Comparison between Generalized-Born and Poisson–Boltzmann methods in physics-based scoring functions for protein structure prediction
Open Access
- 12 August 2005
- journal article
- research article
- Published by Springer Nature in Journal of Molecular Modeling
- Vol. 12 (1) , 101-110
- https://doi.org/10.1007/s00894-005-0013-y
Abstract
Continuum solvent models such as Generalized-Born and Poisson–Boltzmann methods hold the promise to treat solvation effect efficiently and to enable rapid scoring of protein structures when they are combined with physics-based energy functions. Yet, direct comparison of these two approaches on large protein data set is lacking. Building on our previous work with a scoring function based on a Generalized-Born (GB) solvation model, and short molecular-dynamics simulations, we further extended the scoring function to compare with the MM-PBSA method to treat the solvent effect. We benchmarked this scoring function against seven publicly available decoy sets. We found that, somewhat surprisingly, the results of MM-PBSA approach are comparable to the previous GB-based scoring function. We also discussed the effect to the scoring function accuracy due to presence of large ligands and ions in some native structures of the decoy sets.Keywords
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