural network with antifreeze activity and x-ray crystallographic s tructures of the mutants, we extend the existing ice-binding model to a two step process: 1) probing of the surface for the correct ice-binding plane by hydrogen-bonding side chains and 2) attractive van der Waal's interactio ns between the other residues of the ice-binding surface and the ice, which increases the strength of the protein-ice interaction.