The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Progress in Modeling of Protein Structures and Interactions.
Abstract
The prediction of the structures and interactions of biological macromolecules at the atomic level and the design of new structures and interactions are critical tests of our understanding of the interatomic interactions that underlie molecular biology. Equally important, the capability to accurately predict and design macromolecular structures and interactions would streamline the interpretation of genome sequence information and allow the creation of macromolecules with new and useful functions. This review summarizes recent progress in modeling that suggests that we are entering an era in which high-resolution prediction and design will make increasingly important contributions to biology and medicine.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Only recently it has been realized that proteins are not random heteropolymers but their sequences are formed following a tentative design (for a review see [39], [40]).”
From Lethal mutants and truncated selection together solve a paradox of the origin of life (2011) · cites this paper as [40]
Citations
Cites
1 retracted
Computational Design of a Biologically Active Enzyme
Dwyer, M. A., Looger, L. L., & Hellinga, H. W. (2004) · Science · doi:10.1126/science.1098432 · Cited by 295
RetractedGapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
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
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 13,111
Principles that Govern the Folding of Protein Chains
Anfinsen, C. B. (1973) · Science · doi:10.1126/science.181.4096.223 · Cited by 7,096
Jones, D. T. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.3091 · Cited by 5,522
Molecular dynamics simulations of biomolecules
Karplus, M., & McCammon, J. (2002) · Nature Structural Biology · doi:10.1038/nsb0902-646 · Cited by 3,401
HADDOCK: A Protein−Protein Docking Approach Based on Biochemical or Biophysical Information
Dominguez, C., Boelens, R., & Bonvin, A. M. J. J. (2003) · Journal of the American Chemical Society · doi:10.1021/ja026939x · Cited by 3,187
Funnels, pathways, and the energy landscape of protein folding: A synthesis
Bryngelson, J. D., Onuchic, J. N., Socci, N. D., & Wolynes, P. G. (1995) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.340210302 · Cited by 2,648
A hierarchical approach to all‐atom protein loop prediction
Jacobson, M. P., Pincus, D. L., Rapp, C. S., Day, T., Honig, B. H., Shaw, D. E., & Friesner, R. A. (2004) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10613 · Cited by 2,541
VERIFY3D: assessment of protein models with three-dimensional profiles.
Eisenberg, D., Lüthy, R., & Bowie, J. (1997) · Methods in Enzymology · doi:10.1016/s0076-6879(97)77022-8 · Cited by 2,149
Force Fields for Protein Simulations
Ponder, J. W., & Case, D. A. (2003) · Advances in protein chemistry · doi:10.1016/s0065-3233(03)66002-x · Cited by 1,914
Protein Structure Prediction Using Rosetta
Rohl, C. A., Strauss, C. E. M., Misura, K. M. S., & Baker, D. A. (2004) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(04)83004-0 · Cited by 1,754
Self-citationModeller: Generation and Refinement of Homology-Based Protein Structure Models
Fiser, A., & Šali, A. (2003) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(03)74020-8 · Cited by 1,708
Design of a Novel Globular Protein Fold with Atomic-Level Accuracy
Kuhlman, B. A., Dantas, G. A., Ireton, G. C., Varani, G., Stoddard, B. L., & Baker, D. A. (2003) · Science · doi:10.1126/science.1089427 · Cited by 1,666
Self-citationTertiary templates for proteins
Ponder, J. W., & Richards, F. M. (1987) · Journal of Molecular Biology · doi:10.1016/0022-2836(87)90358-5 · Cited by 1,480
Monte Carlo-minimization approach to the multiple-minima problem in protein folding.
Li, Z., & Scheraga, H. A. (1987) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.84.19.6611 · Cited by 1,475
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
Self-citationOnuchic, J. N., & Wolynes, P. G. (2004) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2004.01.009 · Cited by 1,298
Empirical force fields for biological macromolecules: Overview and issues
MacKerell, A. D. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20082 · Cited by 1,263
De Novo Protein Design: Fully Automated Sequence Selection
Dahiyat, B. I., & Mayo, S. L. (1997) · Science · doi:10.1126/science.278.5335.82 · Cited by 1,156
Katchalski-Katzir, E., Shariv, I., Eisenstein, M., Friesem, A., Aflalo, C., & Vakser, I. (1992) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.89.6.2195 · Cited by 1,143
A graph‐theory algorithm for rapid protein side‐chain prediction
Canutescu, A. A., Shelenkov, A. A., & Dunbrack, R. L. (2003) · Protein Science · doi:10.1110/ps.03154503 · Cited by 1,000
Abagyan, R. A., & Totrov, M. M. (1994) · Journal of Molecular Biology · doi:10.1006/jmbi.1994.1052 · Cited by 982
Toward High-Resolution de Novo Structure Prediction for Small Proteins
Bradley, P. H., Misura, K. M. S., & Baker, D. A. (2005) · Science · doi:10.1126/science.1113801 · Cited by 865
Self-citationCAPRI: A Critical Assessment of PRedicted Interactions
Janin, J., Henrick, K., Moult, J., Eyck, L. T., Sternberg, M. J. E., Vajda, S., Vakser, I., & Wodak, S. J. (2003) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.10381 · Cited by 703
Computational design of receptor and sensor proteins with novel functions
Looger, L. L., Dwyer, M. A., Smith, J. J., & Hellinga, H. W. (2003) · Nature · doi:10.1038/nature01556 · Cited by 668
Feig, M., & Brooks, C. L. (2004) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2004.03.009 · Cited by 574
A decade of CASP: progress, bottlenecks and prognosis in protein structure prediction
Moult, J. (2005) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2005.05.011 · Cited by 485
Deciphering the Message in Protein Sequences: Tolerance to Amino Acid Substitutions
Bowie, J. U., Reidhaar-Olson, J. F., Lim, W. A., & Sauer, R. T. (1990) · Science · doi:10.1126/science.2315699 · Cited by 484
Ryter, J. M., & Schultz, S. C. (1998) · The EMBO Journal · doi:10.1093/emboj/17.24.7505 · Cited by 479
High-Resolution Protein Design with Backbone Freedom
Harbury, P. B., Plecs, J. J., Tidor, B., Alber, T., & Kim, P. S. (1998) · Science · doi:10.1126/science.282.5393.1462 · Cited by 458
Contribution of hydrophobic interactions to protein stability
Kellis, J. T., Nyberg, K., ̆ail, D. S., & Fersht, A. R. (1988) · Nature · doi:10.1038/333784a0 · Cited by 432
Enzyme-like proteins by computational design
Bolon, D. N. A., & Mayo, S. L. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.251555398 · Cited by 412
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
ProTherm, version 4.0: thermodynamic database for proteins and mutants
Bava, K. A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh082 · Cited by 367
Assessment of CAPRI predictions in rounds 3–5 shows progress in docking procedures
Méndez, R., Leplae, R., Lensink, M. F., & Wodak, S. J. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20551 · Cited by 336
De novo design of catalytic proteins
Kaplan, J. H., & DeGrado, W. F. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0404387101 · Cited by 316
Ulmer, T. S., Ramirez, B. E., Delaglio, F., & Bax, A. (2003) · Journal of the American Chemical Society · doi:10.1021/ja0350684 · Cited by 301
Computational redesign of protein-protein interaction specificity
Kortemme, T., Joachimiak, Ł. A., Bullock, A. N., Schuler, A. D., Stoddard, B. L., & Baker, D. A. (2004) · Nature Structural & Molecular Biology · doi:10.1038/nsmb749 · Cited by 294
Self-citationStudies on Protein Stability With T4 Lysozyme
Matthews, B. W. (1995) · Advances in protein chemistry · doi:10.1016/s0065-3233(08)60337-x · Cited by 293
New Monte Carlo algorithms for protein folding
Hansmann, U. H. E., & Okamoto, Y. (1999) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(99)80025-6 · Cited by 293
Cellulosome assembly revealed by the crystal structure of the cohesin–dockerin complex
Carvalho, A. L., Dias, F. M. V., Prates, J. A. M., Nagy, T., Gilbert, H. J., Davies, G. J., Ferreira, L. M. A., Romão, M. J., & Fontes, C. M. G. A. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1936124100 · Cited by 259
Morozov, A. V., Kortemme, T., Tsemekhman, K., & Baker, D. A. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307578101 · Cited by 247
Self-citationDesign, Activity, and Structure of a Highly Specific Artificial Endonuclease
Chevalier, B. S., Kortemme, T., Chadsey, M. S., Baker, D. A., Monnat, R. J., & Stoddard, B. L. (2002) · Molecular Cell · doi:10.1016/s1097-2765(02)00690-1 · Cited by 238
Self-citationEnergy functions for protein design
GORDON, D., MARSHALL, S., & MAYOT, S. (1999) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(99)80072-4 · Cited by 218
Protein Flexibility and Adaptability Seen in 25 Crystal Forms of T4 Lysozyme
Zhang, X. C., Wozniak, J. A., & Matthews, B. W. (1995) · Journal of Molecular Biology · doi:10.1006/jmbi.1995.0396 · Cited by 197
Schlosshauer, M., & Baker, D. A. (2004) · Protein Science · doi:10.1110/ps.03517304 · Cited by 192
Self-citationAssessing predictions of protein–protein interaction: The CAPRI experiment
Janin, J. (2005) · Protein Science · doi:10.1110/ps.041081905 · Cited by 179
Bowie, J. U., & Eisenberg, D. S. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.10.4436 · Cited by 174
Assessment of homology-based predictions in CASP5
Tramontano, A. L., & Morea, V. (2003) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10543 · Cited by 172
The Limit of Accuracy of Protein Modeling: Influence of Crystal Packing on Protein Structure
Eyal, E., Gerzon, S., Potapov, V., Edelman, M., & Sobolev, V. M. (2005) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.05.066 · Cited by 137
Scoring profile‐to‐profile sequence alignments
Wang, G., & Dunbrack, R. L. (2004) · Protein Science · doi:10.1110/ps.03601504 · Cited by 135
Modulating Calmodulin Binding Specificity through Computational Protein Design
Shifman, J. M., & Mayo, S. L. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00881-1 · Cited by 118
Methods to study protein folding by stopped-flow FT-IR
Fabian, H. (2004) · Methods · doi:10.1016/j.ymeth.2004.03.004 · Cited by 109
Conformational sampling for the impatient
Tai, K. (2004) · Biophysical Chemistry · doi:10.1016/j.bpc.2003.09.010 · Cited by 107
Schueler‐Furman, O., Wang, C., & Baker, D. A. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20556 · Cited by 99
Self-citationStructural inhibition of the colicin D tRNase by the tRNA‐mimicking immunity protein
Graille, M., Mora, L., Buckingham, R. H., TILBEURGH, H. V., & de Zamaroczy, M. (2004) · The EMBO Journal · doi:10.1038/sj.emboj.7600162 · Cited by 93
Assembling novel protein folds from super-secondary structural fragments
Jones, D. T., & McGuffin, L. J. (2003) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10542 · Cited by 80
TOUCHSTONE: A unified approach to protein structure prediction
Skolnick, J., Zhang, Y., Arakaki, A. K., Koliński, A., Boniecki, M., Szil�gyi, A., & Kihara, D. (2003) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10551 · Cited by 77
Edman, M., Jarhede, T., Sj�str�m, M., & Wieslander, �. (1999) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19990501)35:2 · Cited by 49
Computational design of protein-protein interactions.
Kortemme, T., & Baker, D. (2004) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2003.12.008 · Cited by 34
Self-citationFang, Q., & Shortle, D. (2003) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.10541 · Cited by 26
Modeling and Studying Proteins with Molecular Dynamics
Schleif, R. (2004) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(04)83002-7 · Cited by 8
Predicting Protein Structures Accurately
von Grotthuss, M., Wyrwicz, L. S., Paś, J., & Rychlewski, L. (2004) · Science · doi:10.1126/science.304.5677.1597b · Cited by 7
Flagged first, then by citations
Research works printed but not linked: 4
- C. Levinthal, in Mossbauer Spectroscopy in Biological Systems: Proceedings of a Meeting Held at Allerton House, Monticello, Illinois, J. T. P. DeBrunner, E. Munck, Eds. (Univ. of Illinois Press, Urbana, 1969), pp. 22–24.
- M. von Grotthuss, L. S. Wyrwicz, J. Pas, L. Rychlewski, Science304, 1597 (2004).
- G. E. Moore, Electronics38, 114 (1965).
- S. Y. Chung, S. Subbiah, Pac. Symp. Biocomput.,126 (1996).
Cited by
Sorted by citations
Macromolecular Modeling with Rosetta
Das, R., & Baker, D. A. (2008) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.77.062906.171838 · Cited by 995
Self-citationPrinciples of Protein−Protein Interactions: What are the Preferred Ways For Proteins To Interact?
Keskin, O., Gursoy, A., Ma, B., & Nussinov, R. (2008) · Chemical Reviews · doi:10.1021/cr040409x · Cited by 697
Protein structure determination from NMR chemical shifts
Cavalli, A., Salvatella, X., Dobson, C. M., & Vendruscolo, M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610313104 · Cited by 557
Modeling electrostatic effects in proteins
Warshel, A., Sharma, P. K., Kato, M., & Parson, W. W. (2006) · Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics · doi:10.1016/j.bbapap.2006.08.007 · Cited by 526
Konrad, M., Schaller, A., Seelow, D., Pandey, A. V., Waldegger, S., Lesslauer, A., Vitzthum, H., Suzuki, Y., Luk, J. M., Becker, C., et al. (2006) · The American Journal of Human Genetics · doi:10.1086/508617 · Cited by 525
“A 3D model of the first 115 aa of claudin-19 was constructed using ROSETTA de novo methods, with use of a structure library of protein fragments.(14) Quality of the model was checked by WHATCHECK(15) and Ramachandran plot analysis.”
Method
Metadata
- Authors
- Schueler-Furman, O., Wang, C., Bradley, P., Misura, K., & Baker, D.
- Affiliations
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.
- Howard Hughes Medical Institute (US)
- Corresponding author
- Baker, David
- Venue
- Science
- Published
- 2005-10-28
- Volume
- 310
- Issue
- 5748
- Pages
- 638-642
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2147752484
- Cited by
- 294
- References
- 65
- Citations by year
- 2025: 4 · 2024: 4 · 2023: 2 · 2022: 2 · 2021: 4 · 2020: 5 · 2019: 8 · 2018: 2 · 2017: 8 · 2016: 9 · 2015: 9 · 2014: 8 · 2013: 10 · 2012: 16
- FWCI
- 3.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- 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
- protein structure prediction, protein-protein interaction, interatomic interactions, genome interpretation
- MeSH terms
- Computer Simulation, Computing Methodologies, Models, Molecular, Protein Conformation
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