Determining Monomeric Polyglutamine Structure through FRET, Molecular Dynamics, and Q-learning Alfred Chung (UofM), Michael McPhail (MSU), Karis Stevenson (MIT) Dr. M.A. Zohdy (ECE Department OU), Dr. J. Finke (Chem Department OU) . Circular Dichroism Spectra (Ref.). Q-learning. Discussion.
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Determining Monomeric Polyglutamine Structure through FRET,
Molecular Dynamics, and Q-learning
Alfred Chung (UofM), Michael McPhail (MSU), Karis Stevenson (MIT)
Dr. M.A. Zohdy (ECE Department OU), Dr. J. Finke (Chem Department OU)
Circular Dichroism Spectra (Ref.)
32.8 ± 1.9 Å
The end-to-end distances obtained through molecular simulations with both Parm99SB and the Finke models were found to correspond with the distance determined from FRET experiments. Although the Parm99SB force field is widely used as the gold standard for molecular simulations, we found that Parm99SB erroneously predicted a predominately alpha-helical peptide, against the CD experimental data. The Finke Model accurately determined the end-to-end distance as well as matching the results found through triplet state quenching experiments.
The novel application of Q-Learning proved useful by reducing the time required for a simulation. Varying parameters within the model can be compared with distance distributions to quickly see effects.
30.9 ± 1.5 Å
42.7 ± 10.5 Å
34.1 ± 1.5 Å
Many neurodegenerative disorders are derived from a common class of misfolded proteins which contain an extended polyglutamine tract, implicated in the formation of toxic aggregates and oligomers in neurons. Although much research has been focused on the aggregates themselves, the tertiary structure and dynamics of the monomeric polyglutamine tract has not been well studied.The goal of this project was to investigate the structure of the monomeric polyglutamine peptide (K2Q16K2) by integrating in-vitro experiments, in-silico simulations, and a computer reinforcement learning algorithm. The three techniques were used to determine end-to-end distance of the polyglutamine peptide.
Our findings create a framework for future researchers to use our polyglutamine model to investigate misfolding events and develop future therapeutics. Future studies will investigate the structural features of oligomeric and aggregated forms of the polyglutamine by building upon the three techniques used in this project.
Q learning Distance Distribution
"This work was performed during the SIBHI program at Oakland University funded by NSF and NIH under the BBSI program, grant number 0552707."