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. 2013 Apr 9;9(4):2020-2034.
doi: 10.1021/ct3010485.

Improved Generalized Born Solvent Model Parameters for Protein Simulations

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Free PMC article

Improved Generalized Born Solvent Model Parameters for Protein Simulations

Hai Nguyen et al. J Chem Theory Comput. .
Free PMC article

Abstract

The generalized Born (GB) model is one of the fastest implicit solvent models and it has become widely adopted for Molecular Dynamics (MD) simulations. This speed comes with tradeoffs, and many reports in the literature have pointed out weaknesses with GB models. Because the quality of a GB model is heavily affected by empirical parameters used in calculating solvation energy, in this work we have refit these parameters for GB-Neck, a recently developed GB model, in order to improve the accuracy of both the solvation energy and effective radii calculations. The data sets used for fitting are significantly larger than those used in the past. Comparing to other pairwise GB models like GB-OBC and the original GB-Neck, the new GB model (GB-Neck2) has better agreement to Poisson-Boltzmann (PB) in terms of reproducing solvation energies for a variety of systems ranging from peptides to proteins. Secondary structure preferences are also in much better agreement with those obtained from explicit solvent MD simulations. We also obtain near-quantitative reproduction of experimental structure and thermal stability profiles for several model peptides with varying secondary structure motifs. Extension to non-protein systems will be explored in the future.

Keywords: GBSA; Generalized Born; Implicit solvent; perfect radii; protein folding; solvation energy.

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Figures

Figure 1
Figure 1
2D histograms of inverse effective Born radii of each GB model versus PB ‘perfect’ radii for tc5b. Perfect agreement is shown by the diagonal line. The color indicates the frequency (number of atoms) in each bin.
Figure 2
Figure 2
PMFs for side chain H-bond formation in the SAAE model peptide for various solvent models. The 2 GB-Neck2 curves used different Born radii for the Glu side chain carboxyl oxygen atoms, indicated in Å in the legend.
Figure 3
Figure 3
Salt bridge PMFs for various solvent models. Panel A shows the PMF profiles for RAAE (Arg salt bridge) while panel B shows PMFs for KAAE (Lys salt bridge). GB-OBC, GB-Neck and GB-Neck2 used original mbondi2 radii set while GB-OBC 1.1 HN+ used mbondi2 with modified HN+(Arg). GB-Neck2.mb3 used the optimized radii set denoted mbondi3 (Table S4).
Figure 4
Figure 4
Secondary structure (upper) and local conformational propensities (lower) for each residue of Ala10 at 300K from REMD simulations using different solvent models.
Figure 5
Figure 5
Secondary structure (upper) and local conformational propensities (lower) at 300K for each residue of HP-1, obtained from REMD simulations using different solvent models.
Figure 6
Figure 6
Panel A and B show the thermal stability profiles for the HP5F and tc5b respectively in GB-OBC, GB-Neck and GB-Neck2 (with and without SASA) REMD simulations, compared to experimental data.-

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References

    1. Feig M, Brooks CL. Recent advances in the development and application of implicit solvent models in biomolecule simulations. Curr. Opin. Struc. Biol. 2004;14(2):217–224. - PubMed
    1. Wang W, Donini O, Reyes CM, Kollman PA. BIOMOLECULAR SIMULATIONS: Recent Developments in Force Fields, Simulations of Enzyme Catalysis, Protein-Ligand, Protein-Protein, and Protein-Nucleic Acid Noncovalent Interactions. Annu. Rev. Bioph. Biom. 2001;30(1):211–243. - PubMed
    1. Zagrovic B, Pande V. Solvent viscosity dependence of the folding rate of a small protein: Distributed computing study. J. Comput. Chem. 2003;24(12):1432–1436. - PubMed
    1. Chen J;, III, C. L. B. Implicit modeling of nonpolar solvation for simulating protein folding and conformational transitions. Phys. Chem. Chem. Phys. 2008;10(4):471–481. - PubMed
    2. Levy RM, Zhang LY, Gallicchio E, Felts AK. On the Nonpolar Hydration Free Energy of Proteins: Surface Area and Continuum Solvent Models for the Solute−Solvent Interaction Energy. J. Am. Chem. Soc. 2003;125(31):9523–9530. - PubMed
    3. Wagoner JA, Baker NA. Assessing implicit models for nonpolar mean solvation forces: The importance of dispersion and volume terms. Proc. Natl. Acad. Sci. USA. 2006;103(22):8331–8336. - PMC - PubMed
    4. Chen J, Brooks CL. Critical Importance of Length-Scale Dependence in Implicit Modeling of Hydrophobic Interactions. J. Am. Chem. Soc. 2007;129(9):2444–2445. - PMC - PubMed
    1. Case DA, Darden TA, Cheatham TE, Simmerling CL, Wang J, Duke RE, Luo R, Crowley M, Walker RC, Zhang W, Merz KM, Wang B, Hayik S, Roitberg A, Seabra G, Kolossvary I, Wong KF, Paesani F, Vanicek J, Wu X, Brozell SR, Steinbrecher T, Gohlke H, Yang L, Tan C, Mongan J, Hornak V, Cui G, Mathews DH, Seetin MG, Sagui C, Babin V, Kollman PA. AMBER 10. 2008

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