Characterization of Protein Foldon Physical Energy Landscapes
Board Location: #50
Discipline: Physics
Subcategory: Physics (not Nanoscience)
Session: 2
Rachel Gilbert - Texas Southern University
Co-Author(s): Hana Jaafari
Natural proteins quickly and reliably fold into energetically minimized structures. Foldons, however, are protein segments that can independently fold into stable local structures and appear in folding intermediates. We believe the folding process can be accelerated by protein segments stably folding in parallel while leaving the overall protein minimally frustrated. Diseases like Alzheimer’s stem from protein misfolding, understanding components that assist in the reliability and efficiency of protein folding can give insights for the prevention of such diseases.The following methods were used for protein foldon identification. •Calculate AWSEM energies of protein foldon beginning from the N-terminus to index j and its globular states • Calculate AWSEM energies of remainder of protein beginning from index j to the C-terminus and its globular states • Calculate average of Θ values of protein foldon and remaining protein structure • Determine foldon end index j with maximum average Θ value • Identify next foldon (start index=j) using same procedureIn reviewing the results from graphs comparing foldons of different protein families, related proteins Leghemoglobin and Myoglobin show similar conservation in their exon junctions. Furthermore, foldon and exon junctions appear to overlap with one another, though additional foldons in other proteins must be identified to more conclusively determine their relationship. To further this study, the evolutionary pressure experienced by foldons to fold should also be examined by calculating foldons’ DCA energies.
Funder Acknowledgement(s): ORBITS (NSF-PHY-2019745) and NOTS (NSF-CNS-1338099)
Faculty Advisor: Hana Jaafari, hana.k.jaafari@rice.edu
Role: Analysis of protein folding through the characterization of protein foldon physical energy landscapes.Modified code and executed protein folding simulations using Python (Jupyter Notebook) and Linux.