The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
Free energy landscape of protein folding in water: Explicit vs. implicit solvent
Abstract
The Generalized Born (GB) continuum solvent model is arguably the most widely used implicit solvent model in protein folding and protein structure prediction simulations; however, it still remains an open question on how well the model behaves in these large‐scale simulations. The current study uses the β‐hairpin from C‐terminus of protein G as an example to explore the folding free energy landscape with various GB models, and the results are compared to the explicit solvent simulations and experiments. All free energy landscapes are obtained from extensive conformation space sampling with a highly parallel replica exchange method. Because solvation model parameters are strongly coupled with force fields, five different force field/solvation model combinations are examined and compared in this study, namely the explicit solvent model: OPLSAA/SPC model, and the implicit solvent models: OPLSAA/SGB (Surface GB), AMBER94/GBSA (GB with Solvent Accessible Surface Area), AMBER96/GBSA, and AMBER99/GBSA. Surprisingly, we find that the free energy landscapes from implicit solvent models are quite different from that of the explicit solvent model. Except for AMBER96/GBSA, all other implicit solvent models find the lowest free energy state not the native state. All implicit solvent models show erroneous salt‐bridge effects between charged residues, particularly in OPLSAA/SGB model, where the overly strong salt‐bridge effect results in an overweighting of a non‐native structure with one hydrophobic residue F52 expelled from the hydrophobic core in order to make better salt bridges. On the other hand, both AMBER94/GBSA and AMBER99/GBSA models turn the β‐hairpin in to an α‐helix, and the α‐helical content is much higher than the previously reported α‐helices in an explicit solvent simulation with AMBER94 (AMBER94/TIP3P). Only AMBER96/GBSA shows a reasonable free energy landscape with the lowest free energy structure the native one despite an erroneous salt‐bridge between D47 and K50. Detailed results on free energy contour maps, lowest free energy structures, distribution of native contacts, α‐helical content during the folding process, NOE comparison with NMR, and temperature dependences are reported and discussed for all five models. Proteins 2003. © 2003 Wiley‐Liss, Inc.
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
Cites
A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules
Cornell, W. D., Cieplak, P., Bayly, C. I., Gould, I. R., Merz, K. M., Ferguson, D. M., Spellmeyer, D. C., Fox, T., Caldwell, J. W., & Kollman, P. A. (1995) · Journal of the American Chemical Society · doi:10.1021/ja00124a002 · Cited by 13,103
Replica-exchange molecular dynamics method for protein folding
Sugita, Y., & Okamoto, Y. (1999) · Chemical Physics Letters · doi:10.1016/s0009-2614(99)01123-9 · Cited by 4,514
Wang, J., Cieplak, P., & Kollman, P. A. (2000) · Journal of Computational Chemistry · doi:10.1002/1096-987x(200009)21:12<1049::aid-jcc3>3.0.co;2-f · Cited by 4,015
Duane, S., Kennedy, A. D., Pendleton, B. J., & Roweth, D. (1987) · Physics Letters B · doi:10.1016/0370-2693(87)91197-x · Cited by 3,872
Semianalytical treatment of solvation for molecular mechanics and dynamics
Still, W. C., Tempczyk, A., Hawley, R. C., & Hendrickson, T. (1990) · Journal of the American Chemical Society · doi:10.1021/ja00172a038 · Cited by 3,643
Classical Electrostatics in Biology and Chemistry
Honig, B., & Nicholls, A. (1995) · Science · doi:10.1126/science.7761829 · Cited by 2,879
Knowledge‐based protein secondary structure assignment
Frishman, D., & Argos, P. (1995) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.340230412 · Cited by 2,523
Analytical molecular surface calculation
Connolly, M. L. (1983) · Journal of Applied Crystallography · doi:10.1107/s0021889883010985 · Cited by 2,508
From Levinthal to pathways to funnels
Dill, K. A., & Chan, H. S. (1997) · Nature Structural & Molecular Biology · doi:10.1038/nsb0197-10 · Cited by 2,293
Structure and Mechanism in Protein Science
Fersht, A. (1998) · Cited by 1,882
Effective energy function for proteins in solution
Lazaridis, T., & Karplus, M. (1999) · Proteins: Structure, Function, and Genetics · doi:10.1002/(sici)1097-0134(19990501)35:2<133::aid-prot1>3.0.co;2-n · Cited by 1,269
Approximate atomic surfaces from linear combinations of pairwise overlaps (LCPO)
Weiser, J., Shenkin, P. S., & Still, W. C. (1999) · Journal of Computational Chemistry · doi:10.1002/(sici)1096-987x(19990130)20:2<217::aid-jcc4>3.0.co;2-a · Cited by 1,198
Generalized Born Models of Macromolecular Solvation Effects
Bashford, D., & Case, D. A. (2000) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.51.1.129 · Cited by 1,146
Global Optimization of Clusters, Crystals, and Biomolecules
Wales, D. J., & Scheraga, H. A. (1999) · Science · doi:10.1126/science.285.5432.1368 · Cited by 1,114
Modification of the Generalized Born Model Suitable for Macromolecules
Onufriev, A., Bashford, D., & Case, D. A. (2000) · The Journal of Physical Chemistry B · doi:10.1021/jp994072s · Cited by 1,074
What are the dielectric “constants” of proteins and how to validate electrostatic models?
Schutz, C. N., & Warshel, A. (2001) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.1106 · Cited by 942
Current opinion in structural biology
(1992) · Current Opinion in Structural Biology · doi:10.1016/0959-440x(92)90120-v · Cited by 933
Folding dynamics and mechanism of β-hairpin formation
Muñoz, V., Thompson, P. A., Hofrichter, J., & Eaton, W. A. (1997) · Nature · doi:10.1038/36626 · Cited by 929
Designing a 20-residue protein
Neidigh, J. W., Fesinmeyer, R. M., & Andersen, N. H. (2002) · Nature Structural Biology · doi:10.1038/nsb798 · Cited by 793
Large-amplitude nonlinear motions in proteins
García, A. E. (1992) · Physical Review Letters · doi:10.1103/physrevlett.68.2696 · Cited by 787
Absolute comparison of simulated and experimental protein-folding dynamics
Snow, C. D., Nguyen, H., Pande, V. S., & Gruebele, M. (2002) · Nature · doi:10.1038/nature01160 · Cited by 701
All-Atom Structure Prediction and Folding Simulations of a Stable Protein
Simmerling, C., Strockbine, B., & Roitberg, A. E. (2002) · Journal of the American Chemical Society · doi:10.1021/ja0273851 · Cited by 589
A short linear peptide that folds into a native stable β-hairpin in aqueous solution
Blanco, F. J., Rivas, G., & Serrano, L. (1994) · Nature Structural & Molecular Biology · doi:10.1038/nsb0994-584 · Cited by 532
Cheung, M. S., García, A. E., & Onuchic, J. N. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.022387699 · Cited by 507
The free energy landscape for β hairpin folding in explicit water
Zhou, R., Berne, B. J., & Germain, R. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.201543998 · Cited by 478
Self-citationα-Helical stabilization by side chain shielding of backbone hydrogen bonds
García, A. E., & Sanbonmatsu, K. Y. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.042496899 · Cited by 442
Generalized Born Model Based on a Surface Integral Formulation
Ghosh, A., Rapp, C. S., & Friesner, R. A. (1998) · The Journal of Physical Chemistry B · doi:10.1021/jp982533o · Cited by 383
Exploring the energy landscape of a ? hairpin in explicit solvent
Garc�a, A. E., & Sanbonmatsu, K. Y. (2001) · Proteins: Structure, Function, and Genetics · doi:10.1002/1097-0134(20010215)42:3<345::aid-prot50>3.0.co;2-h · Cited by 341
Beachy, M. D., Chasman, D., Murphy, R. B., Halgren, T. A., & Friesner, R. A. (1997) · Journal of the American Chemical Society · doi:10.1021/ja962310g · Cited by 336
Can a continuum solvent model reproduce the free energy landscape of a β-hairpin folding in water?
Zhou, R., & Berne, B. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.142430099 · Cited by 336
Self-citationA statistical mechanical model for β-hairpin kinetics
Muñoz, V., Henry, E. R., Hofrichter, J., & Eaton, W. A. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.11.5872 · Cited by 334
Understanding β-hairpin formation
Dinner, A. R., Lazaridis, T., & Karplus, M. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.16.9068 · Cited by 326
Molecular dynamics simulations of unfolding and refolding of a β-hairpin fragment of protein G
Pande, V. S., & Rokhsar, D. S. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.16.9062 · Cited by 316
Zagrovic, B., Sorin, E. J., & Pande, V. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.5033 · Cited by 269
Interpreting the folding kinetics of helical proteins
Zhou, Y., & Karplus, M. (1999) · Nature · doi:10.1038/43937 · Cited by 258
Gallicchio, E., Zhang, L. Y., & Levy, R. M. (2002) · Journal of Computational Chemistry · doi:10.1002/jcc.10045 · Cited by 249
Experimental measurement of the effective dielectric in the hydrophobic core of a protein
García-Moreno, B. E., Dwyer, J. J., Gittis, A. G., Lattman, E. E., Spencer, D. S., & Stites, W. E. (1997) · Biophysical Chemistry · doi:10.1016/s0301-4622(96)02238-7 · Cited by 244
Kollman, P., Dixon, R., Cornell, W., Fox, T., Chipot, C., & Pohorille, A. (1997) · Computer Simulation of Biomolecular Systems · doi:10.1007/978-94-017-1120-3_2 · Cited by 242
Mechanisms and kinetics of β-hairpin formation
Klimov, D. K., & Thirumalai, D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.6.2544 · Cited by 240
The Trp Cage: Folding Kinetics and Unfolded State Topology via Molecular Dynamics Simulations
Snow, C. D., Zagrovic, B., & Pande, V. S. (2002) · Journal of the American Chemical Society · doi:10.1021/ja028604l · Cited by 237
Chemical physics of protein folding
Brooks, C. L., Gruebele, M., Onuchic, J. N., & Wolynes, P. G. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.19.11037 · Cited by 225
Potentials of Mean Force between Ionizable Amino Acid Side Chains in Water
Masunov, A., & Lazaridis, T. (2003) · Journal of the American Chemical Society · doi:10.1021/ja025521w · Cited by 196
Blanco, F. J., & Serrano, L. (1995) · European Journal of Biochemistry · doi:10.1111/j.1432-1033.1995.0634h.x · Cited by 175
Kaya, H., & Chan, H. S. (2003) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)01434-1 · Cited by 172
Zhou, R., Harder, E. D., Xu, H., & Berne, B. J. (2001) · The Journal of Chemical Physics · doi:10.1063/1.1385159 · Cited by 126
Self-citationNew Linear Interaction Method for Binding Affinity Calculations Using a Continuum Solvent Model
Zhou, R., Friesner, R. A., Ghosh, A., Rizzo, R. C., Jorgensen, W. L., & Levy, R. M. (2001) · The Journal of Physical Chemistry B · doi:10.1021/jp011480z · Cited by 122
Self-citationA molecular dynamics study of the 41‐56 β‐hairpin from B1 domain of protein G
Roccatano, D., Amadei, A., Nola, A. D., & Berendsen, H. J. C. (1999) · Protein Science · doi:10.1110/ps.8.10.2130 · Cited by 109
Dynamics and Thermodynamics of β-Hairpin Assembly: Insights from Various Simulation Techniques
Koliński, A., Ilkowski, B., & Skolnick, J. (1999) · Biophysical Journal · doi:10.1016/s0006-3495(99)77127-4 · Cited by 87
Fersht, A. R. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.182542699 · Cited by 80
Cited by
Parallel tempering: Theory, applications, and new perspectives
Earl, D. J., & Deem, M. W. (2005) · Physical Chemistry Chemical Physics · doi:10.1039/b509983h · Cited by 1,313
Dill, K. A., Ozkan, S. B., Shell, M. S., & Weikl, T. R. (2008) · Annual Review of Biophysics · doi:10.1146/annurev.biophys.37.092707.153558 · Cited by 1,163
The VSGB 2.0 model: A next generation energy model for high resolution protein structure modeling
Li, J., Abel, R., Zhu, K., Cao, Y., Zhao, S., & Friesner, R. A. (2011) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.23106 · Cited by 1,159
Feig, M., & Brooks, C. L. (2004) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2004.03.009 · Cited by 566
Hidden complexity of free energy surfaces for peptide (protein) folding
Krivov, S. V., & Karplus, M. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0406234101 · Cited by 358
Metadata
- Authors
- Zhou, R.
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2003-09-03
- Volume
- 53
- Issue
- 2
- Pages
- 148-161
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- OpenAlex
- W2135469866
- Cited by
- 300
- References
- 49
- FWCI
- 7.40
- 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.