Folding Coarse-Grained Oligomer Models with PyRosetta.

Non-biological foldamers are a promising class of macromolecules that share similarities to classical biopolymers such as proteins and nucleic acids. Currently, designing novel foldamers is a non-trivial process, often involving many iterations of trial synthesis and characterization until folded structures are observed. In this work, we aim to tackle these foldamer design challenges using computational modeling techniques. We developed CG PyRosetta, an extension to the popular protein folding python package, PyRosetta, which introduces coarse-grained (CG) residues into PyRosetta, enabling the folding of toy CG foldamer models. Although these models are simplified, they can help explore overarching physical hypotheses about how oligomers can form. Through systematic variation of CG parameters in these models, we can investigate various folding hypotheses at the CG scale to inform the design process of new foldamer chemistries. In this study, we demonstrate CG PyRosetta's ability to identify minimum energy structures with a diverse structural search over a range of simple models, as well as two hypothesis-driven parameter scans investigating the effects of side-chain size and internal backbone angle on secondary structures. We are able to identify several types of secondary structures from single- and double-helices to sheet-like and knot-like structures. We show how side-chain size and backbone bond angle both play an important role in the structure and energetics of these toy models. Optimal side-chain sizes promote favorable packing of side chains, while specific backbone bond angles influence the specific helix type found in folded structures.

Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure.

Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1-1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Moreover, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.

Potential Foldamers Based on an ortho-Terphenyl Amino Acid.

We describe the synthesis and characterization of a new class of oligomers built from a terphenyl-based amino acid. These oligomeric amides are of interest because the adoption of specific conformations could potentially be driven by the coordinated formation of inter-residue hydrogen bonds and aromatic interactions. Although high-resolution structural data have proven inaccessible, circular dichroism and nuclear magnetic resonance studies suggest that the new oligomers fold concomitantly with discrete self-association in chloroform.

Cys.sqlite: A Structured-Information Approach to the Comprehensive Analysis of Cysteine Disulfide Bonds in the Protein Databank.

Cysteine is a multifaceted amino acid that is central to the structure and function of many proteins. A disulfide bond formed between two cysteines restrains protein conformations through the strong covalent bond and torsions about the bond that prefer, energetically, ±90°. In this study, we transform over 30 000 Protein Databank files (PDBx/mmCIFs) into a single file, the SQLite database (Cys.sqlite). The database schema is designed to accommodate the structural information on both oxidized and reduced cysteines and to retain essential protein metadata to establish informational and biological provenance. Cys.sqlite contains over 95 000 peptide chains and 500 000 cysteines (700 000 structural conformers); there are over 265 000 cysteine disulfide bond conformations from structures solved with all available experimental methods. The structural information is analyzed with respect to sequence identity cutoff, the experimental method, and energetics of the disulfide. We find that as the experimental information becomes limiting and the influence of modeling becomes more pronounced, the observed average strain increases artificially. The database and analyses presented here can be used to improve the refinement of biological structures from experiments that are known to contain one or more disulfide bonds.