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Title: Bounding the electrostatic free energies associated with linear continuum models of molecular solvation.

Journal Article · · J. Chem. Phys.
DOI:https://doi.org/10.1063/1.3081148· OSTI ID:1007394

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Research Organization:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC); Wilkinson Fellowship in Scientific Computing
DOE Contract Number:
DE-AC02-06CH11357
OSTI ID:
1007394
Report Number(s):
ANL/BIO/JA-63360; TRN: US201106%%257
Journal Information:
J. Chem. Phys., Vol. 130, Issue Mar. 2009
Country of Publication:
United States
Language:
ENGLISH