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spelling ndltd-CALTECH-oai-thesis.library.caltech.edu-100012021-01-17T05:01:41Z https://thesis.library.caltech.edu/10001/ First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics Dong, Sijia S. <p>This thesis focuses on simulating large molecular systems within and beyond the Born-Oppenheimer framework from first principles. Two approaches have been developed for very different but important applications.</p> <p>The first one is a hybrid method based on classical force fields that predicts the high-energy ensemble of three-dimensional structures of a class of proteins critical in human physiology: the G protein-coupled receptors (GPCRs). GPCRs' functions rely on their activation marked by a series of conformational changes related to binding of certain ligands, but the short of experimental structures has hampered the study of their activation mechanism and drug discovery. Our method, combining homology modeling, hierarchical sampling, and nanosecond-scale molecular dynamics, is one of the very few computational methods that can predict their active-state conformations and is one of the most computationally inexpensive. It enables the conformational landscape and the first quantitative energy landscape of GPCR activation to be efficiently mapped out. </p> <p>This method, named ActiveGEnSeMBLE, allows the inactive- and active-state conformations of GPCRs without an experimental structure to be systematically predicted. We have validated the method with one of the most well-studied GPCRs, human &#946;<sub>2</sub> adrenergic receptor (h&#946;<sub>2</sub>AR), and applied the method on a GPCR without an experimental structure, human somatostatin receptor 5 (hSSTR5). Insights on GPCR activation as well as structure prediction methods are discussed.</p> <p>The second one is a semiclassical approach for large-scale nonadiabatic dynamics of condensed systems in extreme conditions, termed Gaussian Hartree Approximated Quantum Mechanics (GHA-QM). Many nonadiabatic processes related to important applications (e.g. renewable energy) happen in large systems, but existing excited state dynamics methods are too computationally demanding for their long timescale simulations. GHA-QM is based on the electron force field (eFF) framework where we model electrons as Gaussian wavepackets and nuclei as classical point charges, and obtain a simplified solution to the time-dependent Schrödinger equation as the equation of motion. We employ a force field philosophy approximating the total energy as a sum of electronic kinetic energies, electrostatic energies and a Pauli correction, which corrects for the lack of explicit antisymmetry in the wavefunctions. New designs of the Pauli potential and preliminary results on hydrogen systems are discussed. With the new development, we hope to improve the accuracy and range of applications of eFF to simulate the nonadiabatic dynamics of hundreds of thousands of electrons on nanosecond timescale.</p> 2017 Thesis NonPeerReviewed application/pdf en other https://thesis.library.caltech.edu/10001/53/Dong_Sijia_Dec2016_thesis.pdf application/pdf en other https://thesis.library.caltech.edu/10001/20/Dong_Sijia_Dec2016_thesis_IntroGPCR.pdf application/pdf en other https://thesis.library.caltech.edu/10001/59/Dong_Sijia_Dec2016_thesis_Chapter5GHAQM.pdf application/pdf en other https://thesis.library.caltech.edu/10001/27/Dong_Sijia_Dec2016_thesis_AppendixD.pdf application/zip en other https://thesis.library.caltech.edu/10001/66/Dong_Sijia_Dec2016_thesis_GPCR_supp_PDB.zip Dong, Sijia S. (2017) First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z98C9T8D. https://resolver.caltech.edu/CaltechTHESIS:01032017-003321706 <https://resolver.caltech.edu/CaltechTHESIS:01032017-003321706> https://resolver.caltech.edu/CaltechTHESIS:01032017-003321706 CaltechTHESIS:01032017-003321706 10.7907/Z98C9T8D
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description <p>This thesis focuses on simulating large molecular systems within and beyond the Born-Oppenheimer framework from first principles. Two approaches have been developed for very different but important applications.</p> <p>The first one is a hybrid method based on classical force fields that predicts the high-energy ensemble of three-dimensional structures of a class of proteins critical in human physiology: the G protein-coupled receptors (GPCRs). GPCRs' functions rely on their activation marked by a series of conformational changes related to binding of certain ligands, but the short of experimental structures has hampered the study of their activation mechanism and drug discovery. Our method, combining homology modeling, hierarchical sampling, and nanosecond-scale molecular dynamics, is one of the very few computational methods that can predict their active-state conformations and is one of the most computationally inexpensive. It enables the conformational landscape and the first quantitative energy landscape of GPCR activation to be efficiently mapped out. </p> <p>This method, named ActiveGEnSeMBLE, allows the inactive- and active-state conformations of GPCRs without an experimental structure to be systematically predicted. We have validated the method with one of the most well-studied GPCRs, human &#946;<sub>2</sub> adrenergic receptor (h&#946;<sub>2</sub>AR), and applied the method on a GPCR without an experimental structure, human somatostatin receptor 5 (hSSTR5). Insights on GPCR activation as well as structure prediction methods are discussed.</p> <p>The second one is a semiclassical approach for large-scale nonadiabatic dynamics of condensed systems in extreme conditions, termed Gaussian Hartree Approximated Quantum Mechanics (GHA-QM). Many nonadiabatic processes related to important applications (e.g. renewable energy) happen in large systems, but existing excited state dynamics methods are too computationally demanding for their long timescale simulations. GHA-QM is based on the electron force field (eFF) framework where we model electrons as Gaussian wavepackets and nuclei as classical point charges, and obtain a simplified solution to the time-dependent Schrödinger equation as the equation of motion. We employ a force field philosophy approximating the total energy as a sum of electronic kinetic energies, electrostatic energies and a Pauli correction, which corrects for the lack of explicit antisymmetry in the wavefunctions. New designs of the Pauli potential and preliminary results on hydrogen systems are discussed. With the new development, we hope to improve the accuracy and range of applications of eFF to simulate the nonadiabatic dynamics of hundreds of thousands of electrons on nanosecond timescale.</p>
author Dong, Sijia S.
spellingShingle Dong, Sijia S.
First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics
author_facet Dong, Sijia S.
author_sort Dong, Sijia S.
title First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics
title_short First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics
title_full First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics
title_fullStr First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics
title_full_unstemmed First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics
title_sort first-principles-based simulations for g protein-coupled receptor activation and for large-scale nonadiabatic electron dynamics
publishDate 2017
url https://thesis.library.caltech.edu/10001/53/Dong_Sijia_Dec2016_thesis.pdf
https://thesis.library.caltech.edu/10001/20/Dong_Sijia_Dec2016_thesis_IntroGPCR.pdf
https://thesis.library.caltech.edu/10001/59/Dong_Sijia_Dec2016_thesis_Chapter5GHAQM.pdf
https://thesis.library.caltech.edu/10001/27/Dong_Sijia_Dec2016_thesis_AppendixD.pdf
https://thesis.library.caltech.edu/10001/66/Dong_Sijia_Dec2016_thesis_GPCR_supp_PDB.zip
Dong, Sijia S. (2017) First-Principles-Based Simulations for G Protein-Coupled Receptor Activation and for Large-Scale Nonadiabatic Electron Dynamics. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z98C9T8D. https://resolver.caltech.edu/CaltechTHESIS:01032017-003321706 <https://resolver.caltech.edu/CaltechTHESIS:01032017-003321706>
work_keys_str_mv AT dongsijias firstprinciplesbasedsimulationsforgproteincoupledreceptoractivationandforlargescalenonadiabaticelectrondynamics
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