Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 6018-6035 |
| Number of pages | 18 |
| Journal | Journal of Chemical Theory and Computation |
| Volume | 17 |
| Issue number | 10 |
| DOIs | |
| State | Published - Oct 12 2021 |
Funding
T.L.F. was in part supported by the U.S. Department of Education’s Graduate Assistance in Areas of National Need (GAANN) fellowship program. This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering (MSE) Division, under award number DE-SC0018651. This work utilized computational resources from the University of Colorado Boulder Research Computing Group, which is supported by the National Science Foundation (awards ACI-1532235 and ACI-1532236), the University of Colorado Boulder, and Colorado State University. This work also used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. Specifically, it used the Bridges system, which is supported by NSF award number ACI-1445606, and the Bridges-2 system, which is supported by NSF ACI-1928147, both at the Pittsburgh Supercomputing Center (PSC). Finally, the authors acknowledge the openmmtools team for useful discussion and help regarding the implementation of the replica exchange simulations, especially John Chodera, Andrea Rizzi, Ana Silviera, and Josh Fass.