4.7 Article

Variational Implicit-Solvent Modeling of Host-Guest Binding: A Case Study on Cucurbit[7]urill

Journal

JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Volume 9, Issue 9, Pages 4195-4204

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/ct400232m

Keywords

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Funding

  1. National Science Foundation (NSF) [DMS-0811259]
  2. Center for Theoretical Biological Physics through the NSF [PHY-0822283]
  3. National Institutes of Health (NIH) [R01GM096188]
  4. NIH [5T32GM007752-32]
  5. Deutsche Forschungsgemeinschaft (DFG)
  6. NSF
  7. NIH
  8. Howard Hughes Medical Institute (HHMI)
  9. Center for Theoretical Biological Physics (CTBP)
  10. National Biomedical Computation Resource (NBCR)
  11. Division Of Physics
  12. Direct For Mathematical & Physical Scien [1308264] Funding Source: National Science Foundation
  13. Div Of Molecular and Cellular Bioscience
  14. Direct For Biological Sciences [1020765] Funding Source: National Science Foundation

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The synthetic host cucurbit[7]uril (CB[7]) binds aromatic guests or metal complexes with ultrahigh affinity compared with that typically displayed in protein- ligand binding. Due to its small size, CB[7] serves as an ideal receptor-ligand system for developing computational methods for molecular recognition. Here, we apply the recently developed variational implicit-solvent model (VISM), numerically evaluated by the level-set method, to study hydration effects in the high-affinity binding of the B2 bicyclo[2.2.2]-octane derivative to CB[7]. For the unbound host, we find that the host cavity favors the hydrated state over the dry state due to electrostatic effects. For the guest binding, we find reasonable agreement to experimental binding affinities. Dissection of the individual VISM free-energy contributions shows that the major driving forces are water-mediated hydrophobic interactions and the intrinsic (vacuum) host-guest van der Waals interactions. These findings are in line with recent experiments and molecular dynamics simulations with explicit solvent. It is expected that the level-set VISM, with further refinement on the electrostatic descriptions, can efficiently predict molecular binding and recognition in a wide range of future applications.

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