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The Protein-Folding Problem, 50 Years On
Abstract
Protein Folding: Past and Future: Fifty years ago the Nobel Prize in chemistry was awarded to Max Perutz and John Kendrew for determining the structure of globular proteins. Since first viewing their structure of myoglobin, scientists have sought to understand protein folding. Dill and MacCallum (p. 1042 ) review the progress that has been made on three central questions: What is the code that relates sequence to structure? How do proteins fold so fast? Can protein structure be computationally predicted? While we have come some way toward answering these questions, new questions have been gene rated. It is no longer useful to talk about “solving the protein-folding problem”—protein folding has grown into a field of research where the next 50 years promise to be as exciting as the last.
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“AlphaFold does not resolve the decades-long protein folding challenge, nor does it identify the folding pathways.”
From AlphaFold, Artificial Intelligence (AI), and Allostery (2022) · cites this paper as [52]
In the citing paper
“According to the funnel hypothesis of protein folding, the native structure of a protein is believed to the global minimum of its free energy [177,193], although many counterexamples exist.”
From The prospects of quantum computing in computational molecular biology (2021) · cites this paper as [177]
In the citing paper
“In fact, as has often been pointed out (for example43) this is a fallacious argument, since the free energy falls progressively as the protein folds, providing sufficient guidance44.”
From Critical assessment of methods of protein structure prediction (CASP)—Round XIV (2021) · cites this paper as [44]
Citations
Cites
Gapped 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
Berman, H. M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.235 · Cited by 40,196
Murzin, A. G., Brenner, S. E., Hubbard, T., & Chothia, C. (1995) · Journal of Molecular Biology · doi:10.1016/s0022-2836(05)80134-2 · Cited by 6,435
Prusiner, S. B. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.23.13363 · Cited by 5,373
Protein folding and misfolding
Dobson, C. M. (2003) · Nature · doi:10.1038/nature02261 · Cited by 4,791
Dominant forces in protein folding
Dill, K. A. (1990) · Biochemistry · doi:10.1021/bi00483a001 · Cited by 3,829
Self-citationThe HHpred interactive server for protein homology detection and structure prediction
Söding, J., Biegert, A., & Lupas, A. N. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki408 · Cited by 3,775
The structure of proteins: Two hydrogen-bonded helical configurations of the polypeptide chain
Pauling, L. C., Corey, R. B., & Branson, H. R. (1951) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.37.4.205 · Cited by 3,007
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
Gellman, S. H. (1998) · Accounts of Chemical Research · doi:10.1021/ar960298r · Cited by 2,550
Flagged first, then by citations
Research works printed but not linked: 2
- Englander S. W., Mayne L., Krishna M. M. G., Q. Rev. Biophys. 40, 287 (2008).
- Snow C. D., Nguyen H., Pande V. S., Gruebele M., Nat. Struct. Mol. Biol. 420, 102 (2002).
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Guo, Z., Hong, H., Yuan, G., Qian, H., Li, B., Cao, Y., Wang, W., Wu, C., & Chen, H. (2020) · Physical Review Letters · doi:10.1103/physrevlett.125.198101 · Cited by 38
Modification of Enzyme Activity by Vibrational Strong Coupling of Water
Vergauwe, R. M. A., Thomas, A., Nagarajan, K., Shalabney, A., George, J., Chervy, T., Seidel, M., Devaux, É., Torbeev, V. Y., & Ebbesen, T. W. (2019) · Angewandte Chemie · doi:10.1002/ange.201908876 · Cited by 38
Protein folding problem: enigma, paradox, solution
Finkelstein, A. V., Bogatyreva, N. S., Ivankov, D. N., & Garbuzynskiy, S. O. (2022) · Biophysical Reviews · doi:10.1007/s12551-022-01000-1 · Cited by 41
What are the principles that govern life?
Gómez‐Márquez, J. (2020) · Communicative & Integrative Biology · doi:10.1080/19420889.2020.1803591 · Cited by 39
Li, D., & Liu, C. (2023) · Structure · doi:10.1016/j.str.2023.08.006 · Cited by 39
Resolving chaperone-assisted protein folding on the ribosome at the peptide level
Wales, T. E., Pajak, A., Roeselová, A., Shivakumaraswamy, S., Howell, S. A., Kjær, S., Hartl, F. U., Engen, J. R., & Balchin, D. (2024) · Nature Structural & Molecular Biology · doi:10.1038/s41594-024-01355-x · Cited by 38
Does water drive protein folding?
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Schennach, M., & Breuker, K. (2013) · Angewandte Chemie International Edition · doi:10.1002/anie.201306838 · Cited by 37
Characterizing key features in the formation of ice and gas hydrate systems
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Chong, S., Im, H., & Ham, S. (2019) · ACS Central Science · doi:10.1021/acscentsci.9b00200 · Cited by 37
Effects of pH on an IDP conformational ensemble explored by molecular dynamics simulation
Lindsay, R. J., Mansbach, R. A., Gnanakaran, S., & Shen, T. (2021) · Biophysical Chemistry · doi:10.1016/j.bpc.2021.106552 · Cited by 39
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Lento, C., & Wilson, D. J. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00222 · Cited by 37
Protein structure prediction in the deep learning era
Peng, Z., Wang, W., Han, R., Zhang, F., & Yang, J. (2022) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2022.102495 · Cited by 40
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Curtis, V. (2015) · Open Research Online (The Open University) · doi:10.21954/ou.ro.0000a4ff · Cited by 37
Ley, K. J., Christofferson, A. J., Penna, M. J., Winkler, D. A., MacLaughlin, S. A., & Yarovsky, I. (2015) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2015.00064 · Cited by 36
Fellner, L., Simon, S., Scherling, C., Witting, M. A., Schober, S., Polte, C., Schmitt‐Kopplin, P., Keim, D. A., Scherer, S., & Neuhaus, K. (2015) · BMC Evolutionary Biology · doi:10.1186/s12862-015-0558-z · Cited by 39
Fogarty, A. C., Potestio, R., & Kremer, K. (2016) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25173 · Cited by 36
Downhill, Ultrafast and Fast Folding Proteins Revised
Banach, M., Stąpor, K., Konieczny, L., Fabian, P., & Roterman, I. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21207632 · Cited by 36
Rico-Pastó, M., Zaltron, A., Davis, S. J., Frutos, S., & Ritort, F. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2112382119 · Cited by 36
Soler, M. A., Rey, A., & Faísca, P. F. N. (2016) · Physical Chemistry Chemical Physics · doi:10.1039/c6cp05086g · Cited by 36
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Frederickx, R., Veld, T. I., & Carlon, E. (2014) · Physical Review Letters · doi:10.1103/physrevlett.112.198102 · Cited by 35
Engel, M. C., Ritchie, D. B., Foster, D. A. N., Beach, K. S. D., & Woodside, M. T. (2014) · Physical Review Letters · doi:10.1103/physrevlett.113.238104 · Cited by 35
Finding the needle in the haystack: towards solving the protein-folding problem computationally
Li, B., Fooksa, M., Heinze, S., & Meiler, J. (2017) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.1080/10409238.2017.1380596 · Cited by 39
Fast nonadiabatic dynamics of many-body quantum systems
Larder, B., Gericke, D. O., Richardson, S. M., Mabey, P., White, T. G., & Gregori, G. (2019) · Science Advances · doi:10.1126/sciadv.aaw1634 · Cited by 35
Duan, S., Yang, X., Yang, Z., Liu, Y., Shi, Q., Yang, Z., Wu, H., Han, Y., Wang, Y., Shen, H., et al. (2021) · Macromolecules · doi:10.1021/acs.macromol.1c01498 · Cited by 35
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Booth, L., Browne, E. V., Mauranyapin, N. P., Madsen, L. S., Barfoot, S., Mark, A. E., & Bowen, W. P. (2022) · Scientific Reports · doi:10.1038/s41598-022-05586-0 · Cited by 36
Li, S., Xiong, B., Xu, Y. M., Lu, T., Luo, X., Luo, C., Shen, J., Chen, K., Zheng, M., & Jiang, H. (2014) · Journal of Chemical Theory and Computation · doi:10.1021/ct5002279 · Cited by 36
Fiebig, O. C., Mancini, E., Caputo, G. A., & Vaden, T. D. (2013) · The Journal of Physical Chemistry B · doi:10.1021/jp408061k · Cited by 37
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Chen, S., Yan, T., Fischer, M., Mordvinkin, A., Saalwächter, K., Thurn‐Albrecht, T., & Binder, W. H. (2017) · Angewandte Chemie International Edition · doi:10.1002/anie.201707363 · Cited by 35
Big-data approaches to protein structure prediction
Söding, J. (2017) · Science · doi:10.1126/science.aal4512 · Cited by 36
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El‐Baba, T. J., Fuller, D. R., Hales, D. A., Russell, D. H., & Clemmer, D. E. (2018) · Journal of the American Society for Mass Spectrometry · doi:10.1007/s13361-018-2034-7 · Cited by 36
Song, S., Ji, J., Chen, X., Gao, S., Tang, Z., & Todo, Y. (2018) · Applied Soft Computing · doi:10.1016/j.asoc.2018.07.042 · Cited by 34
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Thomas, D. A., Chang, R., Mucha, E., Lettow, M., Greis, K., Gewinner, S., Schöllkopf, W., Meijer, G., & von Helden, G. (2020) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp02482a · Cited by 34
Sparrow, Z. M., Ernst, B. G., Joo, P. T., Lao, K. U., & DiStasio, R. A. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0068862 · Cited by 35
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Binette, V., Mousseau, N., & Tufféry, P. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c01293 · Cited by 36
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Domcke, W., & Sobolewski, A. L. (2013) · Nature Chemistry · doi:10.1038/nchem.1601 · Cited by 32
Galano‐Frutos, J. J., García‐Cebollada, H., & Sancho, J. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbz146 · Cited by 32
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Idrees, D., Prakash, A., Haque, M. A., Islam, A., Ahmad, F., & Hassan, M. I. (2015) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2015.1100552 · Cited by 31
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Svilenov, H. L., Menzen, T., Richter, K., & Winter, G. (2020) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.0c00330 · Cited by 31
Smith, Z., Ravindra, P., Wang, Y., Cooley, R., & Tiwary, P. (2020) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.0c03985 · Cited by 31
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Zhao, K., Liu, J., Zhou, X., Su, J., Zhang, Y., & Zhang, G. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab484 · Cited by 28
Azarova, I. E., Klyosova, E. Y., & Polonikov, A. (2021) · Life · doi:10.3390/life11090886 · Cited by 33
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Hu, J., Chen, T., Wang, M., Chan, H. S., & Zhang, Z. (2017) · Physical Chemistry Chemical Physics · doi:10.1039/c7cp01532a · Cited by 28
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Sinha, N. J., Wu, D., Kloxin, C. J., Saven, J. G., Jensen, G. V., & Pochan, D. J. (2019) · Soft Matter · doi:10.1039/c9sm01894h · Cited by 29
Freitas, F. C., Ferreira, P. H. B., Favaro, D. C., & de Oliveira, R. J. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c01320 · Cited by 29
Mughram, M. H. A., Catalano, C., Bowry, J. P., Safo, M. K., Scarsdale, J. N., & Kellogg, G. E. (2021) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.1c00235 · Cited by 28
Roy, S. K., Mass, O. A., Kellis, D. L., Wilson, C. K., Hall, J. A., Yurke, B., & Knowlton, W. B. (2021) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.1c07602 · Cited by 29
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Wijker, S., & Palmans, A. R. A. (2023) · ChemPlusChem · doi:10.1002/cplu.202300260 · Cited by 28
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Shuaib, S., Saini, R. K., Goyal, D., & Goyal, B. (2017) · ChemistrySelect · doi:10.1002/slct.201601970 · Cited by 28
Wavelength‐Selective Folding of Single Polymer Chains with Different Colors of Visible Light
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Metadata
- Authors
- Dill, K. A., & MacCallum, J. L.
- Affiliations
- Stony Brook University (US)
- Corresponding author
- Dill, Ken A.
- Venue
- Science
- Published
- 2012-11-23
- Volume
- 338
- Issue
- 6110
- Pages
- 1042-1046
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2014050554
- Cited by
- 1,699
- References
- 72
- Citations by year
- 2026: 140 · 2025: 132 · 2024: 117 · 2023: 148 · 2022: 114 · 2021: 137 · 2020: 123 · 2019: 144 · 2018: 111 · 2017: 123 · 2016: 121 · 2015: 119 · 2014: 94 · 2013: 73 · 2012: 1
- FWCI
- 8.37
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of General Medical Sciences (GM34993, R01GM034993)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Enzyme Structure and Function
- Keywords
- protein folding, folding kinetics, folding funnel, energy landscape, thermal fluctuations, protein structure prediction, Protein Data Bank
- MeSH terms
- Amino Acid Sequence, Computer Simulation, Pharmaceutical Preparations, Models, Chemical, Protein Conformation, Proteins, Protein Folding, Caspase 9
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 ›
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