Representing structures of the multiple conformational states of proteins
Open accessPublished version of a preprint
Abstract
Biomolecules exhibit dynamic behavior that single-state models of their structures cannot fully capture. We review some recent advances for investigating multiple conformations of biomolecules, including experimental methods, molecular dynamics simulations, and machine learning. We also address the challenges associated with representing single- and multiple-state models in data archives, with a particular focus on NMR structures. Establishing standardized representations and annotations will facilitate effective communication and understanding of these complex models to the broader scientific community.
Integrity signals
Registry
Cites
Statistics
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?
Experimental data, especially SAXS, NMR, and cryo-EM, have been described as guides for modeling ensembles and alternative conformations.
“The use of experimental data, especially SAXS, NMR, and cryo-EM, has also been described to guide modeling of ensembles and alternative conformations71,82,108.”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [108]
Cites
Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764 · see citing works
Accurate prediction of protein structures and interactions using a 3-track network
Baek, M., DiMaio, F., Anishchenko, I., Dauparas, J., Ovchinnikov, S., Lee, G. R., Wang, J., Cong, Q., Kinch, L. N., Schaeffer, R. D., et al. (2021) · doi:10.1101/2021.06.14.448402 · Cited by 5,542 · see citing works
Evolutionary-scale prediction of atomic level protein structure with a language model
Lin, Z., Akin, H., Rao, R., Hie, B., Zhu, Z., Lu, W., Smetanin, N., Verkuil, R., Kabeli, O., Shmueli, Y., et al. (2022) · doi:10.1101/2022.07.20.500902 · Cited by 5,523 · see citing works
Proteins: Structure, Function, and Bioinformatics
(2006) · Proteins Structure Function and Bioinformatics · doi:10.1002/(issn)1097-0134 · Cited by 943 · see citing works
Current opinion in structural biology
(1992) · Current Opinion in Structural Biology · doi:10.1016/0959-440x(92)90120-v · Cited by 929 · see citing works
Accessing protein conformational ensembles using room-temperature X-ray crystallography
Fraser, J. S., Bedem, H. V. D., Samelson, A. J., Lang, P. T., Holton, J. M., Echols, N., & Alber, T. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1111325108 · Cited by 619 · 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
Three-Dimensional Structures of Membrane Proteins from Genomic Sequencing
Hopf, T. A., Colwell, L. J., Sheridan, R., Rost, B., Sander, C., & Marks, D. S. (2012) · Cell · doi:10.1016/j.cell.2012.04.012 · Cited by 501 · see citing works
Determination of Ensemble-Average Pairwise Root Mean-Square Deviation from Experimental B-Factors
Kuzmanic, A., & Žagrović, B. (2010) · Biophysical Journal · doi:10.1016/j.bpj.2009.11.011 · Cited by 450 · see citing works
Ahdritz, G., Bouatta, N., Floristean, C., Kadyan, S., Xia, Q., Gerecke, W., O’Donnell, T. J., Berenberg, D., Fisk, I., Zanichelli, N., et al. (2024) · Nature Methods · doi:10.1038/s41592-024-02272-z · Cited by 439 · cited 1× · see citing works
“In particular, as the machine learning (ML) methods of AlphaFold2 (AF2) [2], RosettaFold [3], OpenFold [4], ESMFold [5], RaptorX [6], and other advanced techniques have reached the stage where single structure prediction of small proteins is robust and reliable, and a current frontier is…”
MethodInferential Structure Determination
Rieping, W., Habeck, M., & Nilges, M. (2005) · Science · doi:10.1126/science.1110428 · Cited by 351 · see citing works
Transient Hoogsteen base pairs in canonical duplex DNA
Nikolova, E. N., Kim, E., Wise, A. A., O’Brien, P., Andricioaei, I., & Al‐Hashimi, H. M. (2011) · Nature · doi:10.1038/nature09775 · Cited by 346 · see citing works
Hyberts, S. G., Goldberg, M. S., Havel, T. F., & Wagner, G. (1992) · Protein Science · doi:10.1002/pro.5560010606 · Cited by 328 · see citing works
Modelling dynamics in protein crystal structures by ensemble refinement
Burnley, B. T., Afonine, P. V., Adams, P. D., & Gros, P. (2012) · eLife · doi:10.7554/elife.00311 · Cited by 291 · see citing works
Conformational states dynamically populated by a kinase determine its function
Xie, T., Saleh, T., Rossi, P., & Kalodimos, C. G. (2020) · Science · doi:10.1126/science.abc2754 · Cited by 266 · see citing works
Chemical exchange in biomacromolecules: Past, present, and future
Palmer, A. G. I. (2014) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2014.01.008 · Cited by 263 · see citing works
SPEACH_AF: Sampling protein ensembles and conformational heterogeneity with Alphafold2
Stein, R. A., & Mchaourab, H. S. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1010483 · Cited by 258 · see citing works
Abyzov, A., Blackledge, M., & Zweckstetter, M. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00774 · Cited by 215 · see citing works
Multi‐state modeling of G‐protein coupled receptors at experimental accuracy
Heo, L., & Feig, M. (2022) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26382 · Cited by 215 · see citing works
Mapping allosteric communications within individual proteins
Wang, J., Jain, A., McDonald, L. R., Gambogi, C., Lee, A. L., & Dokholyan, N. V. (2020) · Nature Communications · doi:10.1038/s41467-020-17618-2 · Cited by 201 · see citing works
Impact of protein conformational diversity on AlphaFold predictions
Saldaño, T., Escobedo, N., Marchetti, J., Zea, D. J., Mac Donagh, J., Velez Rueda, A. J., Gonik, E., Melani, A. G., Novomisky Nechcoff, J., Salas, M. N., et al. (2021) · doi:10.1101/2021.10.27.466189 · Cited by 196 · cited 1× · see citing works
“Subsequently, the proclivity of AF2 to model one of multiple conformational states was also reported for a collection of ~100 apo / holo protein structure pairs [51].”
BackgroundImpact of protein conformational diversity on AlphaFold predictions
Saldaño, T., Escobedo, N., Marchetti, J., Zea, D. J., Mac Donagh, J., Velez Rueda, A. J., Gonik, E., García Melani, A., Novomisky Nechcoff, J., Salas, M. N., et al. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac202 · Cited by 196 · see citing works
Wüthrich, K., & Wagner, G. H. (1975) · FEBS Letters · doi:10.1016/0014-5793(75)80504-7 · Cited by 195 · see citing works
AlphaFold, Artificial Intelligence (AI), and Allostery
Nussinov, R., Zhang, M., Liu, Y., & Jang, H. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c04346 · Cited by 190 · see citing works
Accurate de novo design of membrane-traversing macrocycles
Bhardwaj, G., O’Connor, J., Rettie, S., Huang, Y., Ramelot, T. A., Mulligan, V. K., Alpkilic, G. G., Palmer, J. M., Bera, A. K., Bick, M. J., et al. (2022) · Cell · doi:10.1016/j.cell.2022.07.019 · Cited by 177 · see citing works
Self-citationHow directed evolution reshapes the energy landscape in an enzyme to boost catalysis
Otten, R., Padua, R. A. P., Bunzel, H. A., Nguyen, V., Pitsawong, W., Patterson, M., Sui, S., Perry, S. L., Cohen, A. E., Hilvert, D., et al. (2020) · Science · doi:10.1126/science.abd3623 · Cited by 174 · see citing works
The nuclear Overhauser effect from a quantitative perspective
Vögeli, B. (2013) · Progress in Nuclear Magnetic Resonance Spectroscopy · doi:10.1016/j.pnmrs.2013.11.001 · Cited by 164 · see citing works
Recommendations of the wwPDB NMR Validation Task Force
Montelione, G. T., Nilges, M., Bax, A., Güntert, P., Herrmann, T., Richardson, J. S., Schwieters, C. D., Vranken, W., Vuister, G. W., Wishart, D. S., et al. (2013) · Structure · doi:10.1016/j.str.2013.07.021 · Cited by 162 · see citing works
Self-citationImproving peptide-protein docking with AlphaFold-Multimer using forced sampling
Johansson-Åkhe, I., & Wallner, B. (2022) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2022.959160 · Cited by 162 · see citing works
Enzyme Dynamics from NMR Spectroscopy
Palmer, A. G. I. (2015) · Accounts of Chemical Research · doi:10.1021/ar500340a · Cited by 151 · see citing works
Camacho‐Zarco, A. R., Schnapka, V., Guseva, S., Abyzov, A., Adamski, W., Milles, S., Jensen, M. R., Žı́dek, L., Salvi, N., & Blackledge, M. J. (2022) · Chemical Reviews · doi:10.1021/acs.chemrev.1c01023 · Cited by 148 · see citing works
Protein structure prediction with in-cell photo-crosslinking mass spectrometry and deep learning
Stahl, K., Graziadei, A., Dau, T., Brock, O., & Rappsilber, J. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01704-z · Cited by 145 · see citing works
Protein structure prediction has reached the single-structure frontier
Lane, T. J. (2023) · Nature Methods · doi:10.1038/s41592-022-01760-4 · Cited by 125 · see citing works
AlphaFold2-RAVE: From Sequence to Boltzmann Ranking
Vani, B. P., Aranganathan, A., Wang, D., & Tiwary, P. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00290 · Cited by 120 · see citing works
Inclusion of Thermal Motion in Crystallographic Structures by Restrained Molecular Dynamics
Gros, P., A, W. F. V. G., & Hol, W. G. J. (1990) · Science · doi:10.1126/science.2396108 · Cited by 120 · see citing works
Modeling discrete heterogeneity in X-ray diffraction data by fitting multi-conformers
Bedem, H. V. D., Dhanik, A., Latombe, J., & Deacon, A. M. (2009) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909030613 · Cited by 117 · see citing works
Unveiling invisible protein states with NMR spectroscopy
Alderson, T. R., & Kay, L. E. (2019) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2019.10.008 · Cited by 111 · see citing works
Simultaneous Determination of Protein Structure and Dynamics Using Cryo-Electron Microscopy
Bonomi, M., Pellarin, R., & Vendruscolo, M. (2018) · Biophysical Journal · doi:10.1016/j.bpj.2018.02.028 · Cited by 99 · see citing works
Efficient Ensemble Refinement by Reweighting
Köfinger, J., Stelzl, L. S., Reuter, K., Allande, C., Reichel, K., & Hummer, G. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b01231 · Cited by 94 · see citing works
Design of stimulus-responsive two-state hinge proteins
Praetorius, F., Leung, P. J. Y., Tessmer, M. H., Broerman, A., Demakis, C., Dishman, A. F., Pillai, A., Idris, A., Juergens, D., Dauparas, J., et al. (2023) · Science · doi:10.1126/science.adg7731 · Cited by 90 · see citing works
Sala, D., Hildebrand, P. W., & Meiler, J. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1121962 · Cited by 80 · see citing works
Lorieau, J. L., Louis, J. M., Schwieters, C. D., & Bax, A. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1213801109 · Cited by 79 · see citing works
Riley, B. T., Wankowicz, S. A. M., de Oliveira, S. H. P., van Zundert, G. C. P., Hogan, D. W., Fraser, J. S., Keedy, D. A., & Bedem, H. V. D. (2020) · Protein Science · doi:10.1002/pro.4001 · Cited by 77 · see citing works
Structure and mutagenic analysis of the lipid II flippase MurJ from Escherichia coli
Zheng, S., Sham, L., Rubino, F. A., Brock, K. P., Robins, W. P., Mekalanos, J. J., Marks, D. S., Bernhardt, T. G., & Kruse, A. C. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1802192115 · Cited by 73 · see citing works
Computational approaches to investigating allostery
Schueler‐Furman, O., & Wodak, S. J. (2016) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2016.06.017 · Cited by 72 · see citing works
PDBStat: a universal restraint converter and restraint analysis software package for protein NMR
Tejero, R., Snyder, D. A., Mao, B., Aramini, J. M., & Montelione, G. T. (2013) · Journal of Biomolecular NMR · doi:10.1007/s10858-013-9753-7 · Cited by 68 · see citing works
Self-citationPrediction of multiple conformational states by combining sequence clustering with AlphaFold2Preprint
Wayment-Steele, H. K., Ovchinnikov, S., Colwell, L. J., & Kern, D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.17.512570 · Cited by 66 · see citing works
Aramini, J. M., Hamilton, K., Ma, L.-C., Swapna, G. V. T., Leonard, P. G., Ladbury, J. E., Krug, R. M., & Montelione, G. T. (2014) · Structure · doi:10.1016/j.str.2014.01.010 · Cited by 57 · see citing works
Self-citationObjective identification of residue ranges for the superposition of protein structures
Kirchner, D. K., & Güntert, P. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-170 · Cited by 56 · see citing works
Snyder, D. A., & Montelione, G. T. (2005) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.20402 · Cited by 53 · see citing works
Self-citationLiu, B., Shi, H., & Al‐Hashimi, H. M. (2021) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2021.02.007 · Cited by 53 · see citing works
Huang, Y. J., Zhang, N., Bersch, B., Fidelis, K., Inouye, M., Ishida, Y., Kryshtafovych, A., Kobayashi, N., Kuroda, Y., Liu, G., et al. (2021) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26246 · Cited by 49 · see citing works
Self-citationNMR and computational methods for molecular resolution of allosteric pathways in enzyme complexes
East, K. W., Skeens, E., Cui, J. Y., Belato, H. B., Mitchell, B. P., Hsu, R. V., Batista, V. S., Palermo, G., & Lisi, G. P. (2019) · Biophysical Reviews · doi:10.1007/s12551-019-00609-z · Cited by 45 · see citing works
Chiliveri, S. C., Louis, J. M., Ghirlando, R., & Bax, A. (2021) · Science Advances · doi:10.1126/sciadv.abk2226 · Cited by 43 · see citing works
Beerbaum, M., Ballaschk, M., Erdmann, N., Schnick, C., Diehl, A., Uchańska‐Ziegler, B., Ziegler, A., & Schmieder, P. (2013) · Journal of Biomolecular NMR · doi:10.1007/s10858-013-9777-z · Cited by 40 · see citing works
Inhibitor Bound Dengue NS2B-NS3pro Reveals Multiple Dynamic Binding Modes
Gibbs, A. C., Steele, R. A., Liu, G., Tounge, B. A., & Montelione, G. T. (2018) · Biochemistry · doi:10.1021/acs.biochem.7b01127 · Cited by 40 · see citing works
Self-citationDesign and discovery of metamorphic proteins
Dishman, A. F., & Volkman, B. F. (2022) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2022.102380 · Cited by 36 · see citing works
Wang, X., Jing, X., Deng, Y., Nie, Y., Xu, F., Xu, Y., Zhao, Y., Hunt, J. F., Montelione, G. T., & Szyperski, T. (2019) · FEBS Letters · doi:10.1002/1873-3468.13652 · Cited by 35 · see citing works
Self-citationJoh, N. H., Grigoryan, G., Wu, Y., & DeGrado, W. F. (2017) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2016.0214 · Cited by 28 · see citing works
Automated multiconformer model building for X-ray crystallography and cryo-EM
Wankowicz, S. A., Ravikumar, A., Sharma, S., Riley, B., Raju, A., Hogan, D. W., Flowers, J., van den Bedem, H., Keedy, D. A., & Fraser, J. S. (2024) · eLife · doi:10.7554/elife.90606 · Cited by 28 · see citing works
Boulton, S., Selvaratnam, R., Ahmed, R., & Melacini, G. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7386-6_18 · Cited by 26 · see citing works
Reweighting methods for elucidation of conformation ensembles of proteins
Costa, R. G. L., & Fushman, D. (2022) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2022.102470 · Cited by 24 · see citing works
Papaleo, E., Camilloni, C., Teilum, K., Vendruscolo, M., & Lindorff‐Larsen, K. (2018) · PeerJ · doi:10.7717/peerj.5125 · Cited by 23 · see citing works
Refinement of multiconformer ensemble models from multi-temperature X-ray diffraction data
Du, S., Wankowicz, S. A. M., Yabukarski, F., Doukov, T. I., Herschlag, D., & Fraser, J. S. (2023) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/bs.mie.2023.06.009 · Cited by 22 · see citing works
Snyder, D. A., Grullon, J., Huang, Y. J., Tejero, R., & Montelione, G. T. (2013) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24490 · Cited by 21 · see citing works
Self-citationAn introduction to one- and two-dimensional lineshape analysis of chemically exchanging systems
Waudby, C. A., & Alfonso, I. (2023) · Journal of Magnetic Resonance Open · doi:10.1016/j.jmro.2023.100102 · Cited by 20 · see citing works
Chinnam, N. B., Syed, A., Hura, G. L., Hammel, M., Tainer, J. A., & Tsutakawa, S. E. (2022) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/bs.mie.2022.09.023 · Cited by 19 · see citing works
Banerjee, A., Saha, S., Tvedt, N. C., Yang, L., & Bahar, İ. (2022) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2022.102517 · Cited by 19 · see citing works
Interdomain Dynamics via Paramagnetic NMR on the Highly Flexible Complex Calmodulin/Munc13-1
Karschin, N., Becker, S., & Griesinger, C. (2022) · Journal of the American Chemical Society · doi:10.1021/jacs.2c06611 · Cited by 14 · see citing works
Pro‐islet amyloid polypeptide in micelles contains a helical prohormone segment
DeLisle, C. F., Malooley, A. L., Banerjee, I., & Lorieau, J. L. (2020) · FEBS Journal · doi:10.1111/febs.15253 · Cited by 12 · see citing works
Chasing long‐range evolutionary couplings in the AlphaFold era
Karamanos, T. K. (2023) · Biopolymers · doi:10.1002/bip.23530 · Cited by 11 · see citing works
Elucidating the mechanisms underlying protein conformational switching using NMR spectroscopy
Jain, S., & Sekhar, A. (2022) · Journal of Magnetic Resonance Open · doi:10.1016/j.jmro.2022.100034 · Cited by 10 · see citing works
Improving protein structure prediction using templates and sequence embedding
Wu, F., Jing, X., Luo, X., & Xu, J. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac723 · Cited by 10 · see citing works
Harish, B., Swapna, G. V. T., Kornhaber, G. J., Montelione, G. T., & Carey, J. (2017) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25252 · Cited by 9 · see citing works
Self-citationParamagnetic NMR restraints for the characterization of protein structural rearrangements
Parigi, G., Ravera, E., Piccioli, M., & Luchinat, C. (2023) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2023.102595 · Cited by 6 · see citing works
Güntert, P. (2022) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2022.107189 · Cited by 6 · see citing works
SpecDB: A relational database for archiving biomolecular NMR spectral data
Fraga, K. J., Huang, Y. J., Ramelot, T. A., Swapna, G. V. T., Lashawn Anak Kendary, A., Li, E., Korf, I., & Montelione, G. T. (2022) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2022.107268 · Cited by 6 · see citing works
Self-citationOmar, H., Hein, A., Cole, C. A., & Valafar, H. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.806584 · Cited by 2 · see citing works
Flagged first, then by citations
1 of the 80 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins
Agarwal, V., & McShan, A. C. (2024) · Nature Chemical Biology · doi:10.1038/s41589-024-01638-w · Cited by 155 · see citing works
“The use of experimental data, especially SAXS, NMR and cryo-EM, has also been described to guide modeling of ensembles and alternative conformations 71,82,108 .”
MethodAlphaFold prediction of structural ensembles of disordered proteins
Brotzakis, Z. F., Zhang, S., Murtada, M. H., & Vendruscolo, M. (2025) · Nature Communications · doi:10.1038/s41467-025-56572-9 · Cited by 99 · see citing works
Ma, M., Cui, J., Li, C., Blecker, C. S., & Zheng, J. (2024) · Food Hydrocolloids · doi:10.1016/j.foodhyd.2024.110973 · Cited by 29 · see citing works
Wankowicz, S. A. M., & Fraser, J. S. (2024) · IUCrJ · doi:10.1107/s2052252524005098 · Cited by 27 · see citing works
Ellaway, J. I. J., Anyango, S., Nair, S. S., Zaki, H. A., Nadzirin, N., Powell, H. R., Gutmanas, A., Váradi, M., & Velankar, S. S. (2024) · Structural Dynamics · doi:10.1063/4.0000251 · Cited by 27 · see citing works
Explaining Conformational Diversity in Protein Families through Molecular Motions
Lombard, V., Grudinin, S., & Laine, É. (2024) · Scientific Data · doi:10.1038/s41597-024-03524-5 · Cited by 19 · see citing works
NMR tools to detect protein allostery
Gampp, O., Kadavath, H., & Riek, R. (2024) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2024.102792 · Cited by 13 · see citing works
A fully automated benchmarking suite to compare macromolecular complexes
Studer, G., Robin, X., Bienert, S., Durairaj, J., Škrinjar, P., Tauriello, G., Waterhouse, A. M., & Schwede, T. (2026) · Nature Methods · doi:10.1038/s41592-025-02973-z · Cited by 10 · see citing works
“Finally, considerations about flexibility and disorder, involving considerably different sets of methods 55,56 , are out of the scope of this manuscript.”
Restraint validation of biomolecular structures determined by NMR in the Protein Data Bank
Baskaran, K., Płoskoń, E., Tejero, R., Yokochi, M., Harrus, D., Liang, Y., Peisach, E., Persikova, I., Ramelot, T. A., Sekharan, M. R., et al. (2024) · Structure · doi:10.1016/j.str.2024.02.011 · Cited by 10 · see citing works
Self-citationGenerating Multistate Conformations of P-type ATPases with a Conditional Diffusion Model
Xu, J., & Wang, Y. (2024) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.4c01519 · Cited by 9 · see citing works
Statistical Thermodynamics of the Protein Ensemble: Mediating Function and Evolution
Hilser, V. J., Wrabl, J. O., Millard, C. E., Schmitz, A., Brantley, S. J., Pearce, M., Rehfus, J., Russo, M. M., & Voortman‐Sheetz, K. (2025) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-061824-104900 · Cited by 9 · see citing works
Modeling Alternative Conformational States in CASP16
Dube, N., Ramelot, T. A., Benavides, T. L., Huang, Y. J., Moult, J., Kryshtafovych, A., & Montelione, G. T. (2025) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.70065 · Cited by 10 · see citing works
Self-citationSeaMoon: From protein language models to continuous structural heterogeneity
Lombard, V., Timsit, D., Grudinin, S., & Laine, E. (2025) · Structure · doi:10.1016/j.str.2025.06.010 · Cited by 8 · see citing works
Lesovoy, D., Roshchin, K., Sala, B. M., Sandalova, T., Achour, A., Agback, T., Agback, P., & Orekhov, V. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26188917 · Cited by 6 · see citing works
Lesovoy, D., Roshchin, K., Sala, B. M., Sandalova, T., Achour, A., Agback, T., Orekhov, V., & Agback, P. (2025) · doi:10.1101/2025.02.07.637034 · Cited by 6 · see citing works
Assessing the Performance of BioEmu in Understanding Protein Dynamics
Zha, J., Li, N., Li, M., Liu, X., Zhu, R., Feng, L., Lu, X., & Zhang, J. (2026) · International Journal of Molecular Sciences · doi:10.3390/ijms27062896 · Cited by 4 · see citing works
Pennington, H. N., Prahadeesh, K., Mulvihill, Q. M., Shin, S., Im, W., & Lee, J. (2026) · Biophysical Journal · doi:10.1016/j.bpj.2026.01.049 · Cited by 2 · see citing works
SuAVE-Scatter: A Module for Integrating Simulations and SAXS/SANS Analyses
Caetano, D. L. Z., Santo, A. A. D. E., Diane Correia de Araújo, L. I. M. A., Santos, D. E. S., & Soares, T. A. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c00402 · Cited by 2 · see citing works
Şulea, T. A., Martin, E. C., Bugeac, C. A., Bectaș, F. S., Iacob, A.-L., Spiridon, L. N., & Petrescu, A. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26020500 · Cited by 2 · see citing works
Senet, P., Guzzo, A., Delarue, P., Laforge, C., Maisuradze, G. G., Heydel, J.-M., Neiers, F., & Nicolaï, A. (2026) · Chemical Science · doi:10.1039/d5sc06411b · Cited by 3 · see citing works
Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data BankPreprint
Baskaran, K., Płoskoń, E., Tejero, R., Yokochi, M., Harrus, D., Liang, Y., Peisach, E., Persikova, I., Ramelot, T. A., Sekharan, M. R., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.15.575520 · Cited by 1 · see citing works
Self-citationRestraint Validation of Biomolecular Structures Determined By NMR in the Protein Data BankPreprint
Baskaran, K., Płoskoń, E., Tejero, R., Yokochi, M., Harrus, D., Liang, Y., Peisach, E., Persikova, I., Ramelot, T. A., Sekharan, M. R., et al. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4507732
Self-citationAlphaFold-Metainference: Prediction of Structural Ensembles of Disordered ProteinsPreprint
Brotzakis, Z. F., Zhang, S., Murtada, M. H., & Vendruscolo, M. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.09.622758
Genomic and Proteomic Data Analysis for Population Health
Karri, R. L., Prakash, A., Sau, S., Ganesan, S., Nellore, J., & Singh, S. (2025) · doi:10.1002/9781394386659.ch9
Mitjavila-Domènech, N., Díaz‐Holguín, A., Hu, H., Kahlous, N. A., de Vaca, I. C., Wallner, B., & Carlsson, J. (2026) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6c00034
Assembly-Induced Conformational Switching in a Simple Iodinated Furan-2,5-dicarboxanilide
Cao, J., Lei, Z., Duan, J., & Yan, X. (2026) · Synlett · doi:10.1055/a-2919-5803
- Authors
- Ramelot, T. A., Tejero, R., & Montelione, G. T.
- Affiliations
- Rensselaer Polytechnic Institute (US)
- Corresponding author
- Ramelot, Theresa A.
- Montelione, Gaetano T.
- Venue
- Current Opinion in Structural Biology
- Publisher
- Elsevier BV
- Published
- 2023-12
- Volume
- 83
- Pages
- 102703
- ISSN
- 0959-440X (ISSN-L)
- PMC
- PMC10841472
- OpenAlex
- W4387128962
- Cited by
- 26
- References
- 80
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 10 · 2023: 2
- FWCI
- 0.69
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Current Opinion in Structural Biology (publishedVersion, cc-by-nc-nd)
- ChemRxiv (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (R35-GM141818)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Physical Sciences › Chemistry › Spectroscopy › Advanced NMR Techniques and Applications
- Keywords
- protein conformational ensembles, biomolecular dynamics, NMR structure, molecular dynamics simulation, machine learning, data archiving, structural annotation
- MeSH terms
- Molecular Conformation, Magnetic Resonance Spectroscopy, Protein Conformation, Proteins, Molecular Dynamics Simulation
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
