Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins

abstract: In a typical living cell, millions to billions of proteins—nanomachines that fluctuate and cycle among many conformational states—convert available free energy into mechanochemical work. A fundamental goal of biophysics is to ascertain how 3D protein structures encode specific functions, s...

Full description

Bibliographic Details
Other Authors: Seyler, Sean Lee (Author)
Format: Doctoral Thesis
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/2286/R.I.46316
id ndltd-asu.edu-item-46316
record_format oai_dc
spelling ndltd-asu.edu-item-463162018-06-22T03:09:07Z Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins abstract: In a typical living cell, millions to billions of proteins—nanomachines that fluctuate and cycle among many conformational states—convert available free energy into mechanochemical work. A fundamental goal of biophysics is to ascertain how 3D protein structures encode specific functions, such as catalyzing chemical reactions or transporting nutrients into a cell. Protein dynamics span femtosecond timescales (i.e., covalent bond oscillations) to large conformational transition timescales in, and beyond, the millisecond regime (e.g., glucose transport across a phospholipid bilayer). Actual transition events are fast but rare, occurring orders of magnitude faster than typical metastable equilibrium waiting times. Equilibrium molecular dynamics (EqMD) can capture atomistic detail and solute-solvent interactions, but even microseconds of sampling attainable nowadays still falls orders of magnitude short of transition timescales, especially for large systems, rendering observations of such "rare events" difficult or effectively impossible. Advanced path-sampling methods exploit reduced physical models or biasing to produce plausible transitions while balancing accuracy and efficiency, but quantifying their accuracy relative to other numerical and experimental data has been challenging. Indeed, new horizons in elucidating protein function necessitate that present methodologies be revised to more seamlessly and quantitatively integrate a spectrum of methods, both numerical and experimental. In this dissertation, experimental and computational methods are put into perspective using the enzyme adenylate kinase (AdK) as an illustrative example. We introduce Path Similarity Analysis (PSA)—an integrative computational framework developed to quantify transition path similarity. PSA not only reliably distinguished AdK transitions by the originating method, but also traced pathway differences between two methods back to charge-charge interactions (neglected by the stereochemical model, but not the all-atom force field) in several conserved salt bridges. Cryo-electron microscopy maps of the transporter Bor1p are directly incorporated into EqMD simulations using MD flexible fitting to produce viable structural models and infer a plausible transport mechanism. Conforming to the theme of integration, a short compendium of an exploratory project—developing a hybrid atomistic-continuum method—is presented, including initial results and a novel fluctuating hydrodynamics model and corresponding numerical code. Dissertation/Thesis Seyler, Sean Lee (Author) Beckstein, Oliver (Advisor) Chamberlin, Ralph (Committee member) Matyushov, Dmitry (Committee member) Thorpe, Michael F (Committee member) Vaiana, Sara (Committee member) Arizona State University (Publisher) Biophysics Computational physics Fluid mechanics adenylate kinase conformational transitions enhanced sampling fluctuating hydrodynamics molecular dynamics path similarity analysis eng 245 pages Doctoral Dissertation Physics 2017 Doctoral Dissertation http://hdl.handle.net/2286/R.I.46316 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2017
collection NDLTD
language English
format Doctoral Thesis
sources NDLTD
topic Biophysics
Computational physics
Fluid mechanics
adenylate kinase
conformational transitions
enhanced sampling
fluctuating hydrodynamics
molecular dynamics
path similarity analysis
spellingShingle Biophysics
Computational physics
Fluid mechanics
adenylate kinase
conformational transitions
enhanced sampling
fluctuating hydrodynamics
molecular dynamics
path similarity analysis
Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins
description abstract: In a typical living cell, millions to billions of proteins—nanomachines that fluctuate and cycle among many conformational states—convert available free energy into mechanochemical work. A fundamental goal of biophysics is to ascertain how 3D protein structures encode specific functions, such as catalyzing chemical reactions or transporting nutrients into a cell. Protein dynamics span femtosecond timescales (i.e., covalent bond oscillations) to large conformational transition timescales in, and beyond, the millisecond regime (e.g., glucose transport across a phospholipid bilayer). Actual transition events are fast but rare, occurring orders of magnitude faster than typical metastable equilibrium waiting times. Equilibrium molecular dynamics (EqMD) can capture atomistic detail and solute-solvent interactions, but even microseconds of sampling attainable nowadays still falls orders of magnitude short of transition timescales, especially for large systems, rendering observations of such "rare events" difficult or effectively impossible. Advanced path-sampling methods exploit reduced physical models or biasing to produce plausible transitions while balancing accuracy and efficiency, but quantifying their accuracy relative to other numerical and experimental data has been challenging. Indeed, new horizons in elucidating protein function necessitate that present methodologies be revised to more seamlessly and quantitatively integrate a spectrum of methods, both numerical and experimental. In this dissertation, experimental and computational methods are put into perspective using the enzyme adenylate kinase (AdK) as an illustrative example. We introduce Path Similarity Analysis (PSA)—an integrative computational framework developed to quantify transition path similarity. PSA not only reliably distinguished AdK transitions by the originating method, but also traced pathway differences between two methods back to charge-charge interactions (neglected by the stereochemical model, but not the all-atom force field) in several conserved salt bridges. Cryo-electron microscopy maps of the transporter Bor1p are directly incorporated into EqMD simulations using MD flexible fitting to produce viable structural models and infer a plausible transport mechanism. Conforming to the theme of integration, a short compendium of an exploratory project—developing a hybrid atomistic-continuum method—is presented, including initial results and a novel fluctuating hydrodynamics model and corresponding numerical code. === Dissertation/Thesis === Doctoral Dissertation Physics 2017
author2 Seyler, Sean Lee (Author)
author_facet Seyler, Sean Lee (Author)
title Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins
title_short Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins
title_full Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins
title_fullStr Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins
title_full_unstemmed Computational Approaches to Simulation and Analysis of Large Conformational Transitions in Proteins
title_sort computational approaches to simulation and analysis of large conformational transitions in proteins
publishDate 2017
url http://hdl.handle.net/2286/R.I.46316
_version_ 1718701654399778816