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Molecular Factors of Ice Growth Inhibition for Hyperactive and Globular Antifreeze Proteins: Insights from Molecular Dynamics Simulation.

Prasun PalRahul AichSandipan ChakrabortyBiman Jana
Published in: Langmuir : the ACS journal of surfaces and colloids (2022)
The molecular mechanism behind the ice growth inhibition by antifreeze proteins (AFPs) is yet to be understood completely. Also, what physical parameters differentiate between the AFP and non-AFP are largely unknown. Thus, to get an atomistic overview of the differential antifreeze activities of different classes of AFPs, we have studied ice growth from different ice surfaces in the presence of a moderately active globular type III AFP and a hyperactive spruce budworm (sbw) AFP. Results are compared with the observations of ice growth simulations in the presence of topologically similar non-AFPs using all-atom molecular dynamics simulations. Simulation data suggest that the ice surface coverage is a critical factor in ice growth inhibition. Due to the presence of an ice binding surface (IBS), AFPs form a high affinity complex with ice, accompanied by a transition of hydration water around the IBS from clathrate-like to ice-like. Several residues around the periphery of the IBS anchor the AFP to the curved ice surface mediated by multiple strong hydrogen bonds, stabilizing the complex immensely. In the high surface coverage regime, the slow unbinding kinetics dominates over the ice growth kinetics and thus facilitates the ice growth inhibition. Due to the non-availability of a proper IBS, non-AFPs form a low-affinity complex with the growing ice surface. As a result, the non-AFPs are continuously repelled by the surface. If the concentration of AFPs is low, then the effective surface coverage is reduced significantly. In this low surface coverage regime, AFPs can also behave like impurities and are engulfed by the growing ice crystal.
Keyphrases
  • molecular dynamics simulations
  • healthcare
  • molecular docking
  • mental health
  • cystic fibrosis
  • type iii
  • transcription factor
  • data analysis