The DOI matches its Crossref record; 249 of the 249 references it cites were found in a registry or an index.
The Protein Folding Problem
Open accessAbstract
The "protein folding problem" consists of three closely related puzzles: (a) What is the folding code? (b) What is the folding mechanism? (c) Can we predict the native structure of a protein from its amino acid sequence? Once regarded as a grand challenge, protein folding has seen great progress in recent years. Now, foldable proteins and nonbiological polymers are being designed routinely and moving toward successful applications. The structures of small proteins are now often well predicted by computer methods. And, there is now a testable explanation for how a protein can fold so quickly: A protein solves its large global optimization problem as a series of smaller local optimization problems, growing and assembling the native structure from peptide fragments, local structures first.
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.
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
“The statistical energy landscape theory was developed to study protein folding.1,128–131”
From Protein Ensembles: How Does Nature Harness Thermodynamic Fluctuations for Life? The Diverse Functional Roles of Conformational Ensembles in the Cell (2016) · cites this paper as [130]
In the citing paper
“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 [51]
In the citing paper
“Levinthal argued that there is no need to search this vast space since the energy landscape is funnel-like, rather than flat, and thus can guide sampling toward the biological conformational basin.”
From AlphaFold, Artificial Intelligence (AI), and Allostery (2022) · cites this paper as [51]
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 13,111
Comparative Protein Modelling by Satisfaction of Spatial Restraints
Šali, A., & Blundell, T. L. (1993) · Journal of Molecular Biology · doi:10.1006/jmbi.1993.1626 · Cited by 12,977
Principles that Govern the Folding of Protein Chains
Anfinsen, C. B. (1973) · Science · doi:10.1126/science.181.4096.223 · Cited by 7,096
THE weighted histogram analysis method for free‐energy calculations on biomolecules. I. The method
Kumar, S., Rosenberg, J. M., Bouzida, D., Swendsen, R. H., & Kollman, P. A. (1992) · Journal of Computational Chemistry · doi:10.1002/jcc.540130812 · Cited by 6,808
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 4,499
Dominant forces in protein folding
Dill, K. A. (1990) · Biochemistry · doi:10.1021/bi00483a001 · Cited by 3,829
Self-citationPrediction of protein conformation
Chou, P. Y., & Fasman, G. D. (1974) · Biochemistry · doi:10.1021/bi00699a002 · Cited by 3,309
Empirical Predictions of Protein Conformation
Chou, P. Y., & Fasman, G. D. (1978) · Annual Review of Biochemistry · doi:10.1146/annurev.bi.47.070178.001343 · Cited by 3,137
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
Gellman, S. H. (1998) · Accounts of Chemical Research · doi:10.1021/ar960298r · Cited by 2,550
Research works printed but not linked: 2
- Grabowski M, 2007, Nucleic Acids Seq. Topol., 17, 347
- Hubner IA, 2003, Abstr. Pap. Am. Chem. Soc., 226, U450
Cited by
Sorted by citations
Items 701–800 of 1,001
Protein Folding: A Perspective From Statistical PhysicsPreprint
Lei, J., & Huang, K. (2010) · arXiv (Cornell University) · doi:10.48550/arxiv.1002.5013 · Cited by 6
Uddin, M. R., Mahbub, S., Rahman, M. S., & Bayzid, M. S. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/786921 · Cited by 6
G-VAE, a Geometric Convolutional VAE for ProteinStructure GenerationPreprint
Huang, H., Amor, B. B., Lin, X., Zhu, F., & Fang, Y. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.11920 · Cited by 8
Shult, C. G., Gunderson, K., Coffey, S. J., McNally, B., Brandt, M., Smith, L. S., Steczynski, J. E., Olerich, E. R., Schroeder, S. E., Severson, N. J., et al. (2024) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2024.2404531 · Cited by 5
Sahoo, B. R., & Bardwell, J. C. A. (2025) · Molecular Aspects of Medicine · doi:10.1016/j.mam.2025.101384 · Cited by 5
Mingolelli, G., Raherisoanjato, J., Trinh, D., Gao, Y., & Henke, M. T. (2025) · mBio · doi:10.1128/mbio.01523-25 · Cited by 6
Unifying Constraints Linking Protein Folding and Native Dynamics Decoded from AlphaFold
Zhang, Z., Ren, W., Xie, L., Zheng, Y., Guan, X., Wang, J., Li, W., & Tang, Q.-Y. (2026) · Physical Review Letters · doi:10.1103/7j2j-f8f7 · Cited by 5
Annealed fractional Lévy–Itō diffusion models for protein generation
Paquet, E., Soleymani, F., Viktor, H. L., & Michalowski, W. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.04.009 · Cited by 7
Protein structure prediction problem: formalization using quaternions
Hulianytskyi, L., & Rudyk, V. O. (2013) · Cybernetics and Systems Analysis · doi:10.1007/s10559-013-9546-8 · Cited by 5
Grahnen, J. A., Kubelka, J., & Liberles, D. A. (2011) · Journal of Molecular Evolution · doi:10.1007/s00239-011-9454-3 · Cited by 5
In Vivo, High-Throughput Selection of Thermostable Cyclohexanone Monooxygenase (CHMO)
Maxel, S., Zhang, L., King, E. J., Acosta, A. P., Luo, R., & Li, H. (2020) · Catalysts · doi:10.3390/catal10080935 · Cited by 5
Engineering Binders with Exceptional Selectivity
Teng, K. W., Koide, A., & Koide, S. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2285-8_8 · Cited by 5
Palmisani, F., Segelcke, D., & Vollert, J. (2024) · European Journal of Pain · doi:10.1002/ejp.4736 · Cited by 8
Solving the protein folding problem…
Sleator, R. D. (2024) · FEBS Letters · doi:10.1002/1873-3468.15043 · Cited by 7
Wetting of a Dynamically Patterned Surface Is a Time-Dependent Matter
Chen, W., Kroutil, O., Předota, M., Pezzotti, S., & Gaigeot, M. (2024) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.4c05163 · Cited by 5
Darwinian evolution and chemistry
Chiusoli, G. P. (2009) · RENDICONTI LINCEI · doi:10.1007/s12210-009-0043-y · Cited by 6
Transition states in protein folding
Weikl, T. (2009) · Communications in Computational Physics · doi:10.4208/cicp.2009.08.202 · Cited by 12
Self-citationHelix and H-bond formations of alanine-based peptides containing basic amino acids
Leitgeb, B., Janzsó, G., Hudoba, L., Penke, B., Rákhely, G., & Bogár, F. (2011) · Structural Chemistry · doi:10.1007/s11224-011-9824-x · Cited by 5
Kuo, H., Yang, P.-A., Wang, W.-R., Hsu, H.-C., Wu, C., Ting, Y.-T., Weng, M.-H., Kuo, L.-H., & Cheng, R. P. (2014) · Amino Acids · doi:10.1007/s00726-014-1737-8 · Cited by 5
Quantitative thermodynamic model for globular protein folding
Yakubovich, A. V., & Solov’yov, A. V. (2014) · The European Physical Journal D · doi:10.1140/epjd/e2014-50097-3 · Cited by 5
Vymětal, J., Bathula, S. R., Černý, J., Chaloupková, R., Žı́dek, L., Sklenář, V., & Vondrášek, J. (2014) · Protein Engineering Design and Selection · doi:10.1093/protein/gzu046 · Cited by 5
Wang, J., & Wang, W. (2016) · Advances in Physics X · doi:10.1080/23746149.2016.1216329 · Cited by 5
Shi, Y., Tang, Q., Jiang, Y., Pei, Q., Tan, H., Lu, Z., & Gong, B. (2018) · Chemical Communications · doi:10.1039/c8cc01564c · Cited by 5
Bittrich, S., Schroeder, M., & Labudde, D. (2019) · Scientific Reports · doi:10.1038/s41598-019-55047-4 · Cited by 7
Piecewise All-Atom SMD Simulations Reveal Key Secondary Structures in Luciferase Unfolding Pathway
Zhang, P., Wang, D., Yang, W., & Marszałek, P. E. (2020) · Biophysical Journal · doi:10.1016/j.bpj.2020.10.023 · Cited by 5
Insights into four helical proteins folding via self-guided Langevin dynamics simulation
Dong, S., Luo, S., Huang, K., Zhao, X., Duan, L., & Li, H. (2021) · Molecular Physics · doi:10.1080/00268976.2021.1874558 · Cited by 5
Resolution exchange with tunneling for enhanced sampling of protein landscapes
Yaşar, F., Ray, A. J., & Hansmann, U. H. E. (2022) · Physical review. E · doi:10.1103/physreve.106.015302 · Cited by 5
The complexity of protein structure and the challenges it poses in developing biopharmaceuticals
Berkowitz, S. A., & Houde, D. J. (2019) · Elsevier eBooks · doi:10.1016/b978-0-444-64173-1.00001-9 · Cited by 5
Kant, R., Moyle, A. B., Jethva, P. N., & Gross, M. L. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-99127-8.00017-9 · Cited by 5
Amani, K., Shivnauth, V., & Castroverde, C. D. M. (2023) · Plant Direct · doi:10.1002/pld3.509 · Cited by 5
Nikolova, V., & Galabov, B. (2015) · Macedonian Journal of Chemistry and Chemical Engineering · doi:10.20450/mjcce.2015.644 · Cited by 5
Thermodynamics of protein folding using a modified Wako-Saitô-Muñoz-Eaton model
Tsai, M., Yuan, J., Teranishi, Y., & Lin, S. H. (2012) · Journal of Biological Physics · doi:10.1007/s10867-012-9271-y · Cited by 5
Alas, S. J., González-Pérez, P. P., & Beltrán, H. I. (2019) · Biosystems · doi:10.1016/j.biosystems.2019.04.005 · Cited by 5
Faccioli, R. A., Bortot, L. O., & Delbem, A. C. B. (2014) · International Journal of Natural Computing Research · doi:10.4018/ijncr.2014010104 · Cited by 5
Cui, R. Z., Silva, D., Song, J. H., Bowman, G. R., Zhuang, W., & Huang, X. (2012) · Current Physical Chemistry · doi:10.2174/1877946811202010045 · Cited by 5
Hsu, P., Cheong, S. A., & Lai, S. K. (2014) · The Journal of Chemical Physics · doi:10.1063/1.4875802 · Cited by 5
A kinetic mechanism for in vivo protein folding
Cruzeiro-Hansson, L. (2014) · Bio-Algorithms and Med-Systems · doi:10.1515/bams-2014-0010 · Cited by 5
Noé, F., & Prinz, J.-H. (2013) · Advances in experimental medicine and biology · doi:10.1007/978-94-007-7606-7_6 · Cited by 6
Fractional Field Theory Approach to Protein Folding DynamicsPreprint
Nasrolahpour, H. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/153999 · Cited by 5
Protein Structure Prediction Using a Maximum Likelihood Formulation of a Recurrent Geometric NetworkPreprint
Qi, G., Tollefson, M. R., Gogal, R. A., Smith, R. J., AlQuraishi, M., & Schnieders, M. J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.09.03.458873 · Cited by 5
Sahu, K. K., Meher, S., Menon, A. M., Sridhar, M. K., Vardhan, G. V. H., Pandey, S., Kumar, A., & Das, S. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-820352-1.00108-5 · Cited by 5
Genomic Touchstone: Benchmarking Genomic Language Models in the Context of the Central DogmaPreprint
Wang, Y., Cai, Z., Zeng, Q., Gao, Y., Ouyang, J., Xu, Y., Yang, S., He, S., Nie, Y., Cai, Y., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.06.25.661622 · Cited by 7
Unifying constraints linking protein folding and native dynamics decoded from AlphaFold
Zhang, Z., Ren, W., Xie, L., Zheng, Y., Guan, X., Wang, J., Li, W., & Tang, Q.-Y. (2026) · doi:10.64898/2026.01.08.698426 · Cited by 5
Analytical control strategy for biologics. Part I: Foundations
Kendrick, B. S., Sampathkumar, K., Gabrielson, J. P., & Ren, D. (2025) · Journal of Pharmaceutical Sciences · doi:10.1016/j.xphs.2025.103826 · Cited by 5
Mechanistic insights of molecular chaperone Hsp70: Pathogenesis of neurodegenerative diseases
Choudhary, A., Kumar, P., Jagtap, Y. A., Kinger, S., Jha, H. C., Gutti, R. K., Sharma, V., Prajapati, V. K., & Mishra, A. (2025) · Brain Network Disorders · doi:10.1016/j.bnd.2025.05.001 · Cited by 5
Polymorphism in Self-Assembly of Short Peptoid Sequences
Zheng, R., Zhao, M., Zhou, W., Trinh, T. K. H., Zhang, S., Yoreo, J. J. D., Ferguson, A. L., & Chen, C. (2026) · Polymer science & technology. · doi:10.1021/polymscitech.5c00123 · Cited by 4
Condensates and cell states: A new paradigm for understanding tumor biology
Nussinov, R., & Jang, H. (2026) · Biophysical Journal · doi:10.1016/j.bpj.2026.01.052 · Cited by 5
Amino acid composition drives aggregation during peptide synthesis
Tamás, B., Alberts, M., Laino, T., & Hartrampf, N. (2026) · Nature Chemistry · doi:10.1038/s41557-026-02090-0 · Cited by 6
Chaperone dependency during biogenesis does not correlate with chaperone dependency during refolding
Yadav, D., Demiralp, I. I., Fakler, M. J., & Fried, S. D. (2025) · Molecular Systems Biology · doi:10.1038/s44320-025-00166-6 · Cited by 4
A population-based evolutionary algorithm for sampling minima in the protein energy surface
Saleh, S. N., Olson, B., & Shehu, A. (2012) · IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW) · doi:10.1109/bibmw.2012.6470207 · Cited by 4
A generalization of Fermat's principle for classical and quantum systems
Elsayed, T. A. (2014) · Physics Letters A · doi:10.1016/j.physleta.2014.09.032 · Cited by 4
Computational design by evolving folds and assemblies over the alphabet in l- and d-α-amino acids
Ghosh, P., Mushtaq, A. U., & Durani, S. (2012) · RSC Advances · doi:10.1039/c2ra01012g · Cited by 4
Andryushchenko, V. A., & Chekmarev, S. F. (2018) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.8b07737 · Cited by 4
Bhunia, A., Ilyas, H., & Bhattacharjya, S. (2020) · Biochemistry · doi:10.1021/acs.biochem.0c00522 · Cited by 4
Stochastic Lag Time Parameterization for Markov State Models of Protein Dynamics
Gong, S., He, X., Meng, Q., Ma, Z.-M., Shao, B., Wang, T., & Liu, T. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c03711 · Cited by 4
Einstein Model of a Graph to Characterize Protein Folded/Unfolded States
Tyler, S., Laforge, C., Guzzo, A., Nicolaı̈, A., Maisuradze, G. G., & Senet, P. (2023) · Molecules · doi:10.3390/molecules28186659 · Cited by 4
CFOM: Lead Optimization For Drug Discovery With Limited Data
Kaminsky, N., Singer, U., & Radinsky, K. (2023) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3583780.3614807 · Cited by 4
On the distance to the transition state of protein folding in optical tweezers experiments
Corrêa, C. G., & Wilson, C. A. M. (2025) · Biophysical Reviews · doi:10.1007/s12551-024-01264-9 · Cited by 4
On the free energy of protein folding in optical tweezers experiments
Wilson, C. A. M., & Corrêa, C. G. (2025) · Biophysical Reviews · doi:10.1007/s12551-025-01310-0 · Cited by 4
Lattice model refinement of protein structures
Mann, M., & Palù, A. D. (2018) · EPiC series in computing · doi:10.29007/c415 · Cited by 4
Li, Y., Liu, X., Wu, Y., Xu, Z., Li, H., Griffith, L. C., & Zhou, Y. (2010) · Journal of Biological Chemistry · doi:10.1074/jbc.m110.184077 · Cited by 4
von Holst, H., & Li, X. (2015) · Acta Neurochirurgica · doi:10.1007/s00701-015-2368-x · Cited by 4
Dissection of the Zipping-and-Assembly Mechanism for Folding of Model Proteins
Li, S., Wang, J., & Wang, W. (2010) · Chinese Physics Letters · doi:10.1088/0256-307x/27/3/038702 · Cited by 4
Orevi, T., Rahamim, G., Shemesh, S., Ishay, E. B., Amir, D., & Haas, E. (2014) · Bio-Algorithms and Med-Systems · doi:10.1515/bams-2014-0018 · Cited by 4
Molin, J. P. D., da Silva, M. A. A., & Caliri, A. (2011) · Physical Review E · doi:10.1103/physreve.84.041903 · Cited by 4
NCACO-score: An effective main-chain dependent scoring function for structure modeling
Tian, L., Wu, A., Cao, Y., Dong, X., Hu, Y., & Jiang, T. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-208 · Cited by 4
Network Class Superposition Analyses
Pearson, C. A. B., Zeng, C., & Simha, R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0059046 · Cited by 4
Protein Folding and Misfolding: A Perspective from Theory
TA, N. A. K. (2015) · Journal of Glycomics & Lipidomics · doi:10.4172/2153-0637.1000128 · Cited by 4
All-atom calculation of protein free-energy profiles
Orioli, S., Ianeselli, A., Spagnolli, G., & Faccioli, P. (2017) · The Journal of Chemical Physics · doi:10.1063/1.5006039 · Cited by 4
Protein Folding in Vivo: From Anfinsen Back to Levinthal
Cruzeiro-Hansson, L. (2017) · Understanding complex systems · doi:10.1007/978-3-319-72218-4_1 · Cited by 4
Cooperative fibril model: Native, amyloid-like fibril and unfolded states of proteins
Ortiz, J. S. E., & Dias, C. L. (2018) · Physica A Statistical Mechanics and its Applications · doi:10.1016/j.physa.2018.07.045 · Cited by 4
Chin-Fatt, A., Saberianfar, R., & Menassa, R. (2021) · Frontiers in Plant Science · doi:10.3389/fpls.2021.651262 · Cited by 4
Cold Denaturation of α‐Synuclein Amyloid Fibrils
Ikenoue, T., Lee, Y., Kardos, J., Saiki, M., Yagi, H., Kawata, Y., & Goto, Y. (2014) · Angewandte Chemie · doi:10.1002/ange.201403815 · Cited by 4
Kadu, P., Gadhe, L. G., Navalkar, A., Patel, K., Kumar, R., Sastry, M., & Maji, S. K. (2022) · Nanoscale · doi:10.1039/d2nr01942f · Cited by 4
Sucharski, F., Gallo, G., Coelho, C. D. M., Hardy, L., & Würtele, M. (2023) · Journal of Molecular Modeling · doi:10.1007/s00894-023-05490-y · Cited by 4
Liu, Z. H., Zhang, O., Teixeira, J. M. C., Li, J., Head-Gordon, T. L., & Forman-Kay, J. D. (2023) · The Journal of Open Source Software · doi:10.21105/joss.04861 · Cited by 4
Nuclear Magnetic Resonance Spectroscopy to Analyse Protein Folding and Dynamics
Saibo, N. V., Boral, S., Saha, R., Das, A. K., & De, S. (2023) · Springer eBooks · doi:10.1007/978-981-99-2079-2_4 · Cited by 4
Trends Innovations Challenges in Employing Interdisciplinary Approaches to Biomedical Sciences
Ganeshkumar, M., Ayyadhury, S., & Murugan, E. (2024) · Springer eBooks · doi:10.1007/978-981-97-1777-4_20 · Cited by 4
Stratagems for effective function evaluation in computational chemistry
Skone, G., & Skone, G. (2010) · Oxford University Research Archive (ORA) (University of Oxford) · doi:10.5287/ora-o5xqbegvq · Cited by 4
Shukla, E., Agrawal, S. B., & Gaikwad, S. M. (2017) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2017.01.124 · Cited by 4
Denaturant-specific effects on the structural energetics of a protein-denatured ensemble
Moosa, M. M., Goodman, A. Z., Ferreon, J. C., Lee, C. W., Ferreon, A. C. M., & Deniz, A. A. (2017) · European Biophysics Journal · doi:10.1007/s00249-017-1260-4 · Cited by 4
Bayat, M., Karami, L., Gourabi, H., Ahmad, F., Dormiani, K., Nasr‐Esfahani, M. H., & Saboury, A. A. (2019) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2019.03.035 · Cited by 4
Stabilizing and Understanding a Miniprotein by Rational Redesign
Goff, K. L. P., Nicol, D., Williams, C., Crump, M. P., Zieleniewski, F., Samphire, J., Baker, E. G., & Woolfson, D. N. (2019) · Biochemistry · doi:10.1021/acs.biochem.9b00067 · Cited by 4
Improving double-ended transition state searches for soft-matter systems
Röder, K., & Wales, D. J. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0011829 · Cited by 4
Stoichiometry of Amino acids Drives Protein Folding?
da Silva, C. H. T. D. P., & Taft, C. A. (2011) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/073911011010524970 · Cited by 4
Lignell, M., & Becker, H.-D. (2010) · Biophysical Journal · doi:10.1016/j.bpj.2009.10.038 · Cited by 4
Nonextensive statistical mechanics applied to protein folding problem: kinetics aspects
Molin, J. P. D., da Silva, M. A. A., da Silva, I. R., & Caliri, A. (2009) · Brazilian Journal of Physics · doi:10.1590/s0103-97332009000400016 · Cited by 4
Directed transport as a mechanism for protein foldingin vivo
González-Candela, E., & Romero-Rochı́n, V. (2010) · The Journal of Chemical Physics · doi:10.1063/1.3293098 · Cited by 4
Light at the End of the Tunnel
Heilemann, M. (2009) · Angewandte Chemie International Edition · doi:10.1002/anie.200900696 · Cited by 4
Heilemann, M. (2009) · Angewandte Chemie · doi:10.1002/ange.200900696 · Cited by 4
Integer Programming Approach to HP Folding
Yanev, N., Milanov, P., & Mirchev, I. (2012) · Serdica Journal of Computing · doi:10.55630/sjc.2011.5.359-366 · Cited by 4
Coarse-grained dynamics of supramolecules: Conformational changes in outer shells of Dengue viruses
Koehl, P., & Delarue, M. H. (2018) · Progress in Biophysics and Molecular Biology · doi:10.1016/j.pbiomolbio.2018.09.004 · Cited by 4
Nonconservation of Topological Charge and Cusps in a One-Dimensional Laser Scheme
Veretenov, N. A., Fedorov, S. V., & Rosanov, N. N. (2020) · Physical Review Letters · doi:10.1103/physrevlett.125.193901 · Cited by 4
Protein Folding: A New Geometric AnalysisPreprint
Simmons, W. A., & Weiner, J. L. (2008) · arXiv (Cornell University) · doi:10.48550/arxiv.0809.2079 · Cited by 4
Analysis of Two-State Folding Using Parabolic Approximation I: HypothesisPreprint
Sade, R. S. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/036491 · Cited by 3
The computational models of AlphaFold2 and RoseTTAfold carry protein foldability informationPreprint
Liu, S., Wu, K., & Chen, C. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.01.27.477978 · Cited by 4
The Use of Dansyl Chloride to Probe Protein Structure and Dynamics
Larson, J. D., Tokmina‐Lukaszewska, M., Malone, J., Hasenoehrl, E. J., Kelly, W., Fang, X., White, A., Patterson, A., & Bothner, B. B. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26020456 · Cited by 3
Sundari, T. M., Desai, D., & Selvaraj, C. (2025) · Advances in protein chemistry and structural biology · doi:10.1016/bs.apcsb.2025.04.002 · Cited by 3
Uttarkar, A., & Niranjan, V. (2025) · IEEE Transactions on Molecular Biological and Multi-Scale Communications · doi:10.1109/tmbmc.2025.3600516 · Cited by 3
Rizzi, V., Héritier, M., Piasentin, N., Aureli, S., & Gervasio, F. L. (2025) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.5c02079 · Cited by 3
Metadata
- Authors
- Dill, K. A., Ozkan, S. B., Shell, M. S., & Weikl, T. R.
- Affiliations
- University of California, San Francisco (US)
- Arizona State University (US)
- University of California, Santa Barbara (US)
- Max Planck Institute of Colloids and Interfaces (DE)
- Venue
- Annual Review of Biophysics
- Publisher
- Annual Reviews
- Published
- 2008-06-01
- Volume
- 37
- Issue
- 1
- Pages
- 289-316
- ISSN
- 1936-122X (ISSN-L)
- 1936-1238
- PMC
- PMC2443096
- OpenAlex
- W2129020329
- Cited by
- 1,163
- References
- 248
- Citations by year
- 2026: 51 · 2025: 61 · 2024: 60 · 2023: 70 · 2022: 73 · 2021: 73 · 2020: 59 · 2019: 53 · 2018: 52 · 2017: 47 · 2016: 48 · 2015: 43 · 2014: 70 · 2013: 82 · 2012: 78
- FWCI
- 6.04
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annual Review of Biophysics (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- 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 mechanism, protein structure prediction, de novo protein design, peptide fragments, local optimization, global optimization, folding rate
- MeSH terms
- Computer Simulation, Models, Chemical, Models, Molecular, Protein Conformation, Proteins, Protein Folding
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