Molecular Insight of the Ice Nucleation by Ice Binding\nProtein: A Comparative Study With Ice Nucleating Protein, Antifreeze\nProtein, and Non-Ice-Binding Protein
Ice-binding\nproteins (IBPs) are a special class of proteins that\ncan specifically interact with ice. A subclass of IBPs that can inhibit\nice growth by depressing the freezing point of ice in a noncolligative\nmanner are called antifreeze proteins (AFPs). The other subclass of\nIBPs that can enhance the ice nucleation process are called ice nucleating\nproteins (INPs). In this study, using molecular dynamics simulations,\nwe induced ice formation and further compared the nucleation behaviors\nof AFP, INPs, and non ice binding proteins (NonIBPs). The formation\nof the initial stable ice cluster is found to be closer to the T-X-T\nmotif of INP than that of AFP and it is farthest from the NonIBP.\nThe fraction of ice molecules in the largest cluster is also found\nto be highest for INP. More importantly, the configurations of ice\nclusters formed in different independent runs are found to be strikingly\nsimilar for INP which signifies the crucial role of its ice-binding\nsurface in controlling the process. The configurations of the formed\nice in different independent runs are very dissimilar for both AFP\nand NonIBP. Quantitative analysis revealed that INP exhibits a stronger\npreference for hexagonal ice formation over its cubic counterpart\ncompared to AFP/NonIBP. Between the two model INP structures used\nin this study, the latest model structure predicted by AlphaFold2\nshowed superior ice nucleating abilities than the older INP model.\nSimilar conclusions about the abilities of ice nucleation by these\ndifferent classes of proteins are confirmed by free energy calculation.\nFinally, the ice nucleating ability of the water-organizing motif\nof an INP is demonstrated over its nonwater-organizing motif in a\nsingle structure. Our findings provide clear evidence of INP’s\nability to promote ice nucleation over AFPs and other NonIBPs.
Publication Details
- Journal
- Figshare
- Published
- 2024-12-17
- DOI
- https://doi.org/10.1021/acs.jpcc.4c05443.s001
- Primary Topic
- Soil, Finite Element Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00