Date of Award
5-10-2026
Date Published
June 2026
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Biomedical and Chemical Engineering
Advisor(s)
Shikha Nangia
Second Advisor
Atanu Acharya
Keywords
molecular dynamics;multiscale modeling;palmitoylation;post-translational modifications;protein hydropathy
Subject Categories
Biochemistry, Biophysics, and Structural Biology | Biophysics | Life Sciences
Abstract
Understanding how molecular-level interactions govern the behavior of biomolecules and soft matter systems is essential for advancing both fundamental science and practical applications. The work integrates atomistic simulations, coarse-grained (CG) modeling, and method development to enable scalable and design-oriented insights. In Part I, we quantify how post-translational modifications (PTMs) alter protein physicochemical properties. By extending the Protocol for Assigning a Residue’s Character on Hydropathy (PARCH) scale, we systematically evaluate the local hydropathy changes induced by phosphorylation, acetylation, and methylation, revealing distinct and modification-specific trends. We further investigate S-palmitoylation in membrane proteins: claudins, using CG simulations in phase-separated bilayers. The results show that palmitoylation enhances affinity for ordered lipid domains and that the depth of the palmitoyl chain governs lipid regulation, providing a mechanistic link between modification geometry and membrane organization. In Part II, we develop and apply CG modeling approaches across diverse systems. I extend and demonstrate the robustness of the PARCH scale across multiple water models, supporting its broader applicability. I then use CG simulations to study polymer-grafted catalysts, showing how polymer architecture controls solvation and transport near active sites to improve reaction selectivity. Finally, we establish a modular CG platform for antimicrobial peptoids that enables automated model construction, high-throughput simulation, and sequence-dependent analysis of self-assembly. Overall, this work delivers quantitative tools and scalable modeling frameworks that connect molecular design to functional outcomes, supporting predictive design in biomolecular engineering, catalysis, and advanced materials development.
Access
Open Access
Recommended Citation
Qin, Xuyang, "Investigation of Biomolecules and Soft Matter via Multiscale Modeling" (2026). Dissertations - ALL. 2307.
https://surface.syr.edu/etd/2307
