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Title:Composition, thermodynamics, and morphology: A multi-scale computational approach for the design of self-assembling peptides
Author(s):Thurston, Bryce A.
Director of Research:Ferguson, Andrew
Doctoral Committee Chair(s):Song, Jun
Doctoral Committee Member(s):Cheng, Jianjun; Cooper, Lance
Department / Program:Physics
Discipline:Physics
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Self-Assembly
Molecular Dynamics
Peptide
QSAR/QSPR
Abstract:Peptide self-assembly has generated significant interest as a means for the bottom-up fabrication of highly tunable biocompatible nanoaggregates. Individual peptides can be synthesized to include non-natural π-conjugated subunits, endowing assembled aggregates with a range of optical and electronic properties that render them useful in applications as biocompatible organic electronics. The immense number of possible peptides, however, causes the exhaustive traversal of sequence space to be intractable. This massive composition space lends itself toward the use of computer simulation and data science tools to understand molecular aggregation and guide experimental synthesis and design. In this dissertation, I present work employing a hierarchy of molecular modeling techniques to identify self-assembling peptides with specific photophysical properties by probing thermodynamic and structural characteristics of peptide aggregation. We employ classical molecular dynamics simulation to probe the key molecular forces governing the morphology and free energy of oligomerization, time dependent density functional theory to predict photophysical properties as a function of aggregate morphology, and data-driven quantitative structure property models to perform high-throughput virtual screening of chemical space to identify promising peptide chemistries. This work establishes a multi-scale framework for the principled computational design of self-assembling π-conjugated peptides with engineered photophysical properties.
Issue Date:2018-11-29
Type:Thesis
URI:http://hdl.handle.net/2142/102446
Rights Information:Copyright 2018 Bryce A. Thurston
Date Available in IDEALS:2019-02-06
Date Deposited:2018-12


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