Computational study of the structure and function of membrane transport proteins

Shekhar, Mrinal

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Description

Title

Computational study of the structure and function of membrane transport proteins

Author(s)

Shekhar, Mrinal

Issue Date

2019-02-15

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

Tajkhorshid, Emad

Doctoral Committee Chair(s)

Tajkhorshid, Emad

Committee Member(s)

• Grosman, Claudio
• Jin, Hong
• Shukla, Diwakar

Department of Study

School of Molecular & Cell Bio

Discipline

Biophysics & Computnl Biology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

Molecular Dynamics

Abstract

Transport of the nutrients across the cell membrane is regulated by membrane transport proteins which selectively and efficiently transports materials across the membrane. In the present work I focus on the family of membrane transporters the so called sugar porters in both their mammalian and bacterial forms. In the first work I describe the entire thermodynamic cycle of the GLUT1, a glucose transporter from the sugar porter family by employing non-equilibrium MD simulation and determining the free energy landscape associated with the so called IF–OF transition. Employing the information from the free energy calculations and equilibrium MD simulations from the members of the sugar porter family I present a unified mechanism of transport for the uniporter class of transporters. A second class of transporters namely symporters that couple the electrochemical gradient of a co transported ion to perform the uphill transport of the substrate was also studied. Using the H+-coupled Xylose transporter XylE a close homologue of GLUTs, as a prototypical symporter the allosteric effects of the binding of H+ and the subsequent effect on the substrate dynamics is studied. Furthermore, I explored the role of lipids in regulating the conformational equilibrium in XylE. In combination with HD-MS experiments we show that the nature of lipid protein interactions determined the stability of a particular conformational state of XylE. Continuing on the theme of lipid-protein interaction, I present my work on the P2X receptor, a non selective cation channel, where we present a unique ion permeation mechanism where the ion permeation pathway is formed by both protein and the lipid molecules. In recent times, Cryo-EM has emerged as a tool for structural biologists to obtain structures of macro molecules which were previously difficult to elucidate using traditional methods. Employing MD simulations particularly Molecular Dynamics Flexible Fitting (MDFF) in its resolution exchange flavor ReMDFF, I present the results of the 2015-2016 Cryo-EM Model challenge. In this challenge that I participated, we employed the aforementioned methodologies to forward the field of structure determination from the density maps at 3-5 °A resolution. The results presented are focused on providing structures for the proteins TRPV1 & -galactosidase. However, all these approaches, including our popular Molecular Dynamics Flexible Fitting (MDFF), and its various extensions work under the conventional molecular replacement paradigm, whereby any initial search model is morphed to satiate the data-imposed constraints. As a natural consequence, quality of the determined model remains heavily biased by choices of the initial model. Here, we deliver a novel modeling pipeline, MMR (MAINMAST-MELD-ReMDFF) that interactively combines minimum spanning tree-based backbone tracing tool (MAINMAST), Bayesian-likelihood based protein-folding methodology (MELD), and a resolution exchange-based fitting protocol (ReMDFF). Starting from only sequence information, the algorithm places C atoms into the density, fits a random coil to this C trace, generates protein secondary structures on-the-fly, and exhaustively samples the backbone and side chain geometries to deliver a re-fined model. Overcoming limitations of traditional approaches, the need for an initial model or homology information is completely subsided, and de-novo modeling is now made feasible even at low resolutions.

Graduation Semester

2019-05

Type of Resource

text

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Copyright and License Information

Copyright 2019 Mrinal Shekhar

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