Atomic-level characterization of the structural dynamics of proteins

Improved side-chain torsion potentials for the Amber ff99SB protein force field

Lindorff-Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J., Dror, R., & Shaw, D. (2010) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.22711 · Cited by 6,037 · see citing works

The Energy Landscapes and Motions of Proteins

Frauenfelder, H., Sligar, S. G., & Wolynes, P. G. (1991) · Science · doi:10.1126/science.1749933 · Cited by 3,250 · see citing works

Structure at 2.8 Â resolution of F1-ATPase from bovine heart mitochondria

Abrahams, J. P., Leslie, A. G. W., Lutter, R., & Walker, J. E. (1994) · Nature · doi:10.1038/370621a0 · Cited by 3,004 · see citing works

Direct observation of the rotation of F1-ATPase

Noji, H., Yasuda, R., Yoshida, M., & Kinosita, K. (1997) · Nature · doi:10.1038/386299a0 · Cited by 2,235 · see citing works

Dynamics of folded proteins

McCammon, J., Gelin, B., & Karplus, M. (1977) · Nature · doi:10.1038/267585a0 · Cited by 1,972 · see citing works

Computer simulation of protein folding

Levitt, M., & Warshel, A. (1975) · Nature · doi:10.1038/253694a0 · Cited by 1,051 · see citing works

The protein folding ‘speed limit’

Kubelka, J., Hofrichter, J., & Eaton, W. A. (2004) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2004.01.013 · Cited by 832 · see citing works

Constructing the equilibrium ensemble of folding pathways from short off-equilibrium simulations

Noé, F., Schütte, C., Vanden-Eijnden, E., Reich, L., & Weikl, T. R. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905466106 · Cited by 820 · see citing works

Protein Hydration in Aqueous Solution

Otting, G., Liepinsh, E., & Wüthrich, K. (1991) · Science · doi:10.1126/science.1948083 · Cited by 792 · see citing works

New Tools Provide New Insights in NMR Studies of Protein Dynamics

Mittermaier, A., & Kay, L. E. (2006) · Science · doi:10.1126/science.1124964 · Cited by 785 · see citing works

Long-timescale molecular dynamics simulations of protein structure and function

Klepeis, J. L., Lindorff‐Larsen, K., Dror, R. O., & Shaw, D. E. (2009) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2009.03.004 · Cited by 750 · see citing works

Simultaneous determination of protein structure and dynamics

Lindorff‐Larsen, K., Best, R. B., DePristo, M. A., Dobson, C. M., & Vendruscolo, M. (2005) · Nature Cell Biology · doi:10.1038/nature03199 · Cited by 715 · see citing works

Mapping the transition state and pathway of protein folding by protein engineering

Matouschek, A. T., Kellis, J. T., Serrano, L., & Fersht, A. R. (1989) · Nature · doi:10.1038/340122a0 · Cited by 703 · see citing works

Absolute comparison of simulated and experimental protein-folding dynamics

Snow, C. D., Nguyen, H., Pande, V. S., & Gruebele, M. (2002) · Nature · doi:10.1038/nature01160 · Cited by 701 · see citing works

Reaction coordinates and rates from transition paths

Best, R. B., & Hummer, G. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0408098102 · Cited by 512 · see citing works

Structure of bovine pancreatic trypsin inhibitor

Wlodawer, A., WALTER, J., Huber, R., & Sjölin, L. (1984) · Journal of Molecular Biology · doi:10.1016/s0022-2836(84)80006-6 · Cited by 477 · see citing works

Protein folding dynamics: The diffusion‐collision model and experimental data

Karplus, M., & Weaver, D. L. (1994) · Protein Science · doi:10.1002/pro.5560030413 · Cited by 447 · see citing works

Three key residues form a critical contact network in a protein folding transition state

Vendruscolo, M., Paci, E., Dobson, C. M., & Karplus, M. (2001) · Nature · doi:10.1038/35054591 · Cited by 429 · see citing works

Millisecond-scale molecular dynamics simulations on Anton

Shaw, D. E., Dror, R. O., Salmon, J. K., Grossman, J. P., Mackenzie, K. M., Bank, J. A., Young, C., Deneroff, M. M., Batson, B., Bowers, K. J., et al. (2009) · Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis · doi:10.1145/1654059.1654099 · Cited by 382 · see citing works

Critical role of beta-hairpin formation in protein G folding.

McCallister, E. L., Alm, E. J., & Baker, D. A. (2000) · Nature Structural Biology · doi:10.1038/77971 · Cited by 368 · see citing works

Φ-Value analysis and the nature of protein-folding transition states

Fersht, A. R., & Sato, S. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0402684101 · Cited by 351 · see citing works

Ten-Microsecond Molecular Dynamics Simulation of a Fast-Folding WW Domain

Freddolino, L., Liu, F., Gruebele, M., & Schulten, K. J. (2008) · Biophysical Journal · doi:10.1529/biophysj.108.131565 · Cited by 336 · see citing works

The folding mechanism of a β-sheet: the WW domain

Jäger, M., Nguyen, H., Crane, J. C., Kelly, J. W., & Gruebele, M. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.4873 · Cited by 304 · see citing works

Experimental determination of upper bound for transition path times in protein folding from single-molecule photon-by-photon trajectories

Chung, H. S., Louis, J. M., & Eaton, W. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0901178106 · Cited by 285 · see citing works

Context-dependent contributions of backbone hydrogen bonding to β-sheet folding energetics

Deechongkit, S., Nguyen, H., Powers, E. T., Dawson, P. E., Gruebele, M., & Kelly, J. W. (2004) · Nature · doi:10.1038/nature02611 · Cited by 278 · see citing works

Sub-microsecond Protein Folding

Kubelka, J., Chiu, T. K., Davies, D. R., Eaton, W. A., & Hofrichter, J. (2006) · Journal of Molecular Biology · doi:10.1016/j.jmb.2006.03.034 · Cited by 255 · see citing works

Unifying features in protein-folding mechanisms

Gianni, S., Guydosh, N. R., Khan, F., Caldas, T. D., Mayor, U., White, G. W. N., DeMarco, M. L., Daggett, V., & Fersht, A. R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1835776100 · Cited by 241 · see citing works

Structure-function-folding relationship in a WW domain.

Jäger, M., Zhang, Y., Bieschke, J., Nguyen, H., Dendle, M. T. A., Bowman, M. E., Noel, J., Gruebele, M., & Kelly, J. (2006) · Proceedings of the National Academy of Sciences of the United States of America · doi:10.1073/pnas.0600511103 · Cited by 214 · see citing works

Force Field Bias in Protein Folding Simulations

Freddolino, L., Park, S., Roux, B., & Schulten, K. (2009) · Biophysical Journal · doi:10.1016/j.bpj.2009.02.033 · Cited by 197 · see citing works

NMR investigations of the dynamics of the aromatic amino acid residues in the basic pancreatic trypsin inhibitor

Wüthrich, K., & Wagner, G. H. (1975) · FEBS Letters · doi:10.1016/0014-5793(75)80504-7 · Cited by 195 · see citing works

Native proteins are surface-molten solids: application of the lindemann criterion for the solid versus liquid state 1 1Edited by A. R. Fersht

Zhou, Y., Vitkup, D., & Karplus, M. (1999) · Journal of Molecular Biology · doi:10.1006/jmbi.1998.2374 · Cited by 160 · see citing works

Disulfide bond isomerization in BPTI and BPTI(G36S): An NMR study of correlated mobility in proteins

Otting, G., Liepinsh, E., & Wuethrich, K. (1993) · Biochemistry · doi:10.1021/bi00065a008 · Cited by 149 · see citing works

An experimental survey of the transition between two-state and downhill protein folding scenarios

Liu, F., Du, D., Fuller, A. A., Davoren, J. E., Wipf, P., Kelly, J. W., & Gruebele, M. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0711908105 · Cited by 148 · see citing works

Disulfide Bond Isomerization in Basic Pancreatic Trypsin Inhibitor: Multisite Chemical Exchange Quantified by CPMG Relaxation Dispersion and Chemical Shift Modeling

Grey, M. J., Wang, C., & Palmer, A. G. I. (2003) · Journal of the American Chemical Society · doi:10.1021/ja0367389 · Cited by 145 · see citing works

Landscape approaches for determining the ensemble of folding transition states: Success and failure hinge on the degree of frustration

Nymeyer, H., Socci, N. D., & Onuchic, J. N. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.2.634 · Cited by 113 · see citing works

Improved sampling methods for molecular simulation

Lei, H., & Duan, Y. (2007) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2007.03.003 · Cited by 108 · see citing works

Transient Non-native Hydrogen Bonds Promote Activation of a Signaling Protein

Gardino, A. K., Villali, J., Kivenson, A., Lei, M., Liu, C. F., Steindel, P. A., Eisenmesser, E. Z., Labeikovsky, W., Wolf‐Watz, M., Clarkson, M. W., et al. (2009) · Cell · doi:10.1016/j.cell.2009.11.022 · Cited by 107 · see citing works

Nanosecond to Microsecond Protein Dynamics Probed by Magnetic Relaxation Dispersion of Buried Water Molecules

Persson, E., & Halle, B. (2008) · Journal of the American Chemical Society · doi:10.1021/ja0775873 · Cited by 104 · see citing works

Φ-Analysis at the Experimental Limits: Mechanism of β-Hairpin Formation

Petrovich, M., Jonsson, A. L., Ferguson, N. S., et al. (2006) · Journal of Molecular Biology · doi:10.1016/j.jmb.2006.05.050 · Cited by 101 · see citing works

Two proteins with the same structure respond very differently to mutation: the role of plasticity in protein stability

Cota, E., Hamill, S. J., Fowler, S. A., et al. (2000) · Journal of Molecular Biology · doi:10.1006/jmbi.2000.4053 · Cited by 86 · see citing works

A speed limit for conformational change of an allosteric membrane protein

Chakrapani, S., & Auerbach, A. L. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0406777102 · Cited by 75 · see citing works

Sequence determinants of thermodynamic stability in a WW domain—An all‐β‐sheet protein

Jäger, M., Dendle, M. A., & Kelly, J. W. (2009) · Protein Science · doi:10.1002/pro.172 · Cited by 68 · see citing works

The Fip35 WW Domain Folds with Structural and Mechanistic Heterogeneity in Molecular Dynamics Simulations

Ensign, D. L., & Pande, V. S. (2009) · Biophysical Journal · doi:10.1016/j.bpj.2009.01.024 · Cited by 67 · see citing works

The transition state transit time of WW domain folding is controlled by energy landscape roughness

Liu, F., Nakaema, M. K. K., & Gruebele, M. (2009) · The Journal of Chemical Physics · doi:10.1063/1.3262489 · Cited by 67 · see citing works

Φ-Value analysis by molecular dynamics simulations of reversible folding

Settanni, G., Rao, F. V., & Caflisch, A. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0406754102 · Cited by 67 · see citing works

Reinvestigation of the aromatic side-chains in the basic pancreatic trypsin inhibitor by heteronuclear two-dimensional nuclear magnetic resonance

Wagner, G. H., Brühwiler, D., & Wüthrich, K. (1987) · Journal of Molecular Biology · doi:10.1016/0022-2836(87)90524-9 · Cited by 57 · see citing works

Anton: A Specialized Machine for Millisecond-Scale Molecular Dynamics Simulations of Proteins

Shaw, D. E. (2009) · Proceedings/Proceedings - Symposium on Computer Arithmetic · doi:10.1109/arith.2009.33 · Cited by 20 · see citing works

(Un)Folding Mechanisms of the FBP28 WW Domain in Explicit Solvent Revealed by Multiple Rare Event Simulation Methods

Juraszek, J., & Bolhuis, P. G. (2010) · Biophysical Journal · doi:10.1016/j.bpj.2009.10.039 · Cited by 16 · see citing works

Characterisation of transition state structures for protein folding using 'high', 'medium' and 'low' -values

Geierhaas, C. D., Salvatella, X., Clarke, J., et al. (2008) · Protein Engineering Design and Selection · doi:10.1093/protein/gzm092 · Cited by 15 · see citing works

Computer Simulation of Liquids

Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945 · see citing works

How fast-folding proteins fold

Lindorff-Larsen, K., Piana, S., Dror, R. O., & Shaw, D. E. (2011) · Science · doi:10.1126/science.1208351 · Cited by 1,980 · see citing works

The Protein-Folding Problem, 50 Years On

Dill, K. A., & MacCallum, J. L. (2012) · Science · doi:10.1126/science.1219021 · Cited by 1,699 · see citing works

Protein 3D Structure Computed from Evolutionary Sequence Variation

Marks, D. S., Colwell, L. J., Sheridan, R., Hopf, T. A., Pagnani, A., Zecchina, R., & Sander, C. (2011) · PLoS ONE · doi:10.1371/journal.pone.0028766 · Cited by 1,144 · see citing works

Identification of slow molecular order parameters for Markov model construction

Pérez-Hernández, G., Paul, F., Giorgino, T., De Fabritiis, G., & Noé, F. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4811489 · Cited by 990 · see citing works

Protein structure prediction from sequence variation

Marks, D. S., Hopf, T. A., & Sander, C. (2012) · Nature Biotechnology · doi:10.1038/nbt.2419 · Cited by 622 · see citing works

Sampling alternative conformational states of transporters and receptors with AlphaFold2

del Alamo, D., Sala, D., Mchaourab, H. S., & Meiler, J. (2022) · eLife · doi:10.7554/elife.75751 · Cited by 511 · see citing works

From Metadynamics to Dynamics

Tiwary, P., & Parrinello, M. (2013) · Physical Review Letters · doi:10.1103/physrevlett.111.230602 · Cited by 494 · see citing works

MSMBuilder2: Modeling Conformational Dynamics on the Picosecond to Millisecond Scale

Beauchamp, K. A., Bowman, G. R., Lane, T. J., Maibaum, L., Haque, I. S., & Pande, V. S. (2011) · Journal of Chemical Theory and Computation · doi:10.1021/ct200463m · Cited by 372 · see citing works

To milliseconds and beyond: challenges in the simulation of protein folding

Lane, T. J., Shukla, D., Beauchamp, K. A., & Pande, V. S. (2013) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2012.11.002 · Cited by 409 · see citing works

The Complex Folding Network of Single Calmodulin Molecules

Stigler, J., Ziegler, F., Gieseke, A., Gebhardt, J. C. M., & Rief, M. (2011) · Science · doi:10.1126/science.1207598 · Cited by 372 · see citing works

Finding low-energy conformations of lattice protein models by quantum annealing

Perdomo-Ortiz, A., Dickson, N., Drew-Brook, M., Rose, G., & Aspuru-Guzik, A. (2012) · Scientific Reports · doi:10.1038/srep00571 · Cited by 366 · see citing works

A Variational Approach to Modeling Slow Processes in Stochastic Dynamical Systems

Noé, F., & Nüske, F. (2013) · Multiscale Modeling & Simulation · doi:10.1137/110858616 · Cited by 327 · see citing works

Simplifying the representation of complex free-energy landscapes using sketch-map

Ceriotti, M., Tribello, G. A., & Parrinello, M. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1108486108 · Cited by 340 · see citing works

Scalable emulation of protein equilibrium ensembles with generative deep learning

Lewis, S., Hempel, T., Jiménez-Luna, J., Gastegger, M., Xie, Y., Foong, A. Y. K., Satorras, V. G., Abdin, O., Veeling, B. S., Zaporozhets, I., et al. (2025) · Science · doi:10.1126/science.adv9817 · Cited by 335 · see citing works

Variational approach to molecular kinetics

Nüske, F., Keller, B. G., Pérez-Hernández, G., Mey, A. S. J. S., & Noé, F. (2014) · Journal of Chemical Theory and Computation · doi:10.1021/ct4009156 · Cited by 308 · see citing works

The future of molecular dynamics simulations in drug discovery

Borhani, D. W., & Shaw, D. E. (2012) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-011-9517-y · Cited by 313 · see citing works

Markov state models based on milestoning

Schütte, C., Noé, F., Lu, J., Sarich, M., & Vanden-Eijnden, E. (2011) · The Journal of Chemical Physics · doi:10.1063/1.3590108 · Cited by 228 · see citing works

Parallel random numbers: as easy as 1, 2, 3

Salmon, J. K., Moraes, M. A., Dror, R. O., & Shaw, D. E. (2011) · Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis · doi:10.1145/2063384.2063405 · Cited by 227 · see citing works

Using sketch-map coordinates to analyze and bias molecular dynamics simulations

Tribello, G. A., Ceriotti, M., & Parrinello, M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1201152109 · Cited by 202 · see citing works

AlphaFold2: A Role for Disordered Protein/Region Prediction?

Wilson, C. J., Choy, W.-Y., & Karttunen, M. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23094591 · Cited by 173 · see citing works

Biomolecular simulations: from dynamics and mechanisms to computational assays of biological activity

Huggins, D. J., Biggin, P. C., Dämgen, M. A., Essex, J. W., Harris, S. A., Henchman, R. H., Khalid, S., Kuzmanic, A., Laughton, C. A., Michel, J., et al. (2019) · WIREs Computational Molecular Science · doi:10.1002/wcms.1393 · Cited by 169 · see citing works

Exploring the role of receptor flexibility in structure-based drug discovery

Feixas, F., Lindert, S., Sinko, W., & McCammon, J. A. (2014) · Biophysical Chemistry · doi:10.1016/j.bpc.2013.10.007 · Cited by 156 · see citing works

EMMA: A Software Package for Markov Model Building and Analysis

Senne, M., Trendelkamp-Schroer, B., Mey, A. S. J. S., Schütte, C., & Noé, F. (2012) · Journal of Chemical Theory and Computation · doi:10.1021/ct300274u · Cited by 148 · see citing works

Slow Unfolded-State Structuring in Acyl-CoA Binding Protein Folding Revealed by Simulation and Experiment

Voelz, V. A., Jäger, M., Yao, S., Chen, Y., Zhu, L., Waldauer, S. A., Bowman, G. R., Friedrichs, M., Bakajin, O., Lapidus, L. J., et al. (2012) · Journal of the American Chemical Society · doi:10.1021/ja302528z · Cited by 140 · see citing works

Protein sequence design by conformational landscape optimization

Norn, C., Wicky, B. I. M., Juergens, D., Liu, S., Kim, D., Tischer, D., Koepnick, B., Anishchenko, I., Players, F., Baker, D., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2017228118 · Cited by 144 · see citing works

Characterization of the free-energy landscapes of proteins by NMR-guided metadynamics

Granata, D., Camilloni, C., Vendruscolo, M., & Laio, A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1218350110 · Cited by 143 · see citing works

‘Scaling molecular dynamics beyond 100, 000 processor cores for large-scale biophysical simulations’

Jung, J., Nishima, W., Daniels, M., Bascom, G., Kobayashi, C., Adedoyin, A., Wall, M., Lappala, A., Phillips, D., Fischer, W., et al. (2019) · Journal of Computational Chemistry · doi:10.1002/jcc.25840 · Cited by 114 · see citing works

rawMSA: End-to-end Deep Learning using raw Multiple Sequence Alignments

Mirabello, C., & Wallner, B. (2019) · PLOS ONE · doi:10.1371/journal.pone.0220182 · Cited by 105 · see citing works

Basic Features of a Cell Electroporation Model: Illustrative Behavior for Two Very Different Pulses

Son, R. S., Smith, K. C., Gowrishankar, T. R., Vernier, P. T., & Weaver, J. C. (2014) · The Journal of Membrane Biology · doi:10.1007/s00232-014-9699-z · Cited by 99 · see citing works

Free-energy landscape of protein oligomerization from atomistic simulations

Barducci, A., Bonomi, M., Prakash, M. K., & Parrinello, M. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320077110 · Cited by 87 · see citing works

Protein structure prediction by <i>AlphaFold</i> 2: are attention and symmetries all you need?

Bouatta, N., Sorger, P., & AlQuraishi, M. (2021) · Acta Crystallographica Section D Structural Biology · doi:10.1107/s2059798321007531 · Cited by 69 · see citing works

How kinetics within the unfolded state affects protein folding: an analysis based on Markov state models and an ultra-long MD trajectory

Deng, N.-J., Dai, W., & Levy, R. M. (2013) · The Journal of Physical Chemistry B · doi:10.1021/jp401962k · Cited by 64 · see citing works

Crucial Role of Protein Flexibility in Formation of a Stable Reaction Transition State in an α-Amylase Catalysis

Kosugi, T., & Hayashi, S. (2012) · Journal of the American Chemical Society · doi:10.1021/ja212117m · Cited by 58 · see citing works

A Molecular Interpretation of 2D IR Protein Folding Experiments with Markov State Models

Baiz, C. R., Lin, Y.-S., Peng, C. S., Beauchamp, K. A., Voelz, V. A., Pande, V. S., & Tokmakoff, A. (2014) · Biophysical Journal · doi:10.1016/j.bpj.2014.02.008 · Cited by 51 · see citing works

Hierarchical Folding Free Energy Landscape of HP35 Revealed by Most Probable Path Clustering

Jain, A., & Stock, G. (2014) · The Journal of Physical Chemistry B · doi:10.1021/jp410398a · Cited by 48 · see citing works

Efficient Bayesian estimation of Markov model transition matrices with given stationary distribution

Trendelkamp-Schroer, B., & Noé, F. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4801325 · Cited by 39 · see citing works

Protein multiple conformations prediction using multi-objective evolution algorithm

Hou, M.-H., Jin, S.-R., Cui, X.-Y., Peng, C.-X., Zhao, K.-L., Song, L., & Zhang, G.-J. (2023) · doi:10.1101/2023.04.21.537776 · Cited by 29 · see citing works

EGFR in Limbo

Eck, M. J., & Hahn, W. C. (2012) · Cell · doi:10.1016/j.cell.2012.04.015 · Cited by 5 · see citing works

Conditional diffusion with locality-aware modal alignment for generating diverse protein conformational ensembles

Wang, B., Wang, C., Chen, J., Liu, D., Sun, C., Zhang, J., Zhang, K., & Li, H. (2026) · Nature Machine Intelligence · doi:10.1038/s42256-026-01198-9 · Cited by 5 · see citing works

Optimizing Stability in Dynamic Small-Molecule Binding Proteins

Scherer, M., Kriegel, M., Höcker, B., & Fleishman, S. J. (2026) · Journal of the American Chemical Society · doi:10.1021/jacs.5c19571 · Cited by 2 · see citing works

Force Field Bias in Protein Folding Simulations

Freddolino, L., Park, S., Roux, B., & Schulten, K. (2009) · Biophysical Journal · doi:10.1016/j.bpj.2009.02.033 · Cited by 197 · see citing works

Reshaping the Protein Folding Pathway by Osmolyte via its Effects on the Folding Intermediates

Sharma, G., Dar, T., & Singh, L. (2015) · Current Protein &amp; Peptide Science · doi:10.2174/1389203716666150623104330 · Cited by 10 · see citing works

Comparing the Folding and Misfolding Energy Landscapes of Phosphoglycerate Kinase

Agócs, G., Szabó, B. T., Köhler, G., et al. (2012) · Biophysical Journal · doi:10.1016/j.bpj.2012.05.006 · Cited by 7 · see citing works

Biosynthetic Protein Folding and Molecular Chaperons

Fedorov, A. N. (2022) · Biochemistry (Moscow) · doi:10.1134/s0006297922140115 · Cited by 5 · see citing works

Improving folding properties of computationally designed proteins

Bjerre, B., Nissen, J. N., Madsen, M. G., Fahrig‐Kamarauskaitė, J., Norrild, R. K., Holm, P. C., Nordentoft, M. K., O’Shea, C., Willemoës, M., Johansson, K. E., et al. (2019) · Protein Engineering Design and Selection · doi:10.1093/protein/gzz025 · Cited by 5 · see citing works