(507b) Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure | AIChE

(507b) Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure


Walker, C. - Presenter, University of Colorado Boulder
Fobe, T., University of Colorado Boulder
Shirts, M., University of Colorado Boulder
Meek, G., University of Colorado Boulder
Foldamers, oligomeric molecules which form secondary structure in solution due to noncovalent interactions amongst nonadjacent residues, show great promise for a multitude of applications ranging from protein-like catalysts to nanostructured materials to therapeutics. While many studies have elucidated and characterized novel backbone and sidechain chemistries leading to secondary structure formation, further understanding of the basic design principles of molecular folding is still needed to achieve the control over tertiary structure required in many applications.1 In addition, the design of non-biological hetero-oligomers, which inhabit a space of vast physicochemical diversity, has been limited by a lack of experimental data and challenges with synthesis. Coarse-grained molecular modeling is a valuable tool for searching broad chemical spaces and uncovering general features of molecular models leading to cooperative formation of secondary structure.

We developed a Python-based molecular simulation framework (cg_openmm)2 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 (REMD) with the OpenMM software package and features a suite of post-processing thermodynamic and structural analysis tools. Native structures are identified using structure-based clustering, and the Multistate Bennett Acceptance Ratio (MBAR)3 reweighting technique is applied to REMD energies to generate smooth curves of heat capacity, free energy, enthalpy, and entropy of folding, and native contact fraction expectation as functions of temperature.

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 sidechain bead. By scanning both nonbonded and bonded force field parameter space 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. Finally, we discuss insight obtained from cg_openmm into the design of transitions between multiple different secondary structures.


(1) Cheng, R. P. Beyond de Novo Protein Design - De Novo Design of Non-Natural Folded Oligomers. Current Opinion in Structural Biology. 2004, pp 512–520.

(2) cg_openmm is available on GitHub at https://github.com/shirtsgroup/cg_openmm

(3) Shirts, M. R.; Chodera, J. D. Statistically Optimal Analysis of Samples from Multiple Equilibrium States. J. Chem. Phys. 2008, 129 (12).