Structure of cytoplasmic ring of nuclear pore complex by integrative cryo-EM and AlphaFold
Open accessAbstract
INTRODUCTION The nuclear pore complex (NPC) is the molecular conduit in the nuclear membrane of eukaryotic cells that regulates import and export of biomolecules between the nucleus and the cytosol, with vertebrate NPCs ~110 to 125 MDa in molecular mass and ~120 nm in diameter. NPCs are organized into four main rings: the cytoplasmic ring (CR) at the cytosolic side, the inner ring and the luminal ring on the plane of the nuclear membrane, and the nuclear ring facing the nucleus. Each ring possesses an approximate eightfold symmetry and is composed of multiple copies of different nucleoporins. NPCs have been implicated in numerous biological processes, and their dysfunctions are associated with a growing number of serious human diseases. However, despite pioneering studies from many groups over the past two decades, we still lack a full understanding of NPCs’ organization, dynamics, and complexity. RATIONALE We used the Xenopus laevis oocyte as a model system for the structural characterization because each oocyte possesses a large number of NPC particles that can be visualized on native nuclear membranes without the aid of detergent extraction. We used single-particle cryo–electron microscopy (cryo-EM) analysis on data collected at different stage tilt angles for three-dimensional reconstruction and structure prediction with AlphaFold for model building. RESULTS We reconstructed the CR map of X. laevis NPC at 6.9 and 6.7 Å resolutions for the full CR protomer and a core region, respectively, and predicted the structures of the individual nucleoporins using AlphaFold because no high-resolution models of X. laevis Nups were available. For any ambiguous subunit interactions, we also predicted complex structures, which further guided model fitting of the CR protomer. We placed the nucleoporin or complex structures into the CR density to obtain an almost full CR atomic model, composed of the inner and outer Y-complexes, two copies of Nup205, two copies of the Nup214-Nup88-Nup62 complex, one Nup155, and five copies of Nup358. In particular, we predicted the largest protein in the NPC, Nup358, as having an S-shaped globular domain, a coiled-coil domain, and a largely disordered C-terminal region containing phenylalanine-glycine (FG) repeats previously shown to form a gel-like condensate phase for selective cargo passage. Four of the Nup358 copies clamp around the inner and outer Y-complexes to stabilize the CR, and the fifth Nup358 situates in the center of the cluster of clamps. AlphaFold also predicted a homo-oligomeric, likely specifically pentameric, coiled-coil structure of Nup358 that may provide the avidity for Nup358 recruitment to the NPC and for lowering the threshold for Nup358 condensation in NPC biogenesis. CONCLUSION Our studies offer an example of integrative cryo-EM and structure prediction as a general approach for attaining more precise models of megadalton protein complexes from medium-resolution density maps. The more accurate and almost complete model of the CR presented here expands our understanding of the molecular interactions in the NPC and represents a substantial step forward toward the molecular architecture of a full NPC, with implications for NPC function, biogenesis, and regulation. Cryo-EM structure of the cytoplasmatic ring of the nuclear pore complex from X. laevis . The 6.9 Å map was generated with single-particle cryo-EM, and the model was built with AlphaFold structure prediction. The secondary structural elements guided EM map fitting, resulting in an almost complete model of the complex. The approach allowed the identification of five copies of Nup358 and a second copy of the trimeric Nup214-Nup88-Nup62 complex.
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
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?
Numerous areas within the life sciences have experienced considerable impact due to the availability of accurately predicted protein structures, notably structure determination, structure-based drug discovery, and structural bioinformatics.
“As a result, numerous areas within the life sciences have experienced considerable impact due to the availability of accurately predicted protein structures. The primary domains notably affected include structure determination, structure-based drug discovery, and structural bioinformatics (11–13).”
From AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences (2024) · cites this paper as [12]
The Conclusion (page not provided) says AlphaFold predictions enabled more precise modeling of the nuclear pore complex and could assist in determining other structures. This supports the structure-determination example, but the paper does not establish considerable impact across the life sciences or address structure-based drug discovery or structural bioinformatics as affected domains. (LLM, conf=0.88)
Experimental — accuracy not yet measuredUsing AF models in structure determination protocols reduces time and effort compared with ab initio model building.
“The use of AF models in structure determination protocols has shown to reduce the time and effort required relative to ab initio model building68–70”
From The power and pitfalls of AlphaFold2 for structure prediction beyond rigid globular proteins (2024) · cites this paper as [68]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
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
<i>PHENIX</i> : a comprehensive Python-based system for macromolecular structure solution
Adams, P. D., Afonine, P. V., Bunkóczi, G., Chen, V. B., Davis, I. W., Echols, N., Headd, J. J., Hung, L.-W., Kapral, G. J., Grosse-Kunstleve, R. W., et al. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444909052925 · Cited by 23,716 · see citing works
Inference of macromolecular assemblies from crystalline state.
Krissinel, E., & Henrick, K. (2007) · Journal of Molecular Biology · doi:10.1016/j.jmb.2007.05.022 · Cited by 10,189 · see citing works
ColabFold - Making protein folding accessible to all
Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., & Steinegger, M. (2021) · doi:10.1101/2021.08.15.456425 · Cited by 9,391 · see citing works
cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination
Punjani, A., Rubinstein, J. L., Fleet, D. J., & Brubaker, M. A. (2017) · Nature Methods · doi:10.1038/nmeth.4169 · Cited by 9,168 · see citing works
MotionCor2 - anisotropic correction of beam-induced motion for improved cryo-electron microscopy
Zheng, S., Palovcak, E. J., Armache, J., Verba, K., Cheng, Y.-F., & Agard, D. (2017) · Nature Methods · doi:10.1038/nmeth.4193 · Cited by 7,678 · see citing works
UCSF ChimeraX: Meeting modern challenges in visualization and analysis
Goddard, T. D., Huang, C. C., Meng, E. C., Pettersen, E. F., Couch, G. S., Morris, J. H., & Ferrin, T. E. (2018) · Protein Science · doi:10.1002/pro.3235 · Cited by 5,267 · see citing works
CTFFIND4: Fast and accurate defocus estimation from electron micrographs
Rohou, A. L., & Grigorieff, N. (2015) · Journal of Structural Biology · doi:10.1016/j.jsb.2015.08.008 · Cited by 4,926 · see citing works
MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets
Steinegger, M., & Söding, J. (2017) · Nature Biotechnology · doi:10.1038/nbt.3988 · Cited by 4,840 · see citing works
New tools for automated high-resolution cryo-EM structure determination in RELION-3
Zivanov, J., Nakane, T., Forsberg, B., Kimanius, D., Hagen, W., Lindahl, E., & Scheres, S. (2018) · eLife · doi:10.7554/elife.42166 · Cited by 4,377 · see citing works
The EMBL-EBI search and sequence analysis tools APIs in 2019
Madeira, F., Park, Y. M., Lee, J., Buso, N., Gur, T., Madhusoodanan, N., Basutkar, P., Tivey, A. R. N., Potter, S. C., Finn, R. D., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz268 · Cited by 4,167 · see citing works
Predicting coiled coils from protein sequences.
Lupas, A., Van Dyke, M., & Stock, J. (1991) · Science · doi:10.1126/science.252.5009.1162 · Cited by 3,953 · see citing works
Protein complex prediction with AlphaFold-Multimer
Evans, R., O’Neill, M., Pritzel, A., Antropova, N., Senior, A., Green, T., Žídek, A., Bates, R., Blackwell, S., Yim, J., et al. (2021) · doi:10.1101/2021.10.04.463034 · Cited by 3,808 · see citing works
Gctf: Real-time CTF determination and correction
Zhang, K. (2015) · Journal of Structural Biology · doi:10.1016/j.jsb.2015.11.003 · Cited by 3,372 · see citing works
Highly accurate protein structure prediction for the human proteome
Tunyasuvunakool, K., Adler, J., Wu, Z., Green, T., Zielinski, M., Žídek, A., Bridgland, A., Cowie, A., Meyer, C., Laydon, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03828-1 · Cited by 3,025 · cited 2× · see citing works
“The AlphaFold structures in this study were mainly generated from the AlphaFold2 implementation in the ColabFold notebooks (49) running onGoogle Colaboratory (21, 22), using the default settings with Amber relaxation (msa_method=mmseqs2, homooligomer=1, pair_mode=unpaired, max_msa=512:1024, subsample_msa=True, num_rel…”
MethodKühlbrandt, W. (2014) · Science · doi:10.1126/science.1251652 · Cited by 1,325 · see citing works
Collaboration gets the most out of software
Morin, A., Eisenbraun, B., Key, J., Sanschagrin, P. C., Timony, M. A., Ottaviano, M., & Piotr Sliz, A. (2013) · eLife · doi:10.7554/elife.01456 · Cited by 1,034 · see citing works
Frey, S., Richter, R. P., & Görlich, D. (2006) · Science · doi:10.1126/science.1132516 · Cited by 691 · see citing works
Stereochemically restrained refinement of macromolecular structures
Hendrickson, W. A. (1985) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/0076-6879(85)15021-4 · Cited by 606 · see citing works
A general amphipathic α-helical motif for sensing membrane curvature
Drin, G., Casella, J.-F., Gautier, R., Boehmer, T., Schwartz, T., & Antonny, B. (2007) · Nature Structural & Molecular Biology · doi:10.1038/nsmb1194 · Cited by 572 · see citing works
Computed structures of core eukaryotic protein complexes
Humphreys, I. R., Pei, J., Baek, M., Krishnakumar, A., Anishchenko, I., Ovchinnikov, S., Zhang, J., Ness, T. J., Banjade, S., Bagde, S. R., et al. (2021) · Science · doi:10.1126/science.abm4805 · Cited by 542 · see citing works
Wu, J., Matunis, M. J., Kraemer, D. M., et al. (1995) · Journal of Biological Chemistry · doi:10.1074/jbc.270.23.14209 · Cited by 484 · see citing works
Integrative structure and functional anatomy of a nuclear pore complex
Kim, S. J., Fernández-Martı́nez, J., Nudelman, I., Shi, Y., Zhang, W., Raveh, B., Herricks, T., Slaughter, B. D., Hogan, J. A., Upla, P., et al. (2018) · Nature · doi:10.1038/nature26003 · Cited by 469 · see citing works
The Structure of the Nuclear Pore Complex (An Update)
Lin, D. H., & Hoelz, A. (2019) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-062917-011901 · Cited by 449 · see citing works
In situ structural analysis of the human nuclear pore complex
von Appen, A., Kosiński, J., Sparks, L., Ori, A., DiGuilio, A. L., Vollmer, B., Mackmull, M., Banterle, N., Parca, L., Kastritis, P. L., et al. (2015) · Nature · doi:10.1038/nature15381 · Cited by 411 · see citing works
Akey, C. W., & Radermacher, M. (1993) · The Journal of Cell Biology · doi:10.1083/jcb.122.1.1 · Cited by 407 · see citing works
The Nuclear Pore Complex as a Flexible and Dynamic Gate
Knockenhauer, K. E., & Schwartz, T. (2016) · Cell · doi:10.1016/j.cell.2016.01.034 · Cited by 399 · see citing works
Components of Coated Vesicles and Nuclear Pore Complexes Share a Common Molecular Architecture
Devos, D. P., Dokudovskaya, S., Alber, F., Williams, R., Chait, B. T., Šali, A., & Rout, M. P. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020380 · Cited by 390 · see citing works
Artificial intelligence reveals nuclear pore complexity
Mosalaganti, S., Obarska-Kosinska, A., Siggel, M., Turonova, B., Zimmerli, C. E., Buczak, K., Schmidt, F. H., Margiotta, E., Mackmull, M.-T., Hagen, W., et al. (2021) · doi:10.1101/2021.10.26.465776 · Cited by 355 · see citing works
AI-based structure prediction empowers integrative structural analysis of human nuclear pores
Mosalaganti, S., Obarska-Kosinska, A., Siggel, M., Taniguchi, R., Turoňová, B., Zimmerli, C. E., Buczak, K., Schmidt, F. H., Margiotta, E., Mackmull, M.-T., et al. (2022) · Science · doi:10.1126/science.abm9506 · Cited by 355 · see citing works
Integrated Structural Analysis of the Human Nuclear Pore Complex Scaffold
Bui, K. H., von Appen, A., DiGuilio, A. L., Ori, A., Sparks, L., Mackmull, M., Bock, T., Hagen, W. J. H., Andrés‐Pons, A., Glavy, J. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.055 · Cited by 351 · see citing works
Ori, A., Banterle, N., Iskar, M., Andrés‐Pons, A., Escher, C., Bui, K. H., Sparks, L., Solis‐Mezarino, V., Rinner, O., Peer Bork, B., et al. (2013) · Molecular Systems Biology · doi:10.1038/msb.2013.4 · Cited by 308 · see citing works
Architecture of the symmetric core of the nuclear pore
Lin, D. H., Stuwe, T., Schilbach, S., Rundlet, E. J., Perriches, T., Mobbs, G. W., Fan, Y., Thierbach, K., Huber, F. M., Collins, L. N., et al. (2016) · Science · doi:10.1126/science.aaf1015 · Cited by 266 · see citing works
Measuring the effects of particle orientation to improve the efficiency of electron cryomicroscopy
Naydenova, K., & Russo, C. J. (2017) · Nature Communications · doi:10.1038/s41467-017-00782-3 · Cited by 216 · see citing works
Structural Evidence for Common Ancestry of the Nuclear Pore Complex and Vesicle Coats
Brohawn, S. G., Leksa, N. C., Spear, E. D., et al. (2008) · Science · doi:10.1126/science.1165886 · Cited by 215 · see citing works
Interactions and structure of the nuclear pore complex revealed by cryo-electron microscopy.
Akey, C. W. (1989) · The Journal of Cell Biology · doi:10.1083/jcb.109.3.955 · Cited by 193 · see citing works
Structure and gating of the nuclear pore complex
Eibauer, M., Pellanda, M., Turgay, Y., Dubrovsky-Gaupp, A., Wild, A., & Medalia, O. (2015) · Nature Communications · doi:10.1038/ncomms8532 · Cited by 185 · see citing works
Comprehensive structure and functional adaptations of the yeast nuclear pore complex
Akey, C. W., Singh, D., Ouch, C., Echeverria, I., Nudelman, I., Varberg, J. M., Yu, Z., Fang, F., Shi, Y., Wang, J., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.015 · Cited by 180 · see citing works
Bernad, R., van der Velde, H., Fornerod, M. W. J., & Pickersgill, H. (2004) · Molecular and Cellular Biology · doi:10.1128/mcb.24.6.2373-2384.2004 · Cited by 177 · see citing works
Architecture of a Coat for the Nuclear Pore Membrane
Hsia, K., Stavropoulos, P., Blobel, G., & Hoelz, A. (2007) · Cell · doi:10.1016/j.cell.2007.11.038 · Cited by 134 · see citing works
Architecture of the fungal nuclear pore inner ring complex
Stuwe, T., Bley, C. J., Thierbach, K., Petrovic, S., Schilbach, S., Mayo, D. J., Perriches, T., Rundlet, E. J., Jeon, Y. E., Collins, L. N., et al. (2015) · Science · doi:10.1126/science.aac9176 · Cited by 130 · see citing works
A Fence-like Coat for the Nuclear Pore Membrane
Debler, E., Ma, Y., Seo, H., Hsia, K., Noriega, T. R., Blobel, G., & Hoelz, A. (2008) · Molecular Cell · doi:10.1016/j.molcel.2008.12.001 · Cited by 122 · see citing works
Berke, I. C., Boehmer, T., Blobel, G., & Schwartz, T. (2004) · The Journal of Cell Biology · doi:10.1083/jcb.200408109 · Cited by 122 · see citing works
Crystal structure of the metazoan Nup62•Nup58•Nup54 nucleoporin complex
Chug, H., Trakhanov, S. D., Hülsmann, B. B., Pleiner, T., & Görlich, D. (2015) · Science · doi:10.1126/science.aac7420 · Cited by 118 · see citing works
Nuclear Pores Assemble from Nucleoporin Condensates During Oogenesis
Hampoelz, B., Schwarz, A., Ronchi, P., Bragulat-Teixidor, H., Tischer, C., Gáspár, I., Ephrussi, A., Schwab, Y., & Beck, M. (2019) · Cell · doi:10.1016/j.cell.2019.09.022 · Cited by 111 · see citing works
Natively Unfolded FG Repeats Stabilize the Structure of the Nuclear Pore Complex
Onischenko, E. A., Tang, J. H., Andersen, K. R., Knockenhauer, K. E., Vallotton, P., Derrer, C. P., Kralt, A., Mugler, C. F., Chan, L. Y., Schwartz, T., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.033 · Cited by 110 · see citing works
A novel nuclear pore protein Nup82p which specifically binds to a fraction of Nsp1p.
Grandi, P., Emig, S., Weise, C., et al. (1995) · The Journal of Cell Biology · doi:10.1083/jcb.130.6.1263 · Cited by 102 · see citing works
One Ring to Rule them All? Structural and Functional Diversity in the Nuclear Pore Complex
Fernández-Martı́nez, J., & Rout, M. P. (2021) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2021.01.003 · Cited by 95 · see citing works
Functional Characterization of a Nup159p-containing Nuclear Pore Subcomplex
Belgareh‐Touzé, N., Snay-Hodge, C., Pasteau, F., et al. (1998) · Molecular Biology of the Cell · doi:10.1091/mbc.9.12.3475 · Cited by 90 · see citing works
The Multiple Faces of Disordered Nucleoporins
Lemke, E. A. (2016) · Journal of Molecular Biology · doi:10.1016/j.jmb.2016.01.002 · Cited by 86 · see citing works
From integrative structural biology to cell biology
Šali, A. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.100743 · Cited by 84 · see citing works
Molecular basis for Nup37 and ELY5/ELYS recruitment to the nuclear pore complex
Bilokapić, S., & Schwartz, T. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1205151109 · Cited by 72 · see citing works
Bailer, S. M., Balduf, C., & Hurt, E. (2001) · Molecular and Cellular Biology · doi:10.1128/mcb.21.23.7944-7955.2001 · Cited by 69 · see citing works
Kim, S. J., Fernández-Martı́nez, J., Sampathkumar, P., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m114.040915 · Cited by 67 · see citing works
Molecular architecture of the luminal ring of the Xenopus laevis nuclear pore complex
Zhang, Y., Li, S., Zeng, C., Huang, G., Zhu, X., Wang, Q., Wang, K., Zhou, Q., Yan, C., Zhang, W., et al. (2020) · Cell Research · doi:10.1038/s41422-020-0320-y · Cited by 64 · see citing works
Huang, G., Zhang, Y., Zhu, X., Zeng, C., Wang, Q., Zhou, Q., Tao, Q., Liu, M., Lei, J., Yan, C., et al. (2020) · Cell Research · doi:10.1038/s41422-020-0319-4 · Cited by 57 · see citing works
Nordeen, S. A., Turman, D. L., & Schwartz, T. (2020) · Nature Communications · doi:10.1038/s41467-020-19885-5 · Cited by 41 · see citing works
Crystal Structure of the N-Terminal Domain of Nup358/RanBP2
Kassube, S. A., Stuwe, T., Lin, D. H., Antonuk, C. D., Napetschnig, J., Blobel, G., & Hoelz, A. (2012) · Journal of Molecular Biology · doi:10.1016/j.jmb.2012.08.026 · Cited by 40 · see citing works
Cryo-EM structure of the Inner Ring from <i>Xenopus laevis</i> Nuclear Pore Complex
Huang, G., Zhan, X., Zeng, C., Liang, K., Zhu, X., Zhao, Y., Wang, P., Wang, Q., Zhou, Q., Tao, Q., et al. (2021) · doi:10.1101/2021.11.13.468242 · Cited by 33 · see citing works
Tai, L., Zhu, Y., Ren, H., Huang, X., Zhang, C., & Sun, F. (2022) · Protein & Cell · doi:10.1007/s13238-021-00895-y · Cited by 32 · see citing works
Chiu, W., Schmid, M. F., Pintilie, G. D., & Lawson, C. L. (2021) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2021.100560 · Cited by 32 · see citing works
The coming-of-age of nucleocytoplasmic transport in motor neuron disease and neurodegeneration
Ferreira, P. A. (2019) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-019-03029-0 · Cited by 31 · see citing works
Shibata, A., Kasai, M., Hoshino, A., et al. (2021) · Neuroscience Letters · doi:10.1016/j.neulet.2021.136173 · Cited by 12 · see citing works
Deshmukh, P., Singh, A., Khuperkar, D., et al. (2021) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2021.04.027 · Cited by 12 · see citing works
Tai, L., Zhu, Y., Ren, H., Huang, X., Zhang, C., & Sun, F. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.10.468011 · Cited by 3 · see citing works
The Quest for the Blueprint of the Nuclear Pore Complex
Glavy, J. S. (2019) · The Protein Journal · doi:10.1007/s10930-019-09858-z · Cited by 3 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- [39]Bley CJ, Architecture of the cytoplasmic face of the nuclear pore. bioRxiv [Preprint] (2021). 10.1101/2021.10.26.465790. PMC9348906 35679405 · DOI
- [57]Russo CJ, Passmore LA, Electron microscopy: Ultrastable gold substrates for electron cryomicroscopy. Science 346, 1377– 1380 (2014). doi: 10.1126/science.1259530 25504723 PMC4296556 · DOI
Cited by
Sorted by citations
Varadi, M., Bertoni, D., Magana, P., Paramval, U., Pidruchna, I., Radhakrishnan, M., Tsenkov, M., Nair, S., Mirdita, M., Yeo, J., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkad1011 · Cited by 2,052 · see citing works
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 AlphaFold models in structure-determination protocols has been shown to reduce the time and effort required relative to ab initio model building 68–70 .”
MethodUnderstanding a protein fold: The physics, chemistry, and biology of α-helical coiled coils
Woolfson, D. N. (2023) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2023.104579 · Cited by 106 · see citing works
“…important biophysical properties such as coiled-coil dynamics, exchange, and turnover; moving beyond coiled coils as simple oligomerization domains and spacers and exploring the complexity of coiled-coil architectures in the context of larger and functional biological assemblies (235, 240).”
Varadi, M., Bordin, N., Orengo, C., & Velankar, S. (2023) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2023.102543 · Cited by 29 · see citing works
Brookes, E., Rocco, M., Vachette, P., & Trewhella, J. (2023) · Journal of Applied Crystallography · doi:10.1107/s1600576723005344 · Cited by 21 · see citing works
Zhang, Y., Zhang, Z., Kagaya, Y., Terashi, G., Zhao, B., Xiong, Y., & Kihara, D. (2025) · Communications Biology · doi:10.1038/s42003-025-08783-5 · Cited by 19 · see citing works
“Since the release of AF2, it has been used for many practical applications in biology 12 , including for molecular replacement in X-ray crystallography 13 , structure modeling for cryo-electron microscopy (cryo-EM) maps 14 – 16 , and structure-based drug design 1 7,18 .”
Generative artificial intelligence performs rudimentary structural biology modeling
Ille, A. M., Markosian, C., Burley, S. K., Mathews, M. B., Pasqualini, R., & Arap, W. (2024) · Scientific Reports · doi:10.1038/s41598-024-69021-2 · Cited by 16 · see citing works
- Authors
- Fontana, P., Dong, Y., Pi, X., Tong, A. B., Hecksel, C. W., Wang, L., Fu, T.-M., Bustamante, C., & Wu, H.
- Affiliations
- Boston Children's Hospital (US)
- Jason L. Choy Laboratory of Single-Molecule Biophysics, Institute for Quantitative Biosciences-QB3, and Chemistry Graduate Group, University of California, Berkeley, CA 94720, USA.
- SLAC National Accelerator Laboratory (US)
- QB3 (US)
- Corresponding author
- Fontana, Pietro
- Dong, Ying
- Pi, Xiong
- Wu, Hao
- ORCID
- Venue
- Science
- Published
- 2022-06-10
- Volume
- 376
- Issue
- 6598
- Pages
- eabm9326-eabm9326
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC10054137
- OpenAlex
- W4282918855
- Cited by
- 195
- References
- 66
- Citations by year
- 2026: 26 · 2025: 37 · 2024: 46 · 2023: 63 · 2022: 22 · 2012: 1
- FWCI
- 13.72
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
- Cancer Research Institute
- Massachusetts Green High Performance Computing Center
- National Institutes of Health (DE-AC02–05CH11231)
- National Institute of General Medical Sciences (U24GM129541, R01GM032543)
- Basic Energy Sciences (DE-AC02, DE-AC02-05CH11231., AC02–05CH11231)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (DP1HD087988)
- SLAC National Accelerator Laboratory (DE-AC02-05-CH11231)
- Common Fund
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Nuclear Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Advanced Electron Microscopy Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Keywords
- nuclear pore complex, nucleoporins, Nup358, FG repeats, NUP205, NUP155, Xenopus oocytes, nuclear envelope, protein structure prediction, AlphaFold
- MeSH terms
- Animals, Artificial Intelligence, Cytosol, Oocytes, Protein Conformation, Software, Xenopus laevis, Cryoelectron Microscopy, Protein Subunits, Nuclear Pore, Nuclear Pore Complex Proteins, Xenopus Proteins
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
