The DOI matches its Crossref record.
Solvation Free Energy of Biomacromolecules: Parameters for a Modified Generalized Born Model Consistent with the AMBER Force Field
Abstract
The generalized Born (GB) model provides rapid estimates of the electrostatic free energies of solvation for diverse molecules and molecular ions. This method is expected to be of considerable utility for studies of solvation in macromolecular and biological systems. Calculations on biological molecules are typically based on empirical energy functions, each of which have their own prescriptions for determining net atomic charges. For maximum compatibility, GB parameters tailored to specific force fields are required. The development of parameters compatible with the AMBER force field is described. The method is used to estimate free energies of A and B form structures of DNA obtained from molecular dynamics simulations. The results provide an account of the conformational preferences of right-handed DNA in solution.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Implicit Solvation Models: Equilibria, Structure, Spectra, and Dynamics
Cramer, C. J., & Truhlar, D. G. (1999) · Chemical Reviews · doi:10.1021/cr960149m · Cited by 2,308
An Automated Force Field Topology Builder (ATB) and Repository: Version 1.0
Malde, A. K., Zuo, L., Breeze, M., Stroet, M., Poger, D., Nair, P. C., Oostenbrink, C., & Mark, A. E. (2011) · Journal of Chemical Theory and Computation · doi:10.1021/ct200196m · Cited by 1,872
Massova, I., & Kollman, P. A. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008763014207 · Cited by 1,015
Theoretical Methods for the Description of the Solvent Effect in Biomolecular Systems
Orozco, M., & Luque, F. J. (2000) · Chemical Reviews · doi:10.1021/cr990052a · Cited by 622
An improved protein decoy set for testing energy functions for protein structure prediction
Tsai, J., Bonneau, R., Morozov, A. V., Kuhlman, B., Rohl, C. A., & Baker, D. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10454 · Cited by 158
Li, W. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg149 · Cited by 31
Metadata
- Authors
- Jayaram, B., Sprous, D., & Beveridge, D. L.
- Venue
- The Journal of Physical Chemistry B
- Publisher
- American Chemical Society (ACS)
- Published
- 1998-11-01
- Volume
- 102
- Issue
- 47
- Pages
- 9571-9576
- ISSN
- 1520-5207 (ISSN-L)
- 1520-6106
- OpenAlex
- W2098362016
- Cited by
- 258
- References
- 0
- FWCI
- 3.49
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.