Tuning the entropic spring: A predictive modeling approach to dictating order in polymer conjugated peptide assemblies

Project: Research project

Project Details


Living cells possess extraordinary capabilities in maintaining chemical balance in
extreme environments, which are facilitated by exceptional chemical and biological
sensing and selective transport capabilities that far surpass what can currently be
achieved with engineered systems. Advances in polymer chemistry and physics, protein
engineering, and synthetic biology, have created new pathways to transfer biological
capabilities to man-made systems, specifically by enabling the possibility to recreate
nature’s complexity by generating polymeric materials that incorporate nature’s building
blocks (i.e., proteins) in their native functional state. By combining the hierarchical
structure and chemical functionality of proteins with the stability and processability of
polymers, peptide-polymer conjugates may potentially lead to materials of both high
level of ordering and complexity simultaneously. However, the materials science of
peptide-polymer conjugates is still at infancy because a predictive model that links
molecular design parameters to hierarchical organization and functionality remains
elusive for these hybrid systems. The most distinguishing aspect of this work is based
on our original hypothesis that mechanical forces arising from the entropic penalty of
conjugated chains can be used as a means to generate theoretically predictable ordered
structures consisting of functional peptides, specifically helix bundles. Recognizing this
capability as a new frontier in bioinspired material design, control of the spatial
organization of functional peptides conjugated with polymers is the foundational
concept upon which bioinspired synthetic strategies will be built. In pursuit of this
capability, this research aims to establish a rational, predictive modeling approach to
the design of entropic forces in alpha-helix/polyethylene glycol (helix-PEG)
conjugates to achieve hierarchical self-assembling systems with predictable order.
The two aims that will be pursued in light of this overarching objective are:
 Aim 1 - Investigate conformational dynamics of helix-PEG conjugates
 Aim 2- Establish a predictive model to dictate ordering of helix-PEG bundles
Through a combined molecular theory/simulation approach validated by
experimental characterizations, this work will contribute significantly to the current
understanding of how entropic spring forces, generated by polymer conjugation, control
conformational dynamics and hierarchical stability of helix-PEG bundles. The proposed
efforts are foundational in the context of the long-term career objective of the PI, which is
to enable progress towards rapid discovery and design of bioinspired suprabiomolecular
materials by establishing a knowledge base of their physical behavior relevant to
applications beyond the biological milieu. Blending stability analysis concepts from
structural mechanics with directed self-assembly principles from polymer physics, we
will aim to generate predictable functionalities that are inspired from nature. New
understanding gained from these efforts will delineate a science-based approach to
discovering new forms of biomolecular materials with tailored functionalities that will
potentially overcome bottlenecks in future technologies of relevance to the Navy.
Fundamental insight gained through these studies will accelerate the discovery of
functional polymer-peptide conjugate materials that could potentially mimic biological
capabilities of biosensing, molecular recognition, environmental remediation, selective
transport, mech
Effective start/end date8/1/137/31/17


  • Office of Naval Research (N00014-13-1-0760)


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.