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Distance-scaled, finite ideal-gas reference state improves structure-derived potentials of mean force for structure selection and stability prediction
Open accessAbstract
The distance-dependent structure-derived potentials developed so far all employed a reference state that can be characterized as a residue (atom)-averaged state. Here, we establish a new reference state called the distance-scaled, finite ideal-gas reference (DFIRE) state. The reference state is used to construct a residue-specific all-atom potential of mean force from a database of 1011 nonhomologous (less than 30% homology) protein structures with resolution less than 2 A. The new all-atom potential recognizes more native proteins from 32 multiple decoy sets, and raises an average Z-score by 1.4 units more than two previously developed, residue-specific, all-atom knowledge-based potentials. When only backbone and C(beta) atoms are used in scoring, the performance of the DFIRE-based potential, although is worse than that of the all-atom version, is comparable to those of the previously developed potentials on the all-atom level. In addition, the DFIRE-based all-atom potential provides the most accurate prediction of the stabilities of 895 mutants among three knowledge-based all-atom potentials. Comparison with several physical-based potentials is made.
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“These datasets have been widely used to test the predictive power of the PPI prediction methods [12, 13, 27–29, 29–35].”
From Deep geometric representations for modeling effects of mutations on protein-protein binding affinity (2021) · cites this paper as [28]
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Cites
Jorgensen, W. L., Maxwell, D. S., & Tirado-Rives, J. (1996) · Journal of the American Chemical Society · doi:10.1021/ja9621760 · Cited by 14,078
CHARMM: A program for macromolecular energy, minimization, and dynamics calculations
Brooks, B., Bruccoleri, R., Olafson, B. D., States, D., Swaminathan, S., & Karplus, M. (1983) · Journal of Computational Chemistry · doi:10.1002/jcc.540040211 · Cited by 13,736
Assessment of protein models with three-dimensional profiles
Lüthy, R., Bowie, J., & Eisenberg, D. (1992) · Nature · doi:10.1038/356083a0 · Cited by 3,588
An all atom force field for simulations of proteins and nucleic acids
Weiner, S. J., Kollman, P. A., Nguyen, D. T., & Case, D. A. (1986) · Journal of Computational Chemistry · doi:10.1002/jcc.540070216 · Cited by 3,450
Recognition of errors in three‐dimensional structures of proteins
Sippl, M. J. (1993) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340170404 · Cited by 2,156
Guerois, R., Nielsen, J. E., & Serrano, L. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00442-4 · Cited by 1,728
Miyazawa, S., & Jernigan, R. L. (1985) · Macromolecules · doi:10.1021/ma00145a039 · Cited by 1,523
The GROMOS Biomolecular Simulation Program Package
Scott, W. R. P., Hünenberger, P. H., Tironi, I. G., Mark, A. E., Billeter, S. R., Fennen, J., Torda, A. E., Huber, T., Krüger, P., & A, W. F. V. G. (1999) · The Journal of Physical Chemistry A · doi:10.1021/jp984217f · Cited by 1,489
Simons, K. T., Kooperberg, C. L., Huang, E. S., & Baker, D. A. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.0959 · Cited by 1,405
Duan, Y., & Kollman, P. A. (1998) · Science · doi:10.1126/science.282.5389.740 · Cited by 1,337
Simulation of activation free energies in molecular systems
Neria, E., Fischer, S., & Karplus, M. (1996) · The Journal of Chemical Physics · doi:10.1063/1.472061 · Cited by 1,325
Clementi, C., Nymeyer, H., & Onuchic, J. N. (2000) · Journal of Molecular Biology · doi:10.1006/jmbi.2000.3693 · Cited by 1,228
A new approach to protein fold recognition
Jones, D. T., Taylort, W. R., & Thornton, J. M. (1992) · Nature · doi:10.1038/358086a0 · Cited by 1,221
Calculation of conformational ensembles from potentials of mena force
Sippl, M. J. (1990) · Journal of Molecular Biology · doi:10.1016/s0022-2836(05)80269-4 · Cited by 1,068
Selection of representative protein data sets
Hobohm, U., Scharf, M. E., Schneider, R., & Sander, C. (1992) · Protein Science · doi:10.1002/pro.5560010313 · Cited by 816
Determination of atomic desolvation energies from the structures of crystallized proteins
Zhang, C., Vasmatzis, G., Cornette, J. L., & DeLisi, C. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0859 · Cited by 537
Effective energy functions for protein structure prediction
Lazaridis, T. (2000) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(00)00063-4 · Cited by 445
Samudrala, R., & Moult, J. (1998) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1479 · Cited by 441
Tanaka, S., & Scheraga, H. A. (1976) · Macromolecules · doi:10.1021/ma60054a013 · Cited by 437
Statistical Potentials Extracted From Protein Structures: How Accurate Are They?
Thomas, P. D., & Dill, K. A. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0175 · Cited by 425
Energy Functions that Discriminate X-ray and Near-native Folds from Well-constructed Decoys
Park, B. H., & Levitt, M. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0256 · Cited by 409
An empirical energy function for threading protein sequence through the folding motif
Bryant, S. H., & Lawrence, C. E. (1993) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340160110 · Cited by 397
A Course in Statistical Mechanics
Friedman, H. L. (1985) · Medical Entomology and Zoology · Cited by 394
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 386
Practical limits of function prediction
Devos, D. P., & Valencia, A. (2000) · Proteins Structure Function and Bioinformatics · doi:10.1002/1097-0134(20001001)41:1 · Cited by 358
Statistical potentials for fold assessment
Melo, F., Sánchez, R., & Šali, A. (2002) · Protein Science · doi:10.1002/pro.110430 · Cited by 349
Identification of native protein folds amongst a large number of incorrect models
Hendlich, M., Lackner, P., Weitckus, S., Flöckner, H., Froschauer, R., Gottsbacher, K., Casari, G., & Sippl, M. J. (1990) · Journal of Molecular Biology · doi:10.1016/s0022-2836(05)80068-3 · Cited by 296
A distance‐dependent atomic knowledge‐based potential for improved protein structure selection
Lu, H. J., & Skolnick, J. (2001) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.1087 · Cited by 292
Lazaridis, T., & Karplus, M. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.2685 · Cited by 269
Moult, J., & James, M. N. G. (1986) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340010207 · Cited by 258
MONSSTER: a method for folding globular proteins with a small number of distance restraints
Skolnick, J., Koliński, A., & Ortíz, Á. R. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0720 · Cited by 255
Gilis, D., & Rooman, M. J. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1237 · Cited by 219
Sun, S. (1993) · Protein Science · doi:10.1002/pro.5560020508 · Cited by 208
Structure-derived hydrophobic potential
Casari, G., & Sippl, M. J. (1992) · Journal of Molecular Biology · doi:10.1016/0022-2836(92)90556-y · Cited by 166
Ab initio construction of protein tertiary structures using a hierarchical approach
Xia, Y., Huang, E. S., Levitt, M., & Samudrala, R. (2000) · Journal of Molecular Biology · doi:10.1006/jmbi.2000.3835 · Cited by 162
Pillardy, J., Czaplewski, C. R., Liwo, A., Lee, J., Ripoll, D. R., Kaźmierkiewicz, R., Ołdziej, S., Wedemeyer, W. J., Gibson, K. D., Arnautova, Y. A., et al. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.041609598 · Cited by 159
Gilis, D., & Rooman, M. J. (1996) · Journal of Molecular Biology · doi:10.1006/jmbi.1996.0226 · Cited by 157
Holm, L., & Sander, C. (1992) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340140208 · Cited by 153
Proline cis-trans isomers in calbindin D9k observed by X-ray crystallography
Svensson, L. A., Thulin, E., & Forsén, S. (1992) · Journal of Molecular Biology · doi:10.1016/0022-2836(92)90976-q · Cited by 147
Lee, J., Liwo, A., & Scheraga, H. A. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.5.2025 · Cited by 147
Protein folding simulations with genetic algorithms and a detailed molecular description
Pedersen, J. T., & Moult, J. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1010 · Cited by 141
A critical assessment of comparative molecular modeling of tertiary structures of proteins*
Mosimann, S. C., Meleshko, R. A., & James, M. N. G. (1995) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340230305 · Cited by 138
Comparison of systematic search and database methods for constructing segments of protein structure
Fidelis, K., Stern, P. S., Bacon, D., & Moult, J. (1994) · "Protein Engineering, Design and Selection" · doi:10.1093/protein/7.8.953 · Cited by 126 · cited 3×
“Another multiple decoy set is loops (Moult and James 1986; Fidelis et al. 1994) from http://prostar.”
BackgroundWallqvist, A., Jernigan, R. L., & Covell, D. G. (1995) · Protein Science · doi:10.1002/pro.5560040923 · Cited by 126
Felts, A. K., Gallicchio, E., Wallqvist, A., & Levy, R. M. (2002) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10171 · Cited by 124
Comparison of database potentials and molecular mechanics force fields
Moult, J. (1997) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(97)80025-5 · Cited by 122
MacArthur, M. W., Laskowski, R. A., & Thornton, J. M. (1994) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(94)90172-4 · Cited by 114
Zhang, L. Y., Gallicchio, E., Friesner, R. A., & Levy, R. M. (2001) · Journal of Computational Chemistry · doi:10.1002/jcc.1031 · Cited by 114
New sequence motifs in flavoproteins: Evidence for common ancestry and tools to predict structure
Vallon, O. (2000) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(20000101)38:1 · Cited by 109
Identifying native‐like protein structures using physics‐based potentials
Dominy, B. N., & Charles L. Brooks (2001) · Journal of Computational Chemistry · doi:10.1002/jcc.10018 · Cited by 103
Ranking potential binding peptides to MHC molecules by a computational threading approach
Altuvia, Y., Schueler‐Furman, O., & Margalit, H. (1995) · Journal of Molecular Biology · doi:10.1006/jmbi.1995.0293 · Cited by 96
Free energy determinants of tertiary structure and the evaluation of protein models
Petrey, D. S., & Honig, B. H. (2000) · Protein Science · doi:10.1110/ps.9.11.2181 · Cited by 95
Designing potential energy functions for protein folding
Hao, M., & SCHERAGAt, H. A. (1999) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(99)80026-8 · Cited by 83
DeBolt, S. E., & Skolnick, J. (1996) · Protein Engineering Design and Selection · doi:10.1093/protein/9.8.637 · Cited by 61
Avbelj, F., Moult, J., Kitson, D., James, M. N. G., & Hagler, A. T. (1990) · Biochemistry · doi:10.1021/bi00489a023 · Cited by 59
Knowledge-based interaction potentials for proteins
Rojnuckarin, A., & Subramaniam, S. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990701)36:1 · Cited by 59
Protein fold analysis of the B30.2-like domain
Seto, M. H., Liu, H.-L. C., Zajchowski, D. A., & Whitlow, M. D. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990501)35:2 · Cited by 53
The introduction of strain and its effects on the structure and stability of T4 lysozyme
Liu, R., Baase, W. A., & Matthews, B. W. (2000) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.3300 · Cited by 50
Functional aspects of the heme bound hemophore HasA by structural analysis of various crystal forms
Arnoux, P., Haser, R., Izadi‐Pruneyre, N., Lecroisey, A., & Czjzek, M. (2000) · Proteins Structure Function and Bioinformatics · doi:10.1002/1097-0134(20001101)41:2 · Cited by 43
Miyazawa, S., & Jernigan, R. L. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990815)36:3 · Cited by 42
Computer simulation of antibody binding specificity
Pellegrini, M. A., & Doniach, S. (1993) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340150410 · Cited by 32
Wallqvist, A., Gallicchio, E., Felts, A. K., & Levy, R. M. (2002) · Advances in chemical physics · doi:10.1002/0471224421.ch8 · Cited by 4
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Comparative Protein Structure Modeling Using Modeller
Eswar, N., Webb, B., Martı́-Renom, M. A., Madhusudhan, M. S., Eramian, D., Shen, M., Pieper, U., & Šali, A. (2006) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi0506s15 · Cited by 4,618
“They include VERIFY3D (Luthy et al., 1992), PROSAII (Sippl, 1993), HARMONY (Topham et al., 1994), ANOLEA (Melo and Feytmans, 1998), and DFIRE (Zhou and Zhou, 2002).”
Comparative Protein Structure Modeling Using MODELLER
Webb, B., & Šali, A. (2016) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.3 · Cited by 4,404
“template was used for the modeling. correct equivalences, that is, They include VERIFY3D (Luthy et al., 1992), Prosa2003 (Sippl, 1993; Wiederstein and Sippl, 2007), HARMONY (Topham et al., 1994), ANOLEA (Melo and Feytmans, 1998), DFIRE (Zhou and Zhou, 2002), DOPE (Shen and Sali, 2006), SOAP (Dong et al., 2013), QMEAN…”
InfluentialComparative Protein Structure Modeling Using MODELLER
Eswar, N., Webb, B., Martı́-Renom, M. A., Madhusudhan, M. S., Eramian, D., Shen, M., Pieper, U., & Šali, A. (2007) · Current Protocols in Protein Science · doi:10.1002/0471140864.ps0209s50 · Cited by 2,874
“They include VERIFY3D (Luthy et al., 1992), PROSAII (Sippl, 1993), HARMONY (Topham et al., 1994), ANOLEA (Melo and Feytmans, 1998), and DFIRE (Zhou and Zhou, 2002).”
MethodStatistical potential for assessment and prediction of protein structures
Shen, M., & Šali, A. (2006) · Protein Science · doi:10.1110/ps.062416606 · Cited by 2,294
Toward the estimation of the absolute quality of individual protein structure models
Benkert, P., Biasini, M., & Schwede, T. F. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq662 · Cited by 2,312
“The performance of QMEAN with respect to other stateof-the-art methods such as ProSA (Sippl, 1993) and DFIRE (Zhou and Zhou, 2002) has also been recently assessed in an independent study (Rykunov and Fiser, 2010).”
Background
Metadata
- Authors
- Zhou, H., & Zhou, Y.
- Affiliations
- Howard Hughes Medical Institute (US)
- Corresponding author
- Zhou, Yaoqi
- Venue
- Protein Science
- Publisher
- Wiley
- Published
- 2002-11
- Volume
- 11
- Issue
- 11
- Pages
- 2714-2726
- ISSN
- 0961-8368 (ISSN-L)
- 1469-896X
- PMC
- PMC2373736
- OpenAlex
- W2125677968
- Cited by
- 902
- References
- 62
- Citations by year
- 2026: 10 · 2025: 15 · 2024: 15 · 2023: 23 · 2022: 20 · 2021: 34 · 2020: 34 · 2019: 44 · 2018: 40 · 2017: 48 · 2016: 37 · 2015: 45 · 2014: 64 · 2013: 64 · 2012: 49
- FWCI
- 5.58
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Protein Science (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Howard Hughes Medical Institute
- State University of New York
- University at Buffalo
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
- Keywords
- knowledge-based potentials, protein structure prediction, protein stability prediction, protein mutants, protein structure database
- MeSH terms
- Mathematics, Models, Theoretical, Protein Conformation, Proteins, Statistics as Topic, Thermodynamics, Protein Folding, Computational Biology
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