University of Illinois Urbana-Champaign

Computational modeling and simulation of ligand-gated ion channels

Shahoei, Rezvan

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SHAHOEI-DISSERTATION-2020.pdf

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https://hdl.handle.net/2142/108238

Description

Title
Computational modeling and simulation of ligand-gated ion channels
Author(s)
Shahoei, Rezvan
Issue Date
2020-04-02
Director of Research (if dissertation) or Advisor (if thesis)
Tajkhorshid, Emad
Doctoral Committee Chair(s)
Aksimentiev, Aleksei
Committee Member(s)
  • Grosman, Claudio
  • Stack, John
Department of Study
Physics
Discipline
Physics
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2020-08-27T00:49:51Z
Keyword(s)
  • Molecular Dynamics Simulations
  • pentameric Ligand-Gated Ion Channels
Abstract
The pentameric ligand-gated ion channel (pLGIC) superfamily, from bacteria to the brain, convert chemical signals into electric signals. These proteins are composed of two distinct domains; the extracellular domain (ECD), where the chemical compounds (ligands) bind, and the transmembrane domain (TMD), which contains the ion-permeation pore. With the ligand-binding sites and the ion channel gate almost 50 Å apart, an allosteric conformational transition in these proteins has been proposed as the underlying mechanism of signal transduction. Members of the pLGIC superfamily, have intrigued researchers from multiple scientific disciplines for more than a century. The muscle nicotinic acetylcholine receptor (nAChR), a member of the pLGIC superfamily, was the first ion channel to be extracted and thus became a model system not only for pLGICs but for all ligand-gated ion channels. Thanks to decades of electrophysiology experiments along with pharmacological, biochemical, and structural studies, enormous progress has been made in understanding the function and structure of pLGICs. However, relatively high-resolution structures of a small number of pLGICs have been obtained only in the last decade or two. The availability of these structures allows for asking and, hopefully, answering questions that were deemed impossible in the past. Only now, for example, molecular dynamics (MD) simulations can be utilized to probe the interactions between these proteins and different molecules at the atomic level. Another promising area for MD simulations is to investigate if and how the membrane physicochemical properties affect these proteins in different functional states. Moreover, enhanced sampling techniques can be used to characterize the conformational transitions between different functional states in these proteins. In this work, after a brief introduction (Chapter 1), two studies --- each focused on a different mammalian pLGIC --- are discussed. The first project investigates the interaction between menthol, a small lipophilic molecule, and the human alpha4beta2 nAChR --- the most abundant nAChR type in the brain. Various computational methodologies were used to study menthol's interaction with and partitioning in organic phases and lipid bilayers representing cellular membranes (Chapter 2). Once menthol's behavior in the membrane was characterized, its interaction with a membrane-embedded human alpha4beta2 nAChR was studied (Chapter 3). The second project (Chapter 4) focuses on the structure of the human glycine receptor (GlyR), bound to full and partial agonists, in different functional states. In a collaborative work, MD simulations were used along with cryo-electron microscopy and electrophysiology to determine the structural models for the desensitized and open state GlyR bound to the full agonist glycine. More importantly, the structure of the primed/flipped state of GlyR bound to partial agonists, taurine and gamma-aminobutyric acid, were determined. I will focus on the computational part of the joint effort, where MD simulations were employed to establish the stability of different ion conducting states of the receptor in two membrane environments.
Graduation Semester
2020-05
Type of Resource
Thesis
Permalink
http://hdl.handle.net/2142/108238
Copyright and License Information
Copyright 2020 Rezvan Shahoei

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