Computational investigation of membrane-associated phenomena and viral proteins

Gorgun Ozgulbas, Defne

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https://hdl.handle.net/2142/122246 Copy

Description

Title

Computational investigation of membrane-associated phenomena and viral proteins

Author(s)

Gorgun Ozgulbas, Defne

Issue Date

2023-11-30

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

Tajkhorshid, Emad

Doctoral Committee Chair(s)

Tajkhorshid, Emad

Committee Member(s)

• Shukla, Diwakar
• Pogorelov, Taras
• Wu, Nicholas C

Department of Study

School of Molecular & Cell Bio

Discipline

Biophysics & Quant Biology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• molecular dynamics simulations
• viral systems
• lipid-protein interactions

Abstract

Interactions between proteins and biological lipid membranes are essential to unravel the mysteries of numerous biological functions and processes. These interactions are pivotal in health and disease, yet are often complex and challenging to study due to their dynamic and elusive nature. This dissertation presents several projects, leveraging computer simulations to dive deep into the intricate machinery of biomolecules, aiming to reveal the atomic movements between proteins and membranes and uncover insights that could lead to the development of targeted treatments and therapies. Firstly, I examined a peripheral membrane protein, mD4-PFO, that acts as a cholesterol sensor, uncovering the mechanism of detecting varying levels of cholesterol in cell membranes through spontaneous membrane binding simulations and free energy calculations. These insights are beneficial for understanding cellular responses to cholesterol changes, with implications for conditions related to cholesterol imbalance in lipid bilayers. Using a similar approach, in response to the pandemic, our exploration extended to the SARS-CoV-2 virus’s fusion peptide, a critical player in the virus’s ability to infiltrate human cells. We uncovered how this protein interacts with human cell membranes, insights that could be instrumental in blocking the virus’s entry into cells. The replication process of the SARS-CoV-2 virus was another focus area. Therefore, we developed an innovative workflow that bridges the gap between multi-scale simulations using AI methods and revealed the complex mechanism of proofreading of the replication machinery of the virus. These findings can bridge existing knowledge gaps and steer the development of targeted COVID-19 treatments. Another virus that historically caused a pandemic is influenza, still posing a major health issue globally. Here, using an array of advanced simulation technologies, we have developed a high-resolution structural model of full-length, Fab-bound HA in a native viral membrane to characterize key interactions that govern the binding affinity between the antibody and the viral membrane. The developed model provides a structural framework for the rational design and development of more effective therapeutic antibodies. Finally, to aid in these explorations, I introduce "Ring Piercing Resolver," a user-friendly VMD plugin designed to resolve systemic errors such as atomic clashes or tails piercing aromatic rings in the computational models and enhance the reliability of such complex simulations.

Graduation Semester

2023-12

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/122246

Copyright and License Information

Copyright 2023 Defne Gorgun Ozgulbas

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