Computational investigations of the structure, function, and evolution of complex membrane systems

Trebesch, Noah

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https://hdl.handle.net/2142/122111 Copy

Description

Title

Computational investigations of the structure, function, and evolution of complex membrane systems

Author(s)

Trebesch, Noah

Issue Date

2023-11-21

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

Tajkhorshid, Emad

Doctoral Committee Chair(s)

Tajkhorshid, Emad

Committee Member(s)

• Luthey-Schulten, Zaida
• Pogorelov, Taras V
• 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)

• cellular membranes
• elevator transporters
• molecular dynamics
• phylogenetics

Abstract

Cellular membranes are a ubiquitous component of the microbiological world, and their basic function is to be impermeable to most substances, allowing cells to separate themselves from their environments and create specialized compartments within themselves. At the same time, substances must have a way of crossing membranes to sustain the processes that support life, and one key class of integral membrane proteins that are responsible for accomplishing this task are transporters. Together, membranes and transporters act respectively as barriers and gatekeepers for entry into and exit from the cell, which puts them in a unique position to impact all aspects of cellular function. Accordingly, perturbations to the proper function of membranes and transporters often result in disease in humans, which gives these systems clear biomedical and basic biological significance that motivates detailed investigation into their function. In our work, we have used two methods from computational structural biology to advance our knowledge of cellular membranes and transporters, the first of which is molecular dynamics (MD) simulations. MD is a physics-based technique designed to simulate the dynamics of molecular systems at atomistic resolution, and we used it to characterize a large-scale conformational transition that takes place in the mechanism of a transporter called LaINDY. Establishing a new MD-based protocol for LaINDY allowed us to generate a stable model of one of its major functional states that has not been observed experimentally, and these simulations have also laid the foundation to characterize the transport mechanism of a related human transporter called NaCT. In another project, we discovered striking structural similarities among transporters that use the so-called “elevator” mechanism, and we were able to obtain a compelling body of evidence that suggested that these transporters were all homologous. In an application of structure-based phylogenetic inference, another method of computational structural biology, we performed pairwise structural comparisons of the elevator transporter structures, and we used them to construct a phylogenetic tree. The phylogenetic tree allows us to quantify and visualize the evolutionary relationships between elevator transporters, and it is also a natural tool for guiding future investigation into the function of all elevator transporters. Finally, in our last project, we have sought to bring the descriptive power of MD to cell-scale membrane systems. Along with their scale, the complex curvature and lipid compositions of cellular membranes pose grand challenges to building MD-ready models of these systems. Meeting these challenges required a significant investment in the development of new modeling approaches, which has ultimately resulted in a tool called xMAS Builder (Experimentally-Derived Membranes of Arbitrary Shape Builder). To demonstrate the capabilities of xMAS Builder, we have generated a model of a large membrane system with a realistically complex curvature and lipid composition, and we have established the stability and quality of the model using a long-term MD simulation.

Graduation Semester

2023-12

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/122111

Copyright and License Information

© 2023 Noah Trebesch

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