Foldamers are a newly emerging class of macromolecules made up of a set of diverse non-natural monomer subunits. Similar to proteins, foldamer macromolecules show promise for highly specific, designable materials. Currently, there is a limited collection of structural data for these foldamer macromolecules, making traditional protein-based folding techniques unavailable to these types of molecules. In this work, we propose a hypothesis-based coarse-graining (CG) approach to explore the available secondary structure of general foldamer molecules. To this end, we developed CG PyRosetta, an extension to Rosetta, the widely used protein folding software, to explore the secondary structure available to arbitrary foldamer macromolecules. CG PyRosetta is a generalized version of Rosetta that can fold arbitrary linear backbones, and can, ab initio, identify secondary structure elements in simple CG  models provided a parameter set. Attaching hypotheses to these CG parameters, we develop a set of folding trends observed from the emergent secondary structures present in these models. By applying these folding principles to experimental monomers, we can guide experimental design of new foldamers.  We can use this framework to explore the effects of sidechain size, monomer rigidity and sequence heterogeneity on the formation of helices and other secondary structures.

CG PyRosetta: Coarse-grained conformational search tool for general heteropolymers

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

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