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Effective Born radii in the generalized Born approximation: The importance of being perfect
Abstract
Generalized Born (GB) models provide, for many applications, an accurate and computationally facile estimate of the electrostatic contribution to aqueous solvation. The GB models involve two main types of approximations relative to the Poisson equation (PE) theory on which they are based. First, the self‐energy contributions of individual atoms are estimated and expressed as “effective Born radii.” Next, the atom‐pair contributions are estimated by an analytical function fGB that depends upon the effective Born radii and interatomic distance of the atom pairs. Here, the relative impacts of these approximations are investigated by calculating “perfect” effective Born radii from PE theory, and enquiring as to how well the atom‐pairwise energy terms from a GB model using these perfect radii in the standard fGB function duplicate the equivalent terms from PE theory. In tests on several biological macromolecules, the use of these perfect radii greatly increases the accuracy of the atom‐pair terms; that is, the standard form of fGB performs quite well. The remaining small error has a systematic and a random component. The latter cannot be removed without significantly increasing the complexity of the GB model, but an alternative choice of fGB can reduce the systematic part. A molecular dynamics simulation using a perfect‐radii GB model compares favorably with simulations using conventional GB, even though the radii remain fixed in the former. These results quantify, for the GB field, the importance of getting the effective Born radii right; indeed, with perfect radii, the GB model gives a very good approximation to the underlying PE theory for a variety of biomacromolecular types and conformations. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 1297–1304, 2002
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Cited by
The Amber biomolecular simulation programs
Case, D. A., Cheatham, T. E., Darden, T., Gohlke, H., Luo, R., Merz, K. M., Onufriev, A., Simmerling, C., Wang, B., & Woods, R. J. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20290 · Cited by 9,535
Self-citationOnufriev, A., Bashford, D., & Case, D. A. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20033 · Cited by 2,507
Self-citationShearn, C. T., Smathers, R. L., Backos, D. S., Reigan, P., Orlicky, D. J., & Petersen, D. R. (2013) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2013.07.011 · Cited by 69
In Silico Modeling and Scoring of PROTAC-Mediated Ternary Complex Poses
Liao, J., Nie, X., Unarta, I. C., Ericksen, S. S., & Tang, W. (2022) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.1c02155 · Cited by 62
Shearn, C. T., Backos, D. S., Orlicky, D. J., Smathers-McCullough, R. L., & Petersen, D. R. (2014) · Journal of Biological Chemistry · doi:10.1074/jbc.m113.543942 · Cited by 57
Metadata
- Authors
- Onufriev, A., Case, D. A., & Bashford, D.
- Venue
- Journal of Computational Chemistry
- Publisher
- Wiley
- Published
- 2002-08-13
- Volume
- 23
- Issue
- 14
- Pages
- 1297-1304
- ISSN
- 0192-8651 (ISSN-L)
- 1096-987X
- OpenAlex
- W2025880126
- Cited by
- 454
- References
- 0
- FWCI
- 6.16
- Type
- journal article
- Language
- en
- Open access
- closed
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