The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
The nature of folded states of globular proteins
Abstract
We suggest, using dynamical simulations of a simple heteropolymer modelling the α‐carbon sequence in a protein, that genetically the folded states of globular proteins correspond to statistically well‐defined metastable states. This hypothesis, called the metastability hypothesis, states that there are several free energy minima separated by barriers of various heights such that the folded conformations of a polypeptide chain in each of the minima have similar structural characteristics but have different energies from one another. The calculated structural characteristics, such as bond angle and dihedral angle distribution functions, are assumed to arise from only those configurations belonging to a given minimum. The validity of this hypothesis is illustrated by simulations of a continuum model of a heteropolymer whose low temperature state is a well‐defined β‐barrel structure. The simulations were done using a molecular dynamics algorithm (referred to as the “noisy” molecular dynamics method) containing both friction and noise terms. It is shown that for this model there are several distinct metastable minima in which the structural features are similar. Several new methods of analyzing fluctuations in structures belonging to two distinct minima are introduced. The most notable one is a dynamic measure of compactness that can in principle provide the time required for maximal compactness to be achieved. The analysis shows that for a given metastable state in which the protein has a well‐defined folded structure the transition to a state of higher compactness occurs very slowly, lending credence to the notion that the system encounters a late barrier in the process of folding to the most compact structure. The examination of the fluctuations in the structures near the unfolding → folding transition temperature indicates that the transition state for the unfolding to folding process occurs closer to the folded state.
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
“Therefore, on the energy landscape, the protein native state is not a single structure but a collection of conformations fluctuating at the bottom of the funnel with comparable energy and small energy barriers.160–161”
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 [161]
Citations
Cites
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
Scaling concepts in polymer physics
Gordon, M. (1981) · Polymer · doi:10.1016/0032-3861(81)90183-x · Cited by 10,559
Scaling Concepts in Polymer Physics
de Gennes, P. G., & Witten, T. A. (1980) · Physics Today · doi:10.1063/1.2914118 · Cited by 9,348
Principles that Govern the Folding of Protein Chains
Anfinsen, C. B. (1973) · Science · doi:10.1126/science.181.4096.223 · Cited by 7,096
Swope, W. C., Andersen, H. C., Berens, P. H., & Wilson, K. R. (1982) · The Journal of Chemical Physics · doi:10.1063/1.442716 · Cited by 4,068
Dominant forces in protein folding
Dill, K. A. (1990) · Biochemistry · doi:10.1021/bi00483a001 · Cited by 3,829
Spin Glass Theory and Beyond: An Introduction to the Replica Method and Its Applications
Mezard, M., Parisi, G., & Virasoro, M. (1986) · World Scientific Lecture Notes in Physics · doi:10.1142/0271 · Cited by 3,653
The Anatomy and Taxonomy of Protein Structure
Richardson, J. S. (1981) · Advances in protein chemistry · doi:10.1016/s0065-3233(08)60520-3 · Cited by 3,378
Molecular dynamics study of melting and freezing of small Lennard-Jones clusters
Honeycutt, J. D., & Andersen, H. C. (1987) · The Journal of Physical Chemistry · doi:10.1021/j100303a014 · Cited by 3,267
Self-citationRattle: A “velocity” version of the shake algorithm for molecular dynamics calculations
Andersen, H. C. (1983) · Journal of Computational Physics · doi:10.1016/0021-9991(83)90014-1 · Cited by 3,161
Research works printed but not linked: 6
- Creighton T. E., 1984, Proteins: Structure and Molecular Properties
- Stryer L., 1988, Biochemistry
- Levitt M., 1980, Protein Folding
- Gibson K. D., 1987, Structure and Expressions: Nucleic Acids and Proteins
- Stillinger F. H., 1987, Science, 225, 318
- Head‐Gordon T. Stillinger F. H.&Arrecis J.(1991) AT&T Bell Laboratory Preprint February.
Cited by
Sorted by citations
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
THEORY OF PROTEIN FOLDING: The Energy Landscape Perspective
Onuchic, J. N., Luthey-Schulten, Z., & Wolynes, P. G. (1997) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.48.1.545 · Cited by 2,210
Principles of protein folding — A perspective from simple exact models
Dill, K. A., Bromberg, S., Yue, K., Chan, H. S., Fiebig, K. M., Yee, D. P., & Thomas, P. D. (1995) · Protein Science · doi:10.1002/pro.5560040401 · Cited by 1,529
Onuchic, J. N., & Wolynes, P. G. (2004) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2004.01.009 · Cited by 1,298
Speeding molecular recognition by using the folding funnel: The fly-casting mechanism
Shoemaker, B. A., Portman, J. J., & Wolynes, P. G. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.160259697 · Cited by 992
Šali, A., Shakhnovich, E. I., & Karplus, M. (1994) · Nature · doi:10.1038/369248a0 · Cited by 951
Becker, O. M., & Karplus, M. (1997) · The Journal of Chemical Physics · doi:10.1063/1.473299 · Cited by 808
Molecular crowding enhances native state stability and refolding rates of globular proteins
Cheung, M. S., Klimov, D. K., & Thirumalai, D. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0409630102 · Cited by 565
Self-citationNon-globular Domains in Protein Sequences: Automated Segmentation Using Complexity Measures
Wootton, J. (1994) · Computers and Chemistry · doi:10.1016/0097-8485(94)85023-2 · Cited by 537
Engineering of stable and fast-folding sequences of model proteins.
Shakhnovich, E. I., & Gutin, A. M. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.15.7195 · Cited by 516
Shea, J.-E., & Brooks III, C. L. (2001) · Annual Review of Physical Chemistry · doi:10.1146/annurev.physchem.52.1.499 · Cited by 481
Wei, G., Xi, W., Nussinov, R., & Ma, B. (2016) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00562 · Cited by 436
Feature-extraction from endopeptidase cleavage sites in mitochondrial targeting peptides
Schneider, G., Sjöling, S., Wallin, E. J., Wrede, P., Glaser, E. G., & von HEIJNE, G. (1998) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(19980101)30:1 · Cited by 112
Veitshans, T., Klimov, D., & Thirumalai, D. (1997) · Folding and Design · doi:10.1016/s1359-0278(97)00002-3 · Cited by 397
Self-citationKinetics and thermodynamics of folding in model proteins.
Camacho, C. J., & Thirumalai, D. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.13.6369 · Cited by 357
Self-citationKinetics of protein folding: Nucleation mechanism, time scales, and pathways
Guo, Z., & Thirumalai, D. (1995) · Biopolymers · doi:10.1002/bip.360360108 · Cited by 336
Self-citationCoarse-grained models of protein folding: toy models or predictive tools?
Clementi, C. (2007) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2007.10.005 · Cited by 335
Protein folding funnels: the nature of the transition state ensemble
Onuchic, J. N., Socci, N. D., Luthey-Schulten, Z. A., & Wolynes, P. G. (1996) · Folding and Design · doi:10.1016/s1359-0278(96)00060-0 · Cited by 330
Folding funnels and frustration in off-lattice minimalist protein landscapes
Nymeyer, H., Garcı́a, A. E., & Onuchic, J. N. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.11.5921 · Cited by 324
Okazaki, K.-I., Koga, N., Takada, S., Onuchic, J. N., & Wolynes, P. G. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0604375103 · Cited by 315
Chan, H. S., & Dill, K. A. (1993) · Physics Today · doi:10.1063/1.881371 · Cited by 309
The nature of protein folding pathways: The classical versus the new view
Baldwin, R. L. (1995) · Journal of Biomolecular NMR · doi:10.1007/bf00208801 · Cited by 307
A test of lattice protein folding algorithms.
Yue, K., Fiebig, K. M., Thomas, P. D., Chan, H. S., Shakhnovich, E. I., & Dill, K. A. (1995) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.92.1.325 · Cited by 286
Transition states and folding dynamics of proteins and heteropolymers
Chan, H. S., & Dill, K. A. (1994) · The Journal of Chemical Physics · doi:10.1063/1.466677 · Cited by 282
Theoretical studies of protein folding and unfolding
Karplus, M., & Šali, A. (1995) · Current Opinion in Structural Biology · doi:10.1016/0959-440x(95)80010-x · Cited by 255
Constant temperature simulations using the Langevin equation with velocity Verlet integration
Paterlini, M., & Ferguson, D. M. (1998) · Chemical Physics · doi:10.1016/s0301-0104(98)00214-6 · Cited by 232
CafeMol: A Coarse-Grained Biomolecular Simulator for Simulating Proteins at Work
Kenzaki, H., Koga, N., Hori, N., Kanada, R., Li, W., Okazaki, K.-I., Yao, X., & Takada, S. (2011) · Journal of Chemical Theory and Computation · doi:10.1021/ct2001045 · Cited by 231
Takagi, F., Koga, N., & Takada, S. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1831920100 · Cited by 218
Energy Landscapes: From Clusters to Biomolecules
Wales, D. J., Doye, J. P. K., Miller, M. A., Mortenson, P. N., & Walsh, T. R. (2000) · Advances in chemical physics · doi:10.1002/9780470141748.ch1 · Cited by 204
Understanding protein folding with energy landscape theory Part I: Basic concepts
Plotkin, S. S., & Onuchic, J. N. (2002) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583502003761 · Cited by 200
Criterion that Determines the Foldability of Proteins
Klimov, D. K., & Thirumalai, D. (1996) · Physical Review Letters · doi:10.1103/physrevlett.76.4070 · Cited by 197
Self-citationSimple model of protein folding kinetics.
Zwanzig, R. W. (1995) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.92.21.9801 · Cited by 194
Reduced models of proteins and their applications
Koliński, A., & Skolnick, J. (2003) · Polymer · doi:10.1016/j.polymer.2003.10.064 · Cited by 190
Energy landscapes: calculating pathways and rates
Wales, D. J. (2006) · International Reviews in Physical Chemistry · doi:10.1080/01442350600676921 · Cited by 186
The energy landscape as a unifying theme in molecular science
Wales, D. J. (2004) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2004.1497 · Cited by 176
Molecular Modeling of Proteins and Mathematical Prediction of Protein Structure
Neumaier, A. (1997) · SIAM Review · doi:10.1137/s0036144594278060 · Cited by 173
Deciphering the timescales and mechanisms of protein folding using minimal off-lattice models
Thirumalai, D., & Klimov, D. K. (1999) · Current Opinion in Structural Biology · doi:10.1016/s0959-440x(99)80028-1 · Cited by 161
Self-citationThe effects of nonnative interactions on protein folding rates: Theory and simulation
Clementi, C., & Plotkin, S. S. (2004) · Protein Science · doi:10.1110/ps.03580104 · Cited by 158
Conformational Polymorphism of Amphiphilic Polymers in a Poor Solvent
Vasilevskaya, V. V., Khalatur, P. G., & Khokhlov, A. R. (2003) · Macromolecules · doi:10.1021/ma0350563 · Cited by 153
Interphase human chromosome exhibits out of equilibrium glassy dynamics
Shi, G., Liu, L., Hyeon, C., & Thirumalai, D. (2018) · Nature Communications · doi:10.1038/s41467-018-05606-6 · Cited by 150
Self-citationCoarse-Grained Model for Predicting RNA Folding Thermodynamics
Denesyuk, N. A., & Thirumalai, D. (2013) · The Journal of Physical Chemistry B · doi:10.1021/jp401087x · Cited by 150
Self-citationFree energy landscapes of model peptides and proteins
Evans, D. A., & Wales, D. J. (2003) · The Journal of Chemical Physics · doi:10.1063/1.1540099 · Cited by 146
Solvent Viscosity and Friction in Protein Folding Dynamics
Hagen, S. J. (2010) · Current Protein and Peptide Science · doi:10.2174/138920310791330596 · Cited by 145
Shimada, J., Kussell, E. L., & Shakhnovich, E. I. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.4586 · Cited by 144
Internal strain regulates the nucleotide binding site of the kinesin leading head
Hyeon, C., & Onuchic, J. N. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0610939104 · Cited by 141
Effects of Macromolecular Crowding on the Collapse of Biopolymers
Kang, H., Pincus, P. A., Hyeon, C., & Thirumalai, D. (2015) · Physical Review Letters · doi:10.1103/physrevlett.114.068303 · Cited by 138
Self-citationZhuravlev, P. I., & Papoian, G. A. (2010) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583510000119 · Cited by 138
Minimum energy compact structures of random sequences of heteropolymers
Camacho, C. J., & Thirumalai, D. (1993) · Physical Review Letters · doi:10.1103/physrevlett.71.2505 · Cited by 134
Self-citationCoarse-grained model for predicting RNA folding thermodynamicsPreprint
Denesyuk, N. A., & Thirumalai, D. (2016) · Cited by 127
Self-citationKinetics at the collapse transition of homopolymers and random copolymers
Kuznetsov, Y. A., Timoshenko, É. G., & Dawson, K. A. (1995) · The Journal of Chemical Physics · doi:10.1063/1.470615 · Cited by 123
Energy landscapes and the collapse dynamics of homopolymers
Chan, H. S., & Dill, K. A. (1993) · The Journal of Chemical Physics · doi:10.1063/1.465277 · Cited by 123
Folding kinetics of proteins: A model study
Guo, Z., Thirumalai, D., & Honeycutt, J. D. (1992) · The Journal of Chemical Physics · doi:10.1063/1.463600 · Cited by 116
Self-citationBaumketner, A., Jewett, A. I., & Shea, J. (2003) · Journal of Molecular Biology · doi:10.1016/s0022-2836(03)00929-x · Cited by 116
Positioning hydrogen atoms by optimizing hydrogen-bond networks in protein structures
Hooft, R. W. W., Sander, C., & Vriend, G. (1996) · Proteins Structure Function and Bioinformatics · doi:10.1002/(sici)1097-0134(199612)26:4 · Cited by 298
Self-citationJewett, A. I., Baumketner, A., & Shea, J. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400720101 · Cited by 113
Collective aspects of protein folding illustrated by a toy model
Stillinger, F. H., & Head-Gordon, T. L. (1995) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.52.2872 · Cited by 111
Gray, D. M. (1997) · Biopolymers · doi:10.1002/(sici)1097-0282(199712)42:7 · Cited by 52
Energy landscape of a model protein
Miller, M. A., & Wales, D. J. (1999) · The Journal of Chemical Physics · doi:10.1063/1.480011 · Cited by 107
Multiscale Ensemble Modeling of Intrinsically Disordered Proteins: p53 N-Terminal Domain
Terakawa, T., & Takada, S. (2011) · Biophysical Journal · doi:10.1016/j.bpj.2011.08.003 · Cited by 105
Symmetry, Rigidity, and Allosteric Signaling: From Monomeric Proteins to Molecular Machines
Thirumalai, D., Hyeon, C., Zhuravlev, P. I., & Lorimer, G. H. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00760 · Cited by 108
Self-citationGeneralized Yvon-Born-Green Theory for Molecular Systems
Mullinax, J. W., & Noid, W. G. (2009) · Physical Review Letters · doi:10.1103/physrevlett.103.198104 · Cited by 103
Zhou, Y., & Karplus, M. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1999.2936 · Cited by 103
Self-assembly of β-sheet forming peptides into chiral fibrillar aggregates
Bellesia, G., & Shea, J. (2007) · The Journal of Chemical Physics · doi:10.1063/1.2739547 · Cited by 101
Condensates in RNA repeat sequences are heterogeneously organized and exhibit reptation dynamics
Nguyen, H. T., Hori, N., & Thirumalai, D. (2022) · Nature Chemistry · doi:10.1038/s41557-022-00934-z · Cited by 102
Self-citationDas, P., Matysiak, S., & Clementi, C. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0409471102 · Cited by 100
D/H amide kinetic isotope effects reveal when hydrogen bonds form during protein folding.
Sosnick, T. R., Krantz, B. A., Moran, L. B., & Kentsis, A. (2000) · Nature Structural Biology · doi:10.1038/71265 · Cited by 99
Fast-folding eriments and the topography of protein folding energy landscapes
Wolynes, P. G., Luthey-Schulten, Z. A., & Onuchic, J. N. (1996) · Chemistry & Biology · doi:10.1016/s1074-5521(96)90090-3 · Cited by 101
Shea, J., Nochomovitz, Y. D., Guo, Z., & Brooks, C. L. (1998) · The Journal of Chemical Physics · doi:10.1063/1.476842 · Cited by 95
Energy landscape of a model proteinPreprint
Miller, M. A., & Wales, D. J. (1999) · Cited by 93
Gronau, G., Krishnaji, S. T., Kinahan, M. E., Giesa, T., Wong, J. Y., Kaplan, D. L., & Buehler, M. J. (2012) · Biomaterials · doi:10.1016/j.biomaterials.2012.06.054 · Cited by 88
Thirumalai, D., & Guo, Z. (1995) · Biopolymers · doi:10.1002/bip.360350114 · Cited by 85
Self-citationThirumalai, D., Klimov, D. K., & Lorimer, G. H. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2035072100 · Cited by 84
Self-citationCheung, M. S., & Thirumalai, D. (2006) · Journal of Molecular Biology · doi:10.1016/j.jmb.2005.12.048 · Cited by 84
Self-citationRole of explicitly cooperative interactions in protein folding funnels: A simulation study
Eastwood, M. P., & Wolynes, P. G. (2001) · The Journal of Chemical Physics · doi:10.1063/1.1315994 · Cited by 83
Multi-basin dynamics of a protein in a crystal environment
Garcı́a, A. E., Blumenfeld, R., Hummer, G., & KRUMHANSL, J. A. (1997) · Physica D Nonlinear Phenomena · doi:10.1016/s0167-2789(97)00090-0 · Cited by 83
Regulation of the H4 tail binding and folding landscapes via Lys-16 acetylation
Potoyan, D. A., & Papoian, G. A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1201805109 · Cited by 83
Energetic frustration and the nature of the transition state in protein folding
Shea, J., Onuchic, J. N., & Brooks, C. L. (2000) · The Journal of Chemical Physics · doi:10.1063/1.1313792 · Cited by 81
Friedel, M., Sheeler, D. J., & Shea, J. (2003) · The Journal of Chemical Physics · doi:10.1063/1.1564048 · Cited by 80
Energy landscapes, global optimization and dynamics of the polyalanine Ac(ala)8NHMe
Mortenson, P. N., & Wales, D. J. (2001) · The Journal of Chemical Physics · doi:10.1063/1.1343486 · Cited by 79
Linking topography of its potential surface with the dynamics of folding of a protein model
Berry, R. S., Elmacı, N., Rose, J. P., & Vekhter, B. G. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.18.9520 · Cited by 79
Theory and simulations for RNA folding in mixtures of monovalent and divalent cations
Nguyen, H. T., Hori, N., & Thirumalai, D. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911632116 · Cited by 78
Self-citationA simplified amino acid potential for use in structure predictions of proteins
Wallqvist, A., & Ullner, M. (1994) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340180308 · Cited by 78
Liu, L., Shi, G., Thirumalai, D., & Hyeon, C. (2018) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006617 · Cited by 78
Self-citationKiefhaber, T., & Baldwin, R. L. (1995) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.92.7.2657 · Cited by 77
Effects of Crowding and Confinement on the Structures of the Transition State Ensemble in Proteins
Cheung, M. S., & Thirumalai, D. (2007) · The Journal of Physical Chemistry B · doi:10.1021/jp068201y · Cited by 76
Self-citationEnergy Landscapes for Proteins: From Single Funnels to Multifunctional Systems
Röder, K., Joseph, J. A., Husic, B. E., & Wales, D. J. (2019) · Advanced Theory and Simulations · doi:10.1002/adts.201800175 · Cited by 76
Global Optimization: Quantum Thermal Annealing with Path Integral Monte Carlo
Lee, Y.-H., & Berne, B. J. (1999) · The Journal of Physical Chemistry A · doi:10.1021/jp991868i · Cited by 73
Guo, Z., & Thirumalai, D. (1997) · Folding and Design · doi:10.1016/s1359-0278(97)00052-7 · Cited by 73
Self-citationHuang, L., Kırmızıaltın, S., & Makarov, D. E. (2005) · The Journal of Chemical Physics · doi:10.1063/1.2008231 · Cited by 72
Topography of the free-energy landscape probed via mechanical unfolding of proteins
Kırmızıaltın, S., Huang, L., & Makarov, D. E. (2005) · The Journal of Chemical Physics · doi:10.1063/1.1931659 · Cited by 71
Searching for foldable protein structures using optimized energy functions
Govindarajan, S., & Goldstein, R. A. (1995) · Biopolymers · doi:10.1002/bip.360360105 · Cited by 70
Cellmer, T., Bratko, D., Prausnitz, J. M., & Blanch, H. W. (2007) · Trends in biotechnology · doi:10.1016/j.tibtech.2007.03.011 · Cited by 69
Chakraborty, D., Straub, J. E., & Thirumalai, D. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2002570117 · Cited by 69
Self-citationSemiflexible chains in confined spaces
Morrison, G., & Thirumalai, D. (2009) · Physical Review E · doi:10.1103/physreve.79.011924 · Cited by 68
Self-citationMatysiak, S., Debenedetti, P. G., & Rossky, P. J. (2012) · The Journal of Physical Chemistry B · doi:10.1021/jp3039175 · Cited by 66
Sequence-Dependent Three Interaction Site Model for Single- and Double-Stranded DNA
Chakraborty, D., Hori, N., & Thirumalai, D. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00091 · Cited by 65
Self-citationScaling behavior of some molecular shape descriptors of polymer chains and protein backbones
Arteca, G. A. (1994) · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · doi:10.1103/physreve.49.2417 · Cited by 65
Arteca, G. A. (1993) · Biopolymers · doi:10.1002/bip.360331209 · Cited by 64
From Hi-C Contact Map to Three-Dimensional Organization of Interphase Human Chromosomes
Shi, G., & Thirumalai, D. (2021) · Physical Review X · doi:10.1103/physrevx.11.011051 · Cited by 64
Self-citationEffect of Finite Size on Cooperativity and Rates of Protein Folding
Kouza, M., Li, M. S., O’Brien, E. P., Hu, C., & Thirumalai, D. (2005) · The Journal of Physical Chemistry A · doi:10.1021/jp053770b · Cited by 63
Self-citation
Metadata
- Authors
- Honeycutt, J. D., & Thirumalai, D.
- Affiliations
- University of Maryland, College Park (US)
- ORCID
- Thirumalai, D.
- Venue
- Biopolymers
- Publisher
- Wiley
- Published
- 1992-06
- Volume
- 32
- Issue
- 6
- Pages
- 695-709
- ISSN
- 0006-3525 (ISSN-L)
- 1097-0282
- OpenAlex
- W2153333215
- Cited by
- 360
- References
- 71
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 9 · 2023: 3 · 2022: 7 · 2021: 3 · 2020: 10 · 2019: 8 · 2018: 11 · 2017: 3 · 2016: 13 · 2015: 7 · 2014: 9 · 2013: 8 · 2012: 9
- FWCI
- 5.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Biopolymers (publishedVersion)
- PubMed (publishedVersion)
- 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
- Physical Sciences › Chemistry › Physical and Theoretical Chemistry › Advanced Physical and Chemical Molecular Interactions
- Keywords
- protein folding, metastable states, free energy minima, beta-barrel, protein compactness, transition state, conformational fluctuations, dihedral angle distribution
- MeSH terms
- Algorithms, Mathematics, Models, Molecular, Models, Theoretical, Protein Conformation, Proteins, Thermodynamics
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