Improved Generalized Born Solvent Model Parameters for Protein Simulations
By Hai Nguyen, D. Roe, Carlos Simmerling. Journal of Chemical Theory and Computation, 2013
536 citations recorded by the source corpus.
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.
Subfields: Materials Chemistry, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/af2597722baeb0bc1ee54f6c7e5c5d60f0a2f30f
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In Materials Chemistry
In Molecular Biology
- Alberto Pérez
- J. C. Robertson
- Cong Liu
- Ken A. Dill
- T. Croll
- Emiliano Brini
- Roy Nassar
- Andriy Kryshtafovych
Citations in the corpus
- NMR-assisted protein structure prediction with MELDxMD (2019, methodology): “16 We seeded the replica exchange ladder with 15 predictions from the servers: Baker-Rosettaserver, 17 Quark, 18 Zhang-Server.”
- ISOLDE: a physically realistic environment for model building into low-resolution electron-density maps (2018, methodology): “MD calculations are handled by OpenMM 7.1 (Eastman et al., 2017) using the AMBER ff14sb force field (Maier et al., 2015) in GB-Neck2 implicit solvent (Nguyen et al., 2013) with gridbased protein backbone corrections (Perez et al., 2015).”