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Van der Waals Perspective on Coarse-Graining: Progress toward Solving Representability and Transferability Problems

Journal

ACCOUNTS OF CHEMICAL RESEARCH
Volume 49, Issue 12, Pages 2832-2840

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.accounts.6b00498

Keywords

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Funding

  1. National Science Foundation (NSF) [MCB-1053970, CHE-1565631]
  2. Alfred P. Sloan Foundation
  3. Camille Dreyfus Teacher-Scholar Award
  4. ACS PRF [52100-ND6]
  5. American Chemical Society
  6. Penn State Materials Computation Center
  7. Direct For Biological Sciences
  8. Div Of Molecular and Cellular Bioscience [1053970] Funding Source: National Science Foundation
  9. Division Of Chemistry
  10. Direct For Mathematical & Physical Scien [1565631] Funding Source: National Science Foundation

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CONSPECTUS: Low-resolution coarse-grained (CG) models provide the necessary efficiency for simulating phenomena that are inaccessible to more detailed models. However, in order to realize their considerable promise, CG models must accurately describe the relevant physical forces and provide useful predictions. By formally integrating out the unnecessary details from an all-atom (AA) model, bottom-up approaches can, at least in principle, quantitatively reproduce the structural and thermodynamic properties of the AA model that are observable at the CG resolution. In practice, though, bottom-up approaches only approximate this exact coarse-graining procedure. The resulting models typically reproduce the intermolecular structure of AA models at a single thermodynamic state point but often describe other state points less accurately and, moreover, tend to provide a poor description of thermodynamic properties. These two limitations have been coined the transferability and representability problems, respectively. Perhaps, the simplest and most commonly discussed manifestation of the representability problem regards the tendency of structure-based CG models to dramatically overestimate the pressure. Furthermore, when these models are adjusted to reproduce the pressure, they provide a poor description of the compressibility. More generally, it is sometimes suggested that CG models are fundamentally incapable of reproducing both structural and thermodynamic properties. After all, there is no such thing as a free lunch; any significant gain in computational efficiency should come at the cost of significant model limitations. At least in the case of structural and thermodynamic properties, though, we optimistically propose that this may be a false dichotomy. Accordingly, we have recently re-examined the exact coarse-graining procedure and investigated the intrinsic consequences of representing an AA-model in reduced resolution. These studies clarify the origin and inter-relationship of representability and transferability problems. Both arise as consequences of transferring thermodynamic information from the high resolution configuration space and encoding this information into the many-body potential of mean force (PMF), that is, the potential that emerges from an exact coarse-graining procedure. At least in principle, both representability and transferability problems can be resolved by properly addressing this thermodynamic information. In particular, we have demonstrated that pressure-matching provides a practical and rigorous means for addressing the density dependence of the PMF. The resulting bottom-up models accurately reproduce the structure, equilibrium density, compressibility, and pressure equation of state for AA models of molecular liquids. Additionally, we have extended this approach to develop transferable potentials that provide similar accuracy for heptane toluene mixtures. Moreover, these potentials provide predictive accuracy for modeling concentrations that were not considered in their parametrization. More generally, this work suggests a van der Waals perspective on coarse graining, in which conventional structure-based methods accurately describe the configuration dependence of the PMF, while independent variational principles infer the thermodynamic information that is necessary to resolve representability and transferability problems.

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