Computational Study on Structures and Aggregations of Amelogenin under Various Conditions
EMSL Project ID
60278
Abstract
We propose to use EMSL supercomputing resources to explore primary, secondary, tertiary, and quaternary structures of amelogenin proteins under various conditions and gain a molecular level understanding on how structural changes of amelogenin proteins direct the formation of materials found in enamel. Deep learning-based structure prediction tools enabled us to explore the possible secondary, tertiary, and quaternary structures of the full-length amelogenin and LRAP, which are a good starting point for this study. After careful validations of the predicted structures, we plan to carry out extensive force-field based classical molecular dynamics (MD) simulations to refine the predicted monomeric and oligomeric amelogenin structures in aqueous solutions and on mineral surfaces. We will also elucidate how excess ions, pH, and mutations can impact the structures of full-length amelogenin and its variants. This proposed research can fill the knowledge gaps of understanding the amelogenin structure and aggregation mechanism, which directly influence controlling the microscopic, and ultimately macroscopic, features of enamel and this critical understanding may shed light on mechanisms for nature-informed repair or regeneration strategies for tooth enamel.
Project Details
Project type
Limited Scope
Start Date
2022-02-01
End Date
2022-04-22
Status
Closed
Released Data Link
Team
Principal Investigator
Co-Investigator(s)