A Stochastic Solver of the Generalized Born Model

• Autorzy: Robert C. Harris , Travis Mackoy , Marcia O. Fenley
• Języki publikacji: EN

Abstrakty

EN

A stochastic generalized Born (GB) solver is presented which can give predictions of energies arbitrarily close to those that would be given by exact effective GB radii, and, unlike analytical GB solvers, these errors are Gaussian with estimates that can be easily obtained from the algorithm. This method was tested by computing the electrostatic solvation energies (ΔGsolv) and the electrostatic binding energies (ΔGbind) of a set of DNA-drug complexes, a set of protein-drug complexes, a set of protein-protein complexes, and a set of RNA-peptide complexes. Its predictions of ΔGsolv agree with those of the linearized Poisson-Boltzmann equation, but it does not predict ΔGbind well, although these predictions of ΔGbind may be marginally better than those of traditional analytical GB solvers. Apparently, the GB model itself must be improved before accurate estimates of ΔGbind can be obtained.

Słowa kluczowe

EN

generalized Born; Poisson-Boltzmann; electrostatics; stochastic; solvation; binding; implicit solvent model

• Wydawca: De Gruyter Open
• Czasopismo: Molecular Based Mathematical Biology
• Rocznik: 2013
• Tom: 1
• Strony: 63-74

Daty

otrzymano

2012-10-15

zaakceptowano

2013-02-19

online

2013-03-21

Twórcy

autor

Robert C. Harris

autor

Travis Mackoy

autor

Marcia O. Fenley

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Identyfikatory

DOI

10.2478/mlbmb-2013-0003