Dictionary of protein secondary structure: Pattern recognition of hydrogen‐bonded and geometrical features
Open accessAbstract
For a successful analysis of the relation between amino acid sequence and protein structure, an unambiguous and physically meaningful definition of secondary structure is essential. We have developed a set of simple and physically motivated criteria for secondary structure, programmed as a pattern‐recognition process of hydrogen‐bonded and geometrical features extracted from x‐ray coordinates. Cooperative secondary structure is recognized as repeats of the elementary hydrogen‐bonding patterns “turn” and “bridge.” Repeating turns are “helices,” repeating bridges are “ladders,” connected ladders are “sheets.” Geometric structure is defined in terms of the concepts torsion and curvature of differential geometry. Local chain “chirality” is the torsional handedness of four consecutive C α positions and is positive for right‐handed helices and negative for ideal twisted β‐sheets. Curved pieces are defined as “bends.” Solvent “exposure” is given as the number of water molecules in possible contact with a residue. The end result is a compilation of the primary structure, including SS bonds, secondary structure, and solvent exposure of 62 different globular proteins. The presentation is in linear form: strip graphs for an overall view and strip tables for the details of each of 10.925 residues. The dictionary is also available in computer‐readable form for protein structure prediction work.
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pDockQ was created by fitting a sigmoidal curve to the DockQ scores using the average interface plDDT multiplied with the logarithm of the number of interface contacts.
“This score is created by fitting a sigmoidal curve (Fig. 2c) using “curve_fit” from SciPy v.1.4.156, to the DockQ scores using the average interface plDDT multiplied with the logarithm of the number of interface contacts, with the following sigmoidal equation:”
From Improved prediction of protein-protein interactions using AlphaFold2 (2021) · cites this paper as [56]
After about 300 ps of simulation, a kink of the helix around the E329 position with insertion of a turn was evidenced by DSSP analysis.
“After about 300 ps of simulation the kink of the helix around the E329 position, with insertion of a turn, was evidenced by the DSSP analysis (58).”
From Structural and Functional Characterization of the Aryl Hydrocarbon Receptor Ligand Binding Domain by Homology Modeling and Mutational Analysis (2007) · cites this paper as [58]
Cites
The protein data bank: A computer-based archival file for macromolecular structures
Bernstein, F. C., Koetzle, T. F., Williams, G. J. B., Meyer, E. F., Brice, M. D., Rodgers, J. R., Kennard, O., Shimanouchi, T., & Tasumi, M. (1977) · Journal of Molecular Biology · doi:10.1016/s0022-2836(77)80200-3 · Cited by 8,582 · see citing works
The interpretation of protein structures: Estimation of static accessibility
Lee, B., & Richards, F. M. (1971) · Journal of Molecular Biology · doi:10.1016/0022-2836(71)90324-x · Cited by 5,884 · see citing works
Water: A Comprehensive Treatise
Franks, F. (1979) · Springer eBooks · doi:10.1007/978-1-4684-8018-4 · Cited by 4,065 · see citing works
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 · see citing works
Structure of the haemagglutinin membrane glycoprotein of influenza virus at 3 Å resolution
Wilson, I. A., Skehel, J. J., & Wiley, D. C. (1981) · Nature · doi:10.1038/289366a0 · Cited by 2,535 · see citing works
Estimation of globular protein secondary structure from circular dichroism
Provencher, S. W., & Gloeckner, J. (1981) · Biochemistry · doi:10.1021/bi00504a006 · Cited by 2,167 · see citing works
Environment and exposure to solvent of protein atoms. Lysozyme and insulin
Shrake, A., & Rupley, J. A. (1973) · Journal of Molecular Biology · doi:10.1016/0022-2836(73)90011-9 · Cited by 1,387 · see citing works
Chou, P. Y., & Fasman, G. D. (1977) · Journal of Molecular Biology · doi:10.1016/0022-2836(77)90094-8 · Cited by 957 · see citing works
Structural invariants in protein folding
Chothia, C. (1975) · Nature · doi:10.1038/254304a0 · Cited by 872 · see citing works
Configurations of Polypeptide Chains With Favored Orientations Around Single Bonds
Pauling, L. C., & Corey, R. B. (1951) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.37.11.729 · Cited by 806 · see citing works
Lewis, P. N., Momany, F. A., & Scheraga, H. A. (1973) · Biochimica et Biophysica Acta (BBA) - Protein Structure · doi:10.1016/0005-2795(73)90350-4 · Cited by 665 · see citing works
Information content in the circular dichroism of proteins
Hennessey, J. P., & Johnson, W. C. (1981) · Biochemistry · doi:10.1021/bi00508a007 · Cited by 594 · see citing works
Deisenhofer, J., & Steigemann, W. (1975) · Acta Crystallographica Section B · doi:10.1107/s0567740875002415 · Cited by 550 · see citing works
Lifson, S., Hagler, A. T., & Dauber, P. (1979) · Journal of the American Chemical Society · doi:10.1021/ja00512a001 · Cited by 509 · see citing works
Automatic identification of secondary structure in globular proteins
Levitt, M., & Greer, J. (1977) · Journal of Molecular Biology · doi:10.1016/0022-2836(77)90207-8 · Cited by 508 · see citing works
Reverse Turns in Peptides and Protein
Smith, J. A., Pease, L. G., & Kopple, K. D. (1980) · Critical Reviews in Biochemistry and Molecular Biology · doi:10.3109/10409238009105470 · Cited by 502 · see citing works
Refinement of protein conformations using a macromolecular energy minimization procedure
Levitt, M., & Lifson, S. (1969) · Journal of Molecular Biology · doi:10.1016/0022-2836(69)90421-5 · Cited by 466 · see citing works
C.J.G. (1980) · Journal of Molecular Structure · doi:10.1016/0022-2860(80)85326-9 · Cited by 418 · see citing works
Refinement of large structures by simultaneous minimization of energy and R factor
Jack, A., & Levitt, M. (1978) · Acta Crystallographica Section A · doi:10.1107/s0567739478001904 · Cited by 357 · see citing works
Conformational energy estimates for statistically coiling polypeptide chains
Brant, D. A., Miller, W. G., & Flory, P. J. (1967) · Journal of Molecular Biology · doi:10.1016/s0022-2836(67)80066-4 · Cited by 352 · see citing works
(1980) · Acta Crystallographica Section B · doi:10.1107/s0567740880010369 · Cited by 295 · see citing works
Three-dimensional structure of adenyl kinase
Schulz, G. E., Elzinga, M., Marx, F., & Schirmer, R. H. (1974) · Nature · doi:10.1038/250120a0 · Cited by 256 · see citing works
Sussman, J. L., Holbrook, S. R., Church, G. M., et al. (1977) · Acta Crystallographica Section A · doi:10.1107/s0567739477001958 · Cited by 246 · see citing works
A real-space refinement procedure for proteins
Diamond, R. (1971) · Acta Crystallographica Section A · doi:10.1107/s0567739471000986 · Cited by 236 · see citing works
Nuclear magnetic resonance of labile protons in the basic pancreatic trypsin inhibitor
Wüthrich, K., & Wagner, G. H. (1979) · Journal of Molecular Biology · doi:10.1016/0022-2836(79)90548-5 · Cited by 195 · see citing works
A new least-squares refinement technique based on the fast Fourier transform algorithm
Agarwal, R. C. (1978) · Acta Crystallographica Section A · doi:10.1107/s0567739478001618 · Cited by 195 · see citing works
Kuntz, I. D. (1972) · Journal of the American Chemical Society · doi:10.1021/ja00766a060 · Cited by 183 · see citing works
Williams, R. W., & Dunker, A. K. (1981) · Journal of Molecular Biology · doi:10.1016/0022-2836(81)90127-3 · Cited by 153 · see citing works
THE STRUCTURE OF PARACOCCUS DENITRIFICANS CYTOCHROME C550
Timkovich, R. (1976) · Worldwide Protein Data Bank · doi:10.2210/pdb155c/pdb · Cited by 121 · see citing works
Specific recognition in the tertiary structure of β-sheets of proteins
Lifson, S., & Sander, C. (1980) · Journal of Molecular Biology · doi:10.1016/0022-2836(80)90052-2 · Cited by 115 · see citing works
Self-citationThe structure of Paracoccus denitrificans cytochrome c550.
Timkovich, R., & Dickerson, R. E. (1976) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(17)33352-5 · Cited by 105 · see citing works
Abbreviations and Symbols for the Description of the Conformation of Polypeptide Chains
IUPAC-IUB Commission on Biochemical Nomenclature (1970) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(18)62561-x · Cited by 82 · see citing works
Difference Fourier refinement of the structure of DIP-trypsin at 1.5 Å with a minicomputer technique
Chambers, J. L., & Stroud, R. M. (1977) · Acta Crystallographica Section B · doi:10.1107/s0567740877007146 · Cited by 74 · see citing works
Dodson, E. J., Isaacs, N. W., & Rollett, J. S. (1976) · Acta Crystallographica Section A · doi:10.1107/s0567739476000685 · Cited by 67 · see citing works
Differential Geometry and Polymer Conformation. 1. Comparison of Protein Conformations1a,b
Rackovsky, S. R., & Scheraga, H. A. (1978) · Macromolecules · doi:10.1021/ma60066a020 · Cited by 61 · see citing works
A new algorithm for finding the peptide chain turns in a globular protein
Rose, G. D., & Seltzer, J. P. (1977) · Journal of Molecular Biology · doi:10.1016/0022-2836(77)90046-8 · Cited by 56 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
AQUA and PROCHECK-NMR: Programs for checking the quality of protein structures solved by NMR
Laskowski, R., Rullmann, J. A., MacArthur, M., Kaptein, R., & Thornton, J. (1996) · Journal of Biomolecular NMR · doi:10.1007/bf00228148 · Cited by 5,502 · see citing works
TM-align: a protein structure alignment algorithm based on the TM-score
Zhang, Y. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki524 · Cited by 3,774 · see citing works
Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2016239118 · Cited by 3,286 · see citing works
Improved protein structure prediction using potentials from deep learning
Senior, A. W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., Green, T., Qin, C., Žídek, A., Nelson, A. W. R., Bridgland, A., et al. (2020) · Nature · doi:10.1038/s41586-019-1923-7 · Cited by 3,378 · see citing works
Crystal Structure of a p53 Tumor Suppressor-DNA Complex: Understanding Tumorigenic Mutations
Cho, Y., Gorina, S., Jeffrey, P. D., & Pavletich, N. P. (1994) · Science · doi:10.1126/science.8023157 · Cited by 2,559 · see citing works
CASTp 3.0: computed atlas of surface topography of proteins
Tian, W., Chen, C., Lei, X., Zhao, J., & Liang, J. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky473 · Cited by 2,389 · see citing works
Starr, T. N., Greaney, A. J., Hilton, S. K., Ellis, D., Crawford, K. H. D., Dingens, A. S., Navarro, M. J., Bowen, J. E., Tortorici, M. A., Walls, A. C., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.012 · Cited by 1,956 · see citing works
Assessing the accuracy of prediction algorithms for classification: an overview
Baldi, P., Brunak, S., Chauvin, Y., Andersen, C. A. F., & Nielsen, H. (2000) · Bioinformatics · doi:10.1093/bioinformatics/16.5.412 · Cited by 2,111 · see citing works
The Ras-RasGAP Complex: Structural Basis for GTPase Activation and Its Loss in Oncogenic Ras Mutants
Scheffzek, K., Ahmadian, M. R., Kabsch, W., Wiesmüller, L., Lautwein, A., Schmitz, F., & Wittinghofer, A. (1997) · Science · doi:10.1126/science.277.5324.333 · Cited by 1,543 · see citing works
Self-citation‘Improved parameters for the Martini coarse-grained protein force field’
de Jong, D. H., Singh, G., Bennett, W. F. D., Arnarez, C., Wassenaar, T. A., Schäfer, L. V., Periole, X., Tieleman, D. P., & Marrink, S. J. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct300646g · Cited by 1,486 · see citing works
HH-suite3 for fast remote homology detection and deep protein annotation
Steinegger, M., Meier, M., Mirdita, M., Vöhringer, H., Haunsberger, S. J., & Söding, J. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3019-7 · Cited by 1,145 · see citing works
A new approach to protein fold recognition
Jones, D. T., Taylort, W. R., & Thornton, J. M. (1992) · Nature · doi:10.1038/358086a0 · Cited by 1,221 · see citing works
Influence of proline residues on protein conformation
MacArthur, M. W., & Thornton, J. M. (1991) · Journal of Molecular Biology · doi:10.1016/0022-2836(91)90721-h · Cited by 1,189 · see citing works
Unified rational protein engineering with sequence-based deep representation learning
Alley, E. C., Khimulya, G., Biswas, S., AlQuraishi, M., & Church, G. M. (2019) · Nature Methods · doi:10.1038/s41592-019-0598-1 · Cited by 1,131 · see citing works
Improved prediction of protein-protein interactions using AlphaFold2
Bryant, P., Pozzati, G., & Elofsson, A. (2021) · doi:10.1101/2021.09.15.460468 · Cited by 1,025 · see citing works
Subtilases: the superfamily of subtilisin-like serine proteases.
Siezen, R. J., & Leunissen, J. A. M. (1997) · Protein Science · doi:10.1002/pro.5560060301 · Cited by 896 · see citing works
Correlated mutations and residue contacts in proteins
Göbel, U., Sander, C., Schneider, R., & Valencia, A. (1994) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.340180402 · Cited by 863 · see citing works
Self-citationConsistent blind protein structure generation from NMR chemical shift data
Shen, Y., Lange, O., Delaglio, F., Rossi, P., Aramini, J. M., Liu, G., Eletsky, A., Wu, Y., Singarapu, K. K., Lemak, A., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800256105 · Cited by 855 · see citing works
Protein Sequence Analysis Using the MPI Bioinformatics Toolkit
Gabler, F., Nam, S., Till, S., Mirdita, M., Steinegger, M., Söding, J., Lupas, A. N., & Alva, V. (2020) · Current Protocols in Bioinformatics · doi:10.1002/cpbi.108 · Cited by 831 · see citing works
Structural Snapshots of Human HDAC8 Provide Insights into the Class I Histone Deacetylases
Somoza, J. R., Skene, R. J., Katz, B. A., Mol, C., Ho, J. D., Jennings, A. J., Luong, C., Arvai, A., Buggy, J. J., Chi, E., et al. (2004) · Structure · doi:10.1016/j.str.2004.04.012 · Cited by 710 · see citing works
Reliable B cell epitope predictions: impacts of method development and improved benchmarking
Kringelum, J. V., Lundegaard, C., Lund, O., & Nielsen, M. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002829 · Cited by 697 · see citing works
Structural Evidence for Ligand Specificity in the Binding Domain of the Human Androgen Receptor
Matias, P. M., Donner, P., Coelho, R., Thomaz, M., Peixoto, C., Macedo, S., Otto, N., Joschko, S., Scholz, P., Wegg, A., et al. (2000) · Journal of Biological Chemistry · doi:10.1074/jbc.m004571200 · Cited by 608 · see citing works
Modeling the language of life – Deep Learning Protein Sequences
Heinzinger, M., Elnaggar, A., Wang, Y., Dallago, C., Nechaev, D., Matthes, F., & Rost, B. (2019) · doi:10.1101/614313 · Cited by 606 · see citing works
Global analysis of protein folding using massively parallel design, synthesis, and testing
Rocklin, G. J., Chidyausiku, T. M., Goreshnik, I., Ford, A., Houliston, S., Lemak, A., Carter, L., Ravichandran, R., Mulligan, V. K., Chevalier, A., et al. (2017) · Science · doi:10.1126/science.aan0693 · Cited by 501 · see citing works
Comparing two K-category assignments by a K-category correlation coefficient
Gorodkin, J. (2004) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2004.09.006 · Cited by 545 · see citing works
Karplus, P. A., Daniels, M. J., & Herriott, J. R. (1991) · Science · doi:10.1126/science.1986412 · Cited by 536 · see citing works
Preformed structural elements feature in partner recognition by intrinsically unstructured proteins
Fuxreiter, M., Simon, I., Friedrich, P., & Tompa, P. (2004) · Journal of Molecular Biology · doi:10.1016/j.jmb.2004.03.017 · Cited by 518 · see citing works
Structure of ribonuclease H phased at 2 a resolution by MAD analysis of the selenomethionyl protein
Yang, W., Hendrickson, W. A., Crouch, R. J., & Satow, Y. (1990) · Science · doi:10.1126/science.2169648 · Cited by 473 · see citing works
Low-N protein engineering with data-efficient deep learning
Biswas, S., Khimulya, G., Alley, E. C., Esvelt, K. M., & Church, G. M. (2021) · Nature Methods · doi:10.1038/s41592-021-01100-y · Cited by 422 · 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 · see citing works
“Regions corresponding to the beta sheets of Lsi1 are predicted by the mainly alpha model with approximately the right shape, except that their atomic coordinates are not sufficiently precise to enable DSSP to classify them as beta sheets.”
MethodInfluentialRives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2019) · doi:10.1101/622803 · Cited by 3,280 · see citing works
Structural basis for high-affinity peptide inhibition of p53 interactions with MDM2 and MDMX
Pazgier, M., Liu, M., Zou, G., Yuan, W., Li, C., Li, C., Li, J., Monbo, J., Zella, D., Tarasov, S. G., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0900947106 · Cited by 391 · see citing works
Crystal Structure of the CSL-Notch-Mastermind Ternary Complex Bound to DNA
Wilson, J. J., & Kovall, R. A. (2006) · Cell · doi:10.1016/j.cell.2006.01.035 · Cited by 371 · see citing works
Catalytic mechanisms and specificities of glutathione peroxidases: variations of a basic scheme
Toppo, S., Flohé, L., Ursini, F., Vanin, S., & Maiorino, M. (2009) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2009.04.007 · Cited by 368 · see citing works
Santiago, J., Henzler, C., & Hothorn, M. (2013) · Science · doi:10.1126/science.1242468 · Cited by 357 · see citing works
Walshaw, J., & Woolfson, D. N. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2001.4545 · Cited by 357 · 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
Three-dimensional structure of ribonuclease H from E. coli
Katayanagi, K., Miyagawa, M., Matsushima, M., Ishikawa, M., Kanaya, S., Ikehara, M., Matsuzaki, T., & Morikawa, K. (1990) · Nature · doi:10.1038/347306a0 · Cited by 349 · see citing works
BeAtMuSiC: prediction of changes in protein–protein binding affinity on mutations
Dehouck, Y., Kwasigroch, J. M., Rooman, M., & Gilis, D. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt450 · Cited by 338 · see citing works
Structural analysis of B-cell epitopes in antibody: protein complexes
Kringelum, J. V., Nielsen, M., Padkjær, S. B., & Lund, O. (2013) · Molecular Immunology · doi:10.1016/j.molimm.2012.06.001 · Cited by 305 · see citing works
Chi, Z., Chen, X. G., Holtz, J. S. W., & Asher, S. A. (1998) · Biochemistry · doi:10.1021/bi971160z · Cited by 301 · see citing works
Structure of the Decorated Ciliary Doublet Microtubule
Ma, M., Stoyanova, M., Rademacher, G., Dutcher, S. K., Brown, A., & Zhang, R. (2019) · Cell · doi:10.1016/j.cell.2019.09.030 · Cited by 290 · see citing works
Unique amino acid composition of proteins in halophilic bacteria
Fukuchi, S., Yoshimune, K., Wakayama, M., Moriguchi, M., & Nishikawa, K. (2003) · Journal of Molecular Biology · doi:10.1016/s0022-2836(03)00150-5 · Cited by 277 · see citing works
Assessing the Impact of Secondary Structure and Solvent Accessibility on Protein Evolution
Goldman, N., Thorne, J. L., & Jones, D. T. (1998) · Genetics · doi:10.1093/genetics/149.1.445 · Cited by 281 · see citing works
Tubiana, J., Schneidman-Duhovny, D., & Wolfson, H. J. (2022) · Nature Methods · doi:10.1038/s41592-022-01490-7 · Cited by 274 · see citing works
Hallucinating symmetric protein assemblies
Wicky, B. I. M., Milles, L. F., Courbet, A., Ragotte, R. J., Dauparas, J., Kinfu, E., Tipps, S., Kibler, R. D., Baek, M., DiMaio, F., et al. (2022) · Science · doi:10.1126/science.add1964 · Cited by 240 · see citing works
Recombining the structures of HIV integrase, RuvC and RNase H
Yang, W., & Steitz, T. A. (1995) · Structure · doi:10.1016/s0969-2126(01)00142-3 · Cited by 246 · see citing works
Improved protein structure refinement guided by deep learning based accuracy estimation
Hiranuma, N., Park, H., Baek, M., Anishchenko, I., Dauparas, J., & Baker, D. (2021) · Nature Communications · doi:10.1038/s41467-021-21511-x · Cited by 243 · see citing works
ABodyBuilder: automated antibody structure prediction with data-driven accuracy estimation
Leem, J., Dunbar, J., Georges, G., Shi, J., & Deane, C. M. (2016) · mAbs · doi:10.1080/19420862.2016.1205773 · Cited by 238 · see citing works
Discovering highly potent antimicrobial peptides with deep generative model HydrAMP
Szymczak, P., Możejko, M., Grzegorzek, T., Jurczak, R., Bauer, M., Neubauer, D., Sikora, K., Michalski, M., Sroka, J., Setny, P., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-36994-z · Cited by 231 · see citing works
Structurally mapping the diverse phenotype of adeno-associated virus serotype 4
Govindasamy, L., Padron, E., McKenna, R., Muzyczka, N., Kaludov, N., Chiorini, J. A., & Agbandje-McKenna, M. (2006) · Journal of Virology · doi:10.1128/jvi.01536-06 · Cited by 205 · see citing works
The Yeast Ski Complex: Crystal Structure and RNA Channeling to the Exosome Complex
Halbach, F., Reichelt, P., Rode, M., & Conti, E. (2013) · Cell · doi:10.1016/j.cell.2013.07.017 · Cited by 210 · see citing works
Transfer learning to leverage larger datasets for improved prediction of protein stability changes
Dieckhaus, H., Brocidiacono, M., Randolph, N. Z., & Kuhlman, B. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2314853121 · Cited by 205 · 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
Crystal structure of SIV matrix antigen and implications for virus assembly
Rao, Z., Belyaev, A. S., Fry, E., Roy, P., Jones, I. M., & Stuart, D. I. (1995) · Nature · doi:10.1038/378743a0 · Cited by 183 · see citing works
Protein sequence design with a learned potential
Anand, N., Eguchi, R., Mathews, I. I., Perez, C. P., Derry, A., Altman, R. B., & Huang, P.-S. (2022) · Nature Communications · doi:10.1038/s41467-022-28313-9 · Cited by 171 · see citing works
Greener, J. G., Kandathil, S. M., & Jones, D. T. (2019) · Nature Communications · doi:10.1038/s41467-019-11994-0 · Cited by 178 · see citing works
NetCGlyc 1.0: Prediction of mammalian C-mannosylation sites
Julenius, K. (2007) · Glycobiology · doi:10.1093/glycob/cwm050 · Cited by 174 · see citing works
Structural basis of epitope recognition by heavy-chain camelid antibodies
Zavrtanik, U., Lukan, J., Loris, R., Lah, J., & Hadži, S. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.09.002 · Cited by 169 · see citing works
Pandini, A., Denison, M. S., Song, Y., Soshilov, A. A., & Bonati, L. (2007) · Biochemistry · doi:10.1021/bi061460t · Cited by 160 · see citing works
The Hydrophobic Temperature Dependence of Amino Acids Directly Calculated from Protein Structures
van Dijk, E., Hoogeveen, A., & Abeln, S. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004277 · Cited by 162 · see citing works
Predicting functional effects of missense variants in voltage-gated sodium and calcium channels
Heyne, H. O., Baez-Nieto, D., Iqbal, S., Palmer, D. S., Brunklaus, A., May, P., Collaborative, E., Johannesen, K. M., Lauxmann, S., Lemke, J. R., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aay6848 · Cited by 140 · see citing works
Soares, C. M., Teixeira, V. H., & Baptista, A. M. (2003) · Biophysical Journal · doi:10.1016/s0006-3495(03)74972-8 · Cited by 149 · see citing works
Structure–Function Insights into Direct Lipid Transfer between Membranes by Mmm1–Mdm12 of ERMES
Kawano, S., Tamura, Y., Kojima, R., Bala, S., Asai, E., Michel, A. H., Kornmann, B., Riezman, I., Riezman, H., Sakae, Y., et al. (2018) · Journal of Cell Biology · doi:10.1083/jcb.201704119 · Cited by 148 · see citing works
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
Müller, A., Müller, J. J., Muller, Y. A., Uhlmann, H., Bernhardt, R., & Heinemann, U. (1998) · Structure · doi:10.1016/s0969-2126(98)00031-8 · Cited by 142 · see citing works
Crystal Structure and Activity of Human p23, a Heat Shock Protein 90 Co-chaperone
Weaver, A. J., Sullivan, W. P., Felts, S. J., Owen, B. A. L., & Toft, D. O. (2000) · Journal of Biological Chemistry · doi:10.1074/jbc.m003410200 · Cited by 136 · see citing works
PED in 2021: a major update of the protein ensemble database for intrinsically disordered proteins
Lazar, T., Martínez-Pérez, E., Quaglia, F., Hatos, A., Chemes, L. B., Iserte, J. A., Méndez, N. A., Garrone, N. A., Saldaño, T. E., Marchetti, J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1021 · Cited by 142 · see citing works
AlphaFold2-aware protein–DNA binding site prediction using graph transformer
Yuan, Q., Chen, S., Rao, J., Zheng, S., Zhao, H., & Yang, Y. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbab564 · Cited by 137 · see citing works
Ramı́rez-Alvarado, M., Blanco, F. J., Niemann, H., & Serrano, L. (1997) · Journal of Molecular Biology · doi:10.1006/jmbi.1997.1347 · Cited by 136 · see citing works
Structural basis for the reversible activation of a Rho protein by the bacterial toxin SopE
Buchwald, G., Friebel, A., Galán, J. E., Hardt, W., Wittinghofer, A., & Scheffzek, K. (2002) · The EMBO Journal · doi:10.1093/emboj/cdf329 · Cited by 135 · see citing works
Finding Our Way in the Dark Proteome
Bhowmick, A., Brookes, D. H., Yost, S. R., Dyson, H. J., Forman-Kay, J. D., Gunter, D., Head-Gordon, M., Hura, G. L., Pande, V. S., Wemmer, D. E., et al. (2016) · Journal of the American Chemical Society · doi:10.1021/jacs.6b06543 · Cited by 128 · see citing works
Protein language models learn evolutionary statistics of interacting sequence motifs
Zhang, Z., Wayment-Steele, H. K., Brixi, G., Wang, H., Kern, D., & Ovchinnikov, S. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2406285121 · Cited by 140 · see citing works
Pandini, A., Soshilov, A. A., Song, Y., Zhao, J., Bonati, L., & Denison, M. S. (2009) · Biochemistry · doi:10.1021/bi900259z · Cited by 124 · see citing works
Martinize2 and Vermouth provide a unified framework for molecular topology generation
Kroon, P. C., Grünewald, F., Barnoud, J., van Tilburg, M., Brasnett, C., Souza, P. C., Wassenaar, T. A., & Marrink, S. J. (2025) · eLife · doi:10.7554/elife.90627 · Cited by 124 · see citing works
The crystal structure of the monomeric reverse transcriptase from Moloney murine leukemia virus
Das, D., & Georgiadis, M. M. (2004) · Structure · doi:10.1016/j.str.2004.02.032 · Cited by 117 · see citing works
Ceccarelli, C., Grodsky, N. B., Ariyaratne, N., Colman, R. F., & Bahnson, B. J. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m207306200 · Cited by 116 · see citing works
Green, A. G., Elhabashy, H., Brock, K. P., Maddamsetti, R., Kohlbacher, O., & Marks, D. S. (2021) · Nature Communications · doi:10.1038/s41467-021-21636-z · Cited by 114 · see citing works
Insights into disease-associated mutations in the human proteome through protein structural analysis
Gao, M., Zhou, H., & Skolnick, J. (2015) · Structure · doi:10.1016/j.str.2015.03.028 · Cited by 113 · see citing works
Lin, Y.-S., Bowman, G. R., Beauchamp, K. A., & Pande, V. S. (2012) · Biophysical Journal · doi:10.1016/j.bpj.2011.12.002 · Cited by 111 · see citing works
Sahakitrungruang, T., Tee, M. K., Blackett, P. R., & Miller, W. L. (2011) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2010-1828 · Cited by 111 · see citing works
AlphaFold2 reveals commonalities and novelties in protein structure space for 21 model organisms
Bordin, N., Sillitoe, I., Nallapareddy, V., Rauer, C., Lam, S. D., Waman, V. P., Sen, N., Heinzinger, M., Littmann, M., Kim, S., et al. (2023) · Communications Biology · doi:10.1038/s42003-023-04488-9 · Cited by 103 · see citing works
De novo protein design by inversion of the <scp>AlphaFold</scp> structure prediction network
Goverde, C. A., Wolf, B., Khakzad, H., Rosset, S., & Correia, B. E. (2023) · Protein Science · doi:10.1002/pro.4653 · Cited by 103 · see citing works
The H3 loop of antibodies shows unique structural characteristics
Regep, C., Georges, G., Shi, J., Popovic, B., & Deane, C. M. (2017) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25291 · Cited by 99 · see citing works
Amino acid encoding methods for protein sequences: a comprehensive review and assessment
Jing, X., Dong, Q., Hong, D., & Lu, R. (2020) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2019.2911677 · Cited by 97 · see citing works
Mining the CRBN target space redefines rules for molecular glue-induced neosubstrate recognition
Petzold, G., Gainza, P., Annunziato, S., Lamberto, I., Trenh, P., McAllister, L. A., DeMarco, B., Schwander, L., Bunker, R. D., Zlotosch, M., et al. (2025) · Science · doi:10.1126/science.adt6736 · Cited by 117 · see citing works
ProteinSGM: Score-based generative modeling for <i>de novo</i> protein design
Lee, J. S., Kim, J., & Kim, P. M. (2022) · doi:10.1101/2022.07.13.499967 · Cited by 94 · see citing works
An overview of the prediction of protein DNA-binding sites
Si, J., Zhao, R., & Wu, R. (2015) · International Journal of Molecular Sciences · doi:10.3390/ijms16035194 · Cited by 91 · see citing works
Crystal structure of isopentenyl diphosphate:dimethylallyl diphosphate isomerase
Durbecq, V., Sainz, G., Oudjama, Y., Clantin, B., Bompard‐Gilles, C., Tricot, C., Caillet, J., Stalon, V., Droogmans, L., & Villeret, V. (2001) · The EMBO Journal · doi:10.1093/emboj/20.7.1530 · Cited by 90 · see citing works
De novo and inverse folding predictions of protein structure and dynamics
Godzik, A., Kolinski, A., & Skolnick, J. (1993) · Journal of Computer-Aided Molecular Design · doi:10.1007/bf02337559 · Cited by 91 · see citing works
Conte, A. D., Mehdiabadi, M., Bouhraoua, A., Miguel Monzon, A., Tosatto, S. C. E., & Piovesan, D. (2023) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26582 · Cited by 86 · see citing works
A quantitative measure for protein conformational heterogeneity
Lyle, N., Das, R. K., & Pappu, R. V. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4812791 · Cited by 85 · see citing works
Geng, C., Vangone, A., Folkers, G. E., Xue, L. C., & Bonvin, A. M. J. J. (2019) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.25630 · Cited by 82 · see citing works
Context-Based Identification of Protein-Protein Interfaces and “Hot-Spot” Residues
Geppert, T., Hoy, B., Wessler, S., & Schneider, G. (2011) · Chemistry & Biology · doi:10.1016/j.chembiol.2011.01.005 · Cited by 80 · see citing works
Predicting the pathogenicity of missense variants using features derived from AlphaFold2
Schmidt, A., Röner, S., Mai, K., Klinkhammer, H., Kircher, M., & Ludwig, K. U. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad280 · Cited by 79 · see citing works
Computational design of epitope-specific functional antibodies
Nimrod, G., Fischman, S., Austin, M., Herman, A., Keyes, F., Leiderman, O., Hargreaves, D., Strajbl, M., Breed, J., Klompus, S., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.10.081 · Cited by 77 · see citing works
Structure and reactivity of LpxD, the <i>N</i> -acyltransferase of lipid A biosynthesis
Buetow, L., Smith, T. K., Dawson, A., Fyffe, S., & Hunter, W. N. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0606356104 · Cited by 78 · see citing works
Using a combined computational-experimental approach to predict antibody-specific B cell epitopes
Sela-Culang, I., Benhnia, M. R.-E.-I., Matho, M. H., Kaever, T., Maybeno, M., Schlossman, A., Nimrod, G., Li, S., Xiang, Y., Zajonc, D., et al. (2014) · Structure · doi:10.1016/j.str.2014.02.003 · Cited by 69 · see citing works
Towards simple kinetic models of functional dynamics for a kinase subfamily
Sultan, M. M., Kiss, G., & Pande, V. S. (2018) · Nature Chemistry · doi:10.1038/s41557-018-0077-9 · Cited by 68 · see citing works
Finelli, M. J., Aprile, D., Castroflorio, E., Jeans, A., Moschetta, M., Chessum, L., Degiacomi, M. T., Grasegger, J., Lupien-Meilleur, A., Bassett, A., et al. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddy370 · Cited by 62 · see citing works
- Authors
- Kabsch, W., & Sander, C.
- Affiliations
- Max Planck Society (DE)
- Max Planck Institute for Medical Research (DE)
- Venue
- Biopolymers
- Publisher
- Wiley
- Published
- 1983-12
- Volume
- 22
- Issue
- 12
- Pages
- 2577-2637
- ISSN
- 0006-3525 (ISSN-L)
- 1097-0282
- OpenAlex
- W2008708467
- Cited by
- 15,320
- References
- 36
- Citations by year
- 2026: 445 · 2025: 615 · 2024: 617 · 2023: 614 · 2022: 625 · 2021: 599 · 2020: 583 · 2019: 571 · 2018: 512 · 2017: 474 · 2016: 511 · 2015: 479 · 2014: 548 · 2013: 595 · 2012: 558
- FWCI
- 6.84
- Type
- journal article
- Language
- en
- Open access
- green
- edoc.mpg.de
- Locations
- Biopolymers (publishedVersion)
- PubMed (publishedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion, cc-by)
- Max Planck Digital Library (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Keywords
- protein secondary structure, hydrogen bonding patterns, helix, beta-sheet, turns, bridges, torsion, curvature, solvent exposure, pattern recognition, globular proteins, sequence-structure relationship, protein structure prediction
- MeSH terms
- Amino Acid Sequence, Hydrogen Bonding, Protein Conformation, 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.
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