Atomistic and Coarse-Grained Investigation of Membrane-Protein Interactions

Gaining mechanistic insights into membrane-protein interactions is vital for compre-hending cellular processes and health disorders. In this work, we pursued two sets ofstudies to elucidate such interactions. First, we used atomistic studies to investigate in-creased binding affinity of a membrane-remodeling protein (epsin) to membranes subjectedto high tension. We performed umbrella sampling calculations to provide the first quantita-tive evidence that tension energetically promotes the insertion of a transmembrane helicaldomain of epsin. Next, we embarked on an ambitious journey to build a coarse-grainedMonte Carlo computational framework to simulate membrane-protein interactions at themesoscale. This framework utilizes building blocks such as body, bonded and non-bondedcomponents and discretized differential geometry operators necessary to create interactionsof customizable molecules with a highly versatile membrane. We provide a concise overviewof the key notions underlying this framework. Next, we demonstrate the unique abilitiesof this framework via several toy problems inspired from biological systems. We simulated,to the best of our knowledge, the highest genus membrane structure in the literature tilldate. This structure resembles a nuclear envelope and consists of two adjacent sphericalmembranes fused at hundreds of sites. Next, we demonstrated the formation of coexistentdomains on an ellipsoidal vesicle generated by heterogeneous lipid composition. Next, wedemonstrated the assembly/disassembly of a tri-legged protein (called clathrin) on a vesi-cle and the ability of the polymerized protein to form cargo-carrying vesicles. Finally, weshow extreme tubulation caused by aggregation of banana-shaped proteins on a sphericalmembrane. These test cases confirm the potential of our new framework to model complexmembrane geometries and membrane-protein interactions.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Mechanical Engineering

Grantor

University of Houston

Year dc:date.issued

2021

Author dc:creator

• Osorio Merea, Carlos A

Advisor dc:contributor.advisor

• Agrawal, Ashutosh

Committee members dc:contributor.committeemember

• Lele, Tanmay P.
• Joshi, Shailendra P.
• Liu, Dong
• Baxevanis, Theocharis

• mebrane Monte Carlo

Statement dc:rights

• The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/10657/9402

OAI identifier oai:identifier

oai:uh-ir.tdl.org:10657/9402