Computational studies of membrane proteins: Structure, function and dynamics

Lam, Kin

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https://hdl.handle.net/2142/108144 Copy

Description

Title

Computational studies of membrane proteins: Structure, function and dynamics

Author(s)

Lam, Kin

Issue Date

2020-05-05

Director of Research (if dissertation) or Advisor (if thesis)

Tajkhorshid, Emad

Doctoral Committee Chair(s)

Aksimentiev, Aleksei

Committee Member(s)

• Grosman, Claudio F
• Shukla, Diwakar

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

2020-08-26T23:58:34Z

Keyword(s)

• Ion channel
• Sodium channel
• Potassium channel
• Chloride channel
• Molecular dynamics
• Simulations
• Free energy calculation
• Machine learning

Abstract

Ion channels are membrane proteins that regulate the flow of ions across the cell membrane. These channels open in response to changes in electrostatic potential across the cell membrane or binding of small molecules to the channels and allow the passage of specific ions through their conduction pore. In particular, K+, Na+, and Cl− channels play important roles in the generation of electrical signals, known as action potentials, which propagate through the membrane of excitable cells. Despite decades of study on the function of these ion channels, detailed molecular mechanisms of the gating and ion selectivity remain elusive. The main aim of this dissertation is to employ molecular dynamics simulations to investigate the structure and function of ion channels, including the gating mechanism in voltage-gated potassium and sodium channels, as well as the ion selectivity in chloride channels. First, the mechanical coupling within the voltage-sensing S4 helix in potassium channels is studied using steered molecular dynamics and network analysis. The hydrogen bonds near the α- to 310-helix transition region in the S4 helix are of vital importance to force translation during voltage gating. Next, anion selectivity in chloride channels is investigated by extensive free energy calculations on the single- and double-ion permeation through the conducting pore. The free energy profiles for Cl−, Br−, and NO3− ions suggest that the interactions between the ions and backbone amides near the ion-binding sites determine the selectivity. Permeation of Br− and NO3− ions are energetically penalized by disrupting the hydration of backbone amides due to their bigger size. The simulated double-ion permeation process has revealed that the comparable size of Cl− and water molecule facilitates a knock-on passage mechanism, which discriminates Cl− from other bulkier anions. The third study concerns the molecular modeling of the structure of a sodium channel. Guided by cross-linking experiment data, a homology model of a eukaryotic sodium channel was constructed in the inactivated state, which has not been resolved in any previous studies. Free energy calculations on the inactivation process have identified a novel pore-blocking mechanism by the domain III S6 helix of domain III of the channel. Apart from molecular simulation, mathematical modeling of the gating kinetics for both the potassium and sodium channels establishes the functional linkage from the channels’ precise gating kinetics to the initiation of action potentials in neurons. In addition, this dissertation presents two side projects. The first side project concerns the effects of Cy3 and Cy5 fluorophores on membrane protein dynamics. An extensive collection of simulations on various membrane proteins provides a detailed quantitative description of the fluorophore-lipid interactions and infer the perturbation on the structure and dynamics of the labeled proteins. The second side project describes a method utilizing an artificial neural network in performing dimensionality reduction for analysis of molecular dynamics simulations. In this dissertation, a collection of computational methods have been applied to study membrane proteins and ion channels and to provide molecular insights to explain experimental observations in these systems.

Graduation Semester

2020-05

Type of Resource

Thesis

Permalink

http://hdl.handle.net/2142/108144

Copyright and License Information

Copyright 2020 Kin Lam

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