Yang, Darian T
(2024)
Invisible Protein States and How to View Them: Integrating 19F NMR and Weighted Ensemble Simulations.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
Protein conformational dynamics are a keystone to understanding biology at the mechanistic level. Traditional methods for studying conformational dynamics are to use NMR spectroscopy and molecular dynamics (MD) simulations. However, many biologically interesting events occur outside of the timescales accessible to conventional MD simulations, and using NMR, many transient states can be sparsely populated, or ensemble averaged, making their resolution recalcitrant to traditional NMR approaches. To resolve these dynamic protein states, both enhanced simulation methods and highly sensitive 19F NMR experiments are needed. In this dissertation, I integrate and further develop computational and experimental methods to fully characterize the conformational ensemble of the HIV-1 capsid protein CTD dimer. In Chapter 1, I motivate the need for a combination of weighted ensemble (WE) path sampling simulations and 19F NMR to resolve the multi-state conformational dynamics of the HIV-1 capsid protein. Chapter 2 describes the development and validation of new force field parameters that allow for simulations of the fluorinated amino acids commonly used in 19F NMR experiments. In Chapter 3, I present a comprehensive study of the structures and dynamics of an "invisible" alternate state of the HIV-1 capsid protein CTD dimer using WE simulations and 19F NMR experiments. A bottleneck for this project was the identification of effective parameters for WE simulations. In Chapter 4, I developed a new algorithm for WE resampling which automates tedious parts of WE simulation parameter selection using concepts from reinforcement learning. Finally, in Chapter 5, I developed a software package for convenient WE data analysis and plotting. Together, the above chapters demonstrate the power of integrating simulations and experiments, as well as the potential of more robust path sampling methods and software for characterizing the conformational ensembles of proteins.
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| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
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| ETD Committee: |
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| Date: |
20 December 2024 |
| Date Type: |
Publication |
| Defense Date: |
26 August 2024 |
| Approval Date: |
20 December 2024 |
| Submission Date: |
3 October 2024 |
| Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
| Number of Pages: |
181 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Dietrich School of Arts and Sciences > Molecular Biophysics and Structural Biology |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
protein conformational dynamics, integrated structural biology, alternate protein states, computational biophysics, HIV-1 capsid protein, 19F NMR, molecular dynamics simulations, weighted ensemble simulations, reinforcement learning, rare-event sampling, path sampling methods, fluorinated amino acids, force field development, conformational ensembles, enhanced sampling methods |
| Date Deposited: |
20 Dec 2024 13:48 |
| Last Modified: |
20 Dec 2024 13:48 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/46993 |
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