Composition, thermodynamics, and morphology: A multi-scale computational approach for the design of self-assembling peptides

Thurston, Bryce A.

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https://hdl.handle.net/2142/102446 Copy

Description

Title

Composition, thermodynamics, and morphology: A multi-scale computational approach for the design of self-assembling peptides

Author(s)

Thurston, Bryce A.

Issue Date

2018-11-29

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

Ferguson, Andrew

Doctoral Committee Chair(s)

Song, Jun

Committee Member(s)

• Cheng, Jianjun
• Cooper, Lance

Department of Study

Physics

Discipline

Physics

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(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.

Graduation Semester

2018-12

Type of Resource

text

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http://hdl.handle.net/2142/102446

Copyright and License Information

Copyright 2018 Bryce A. Thurston

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