ECOD: an evolutionary classification of protein domains
Open accessAbstract
Understanding the evolution of a protein, including both close and distant relationships, often reveals insight into its structure and function. Fast and easy access to such up-to-date information facilitates research. We have developed a hierarchical evolutionary classification of all proteins with experimentally determined spatial structures, and presented it as an interactive and updatable online database. ECOD (Evolutionary Classification of protein Domains) is distinct from other structural classifications in that it groups domains primarily by evolutionary relationships (homology), rather than topology (or "fold"). This distinction highlights cases of homology between domains of differing topology to aid in understanding of protein structure evolution. ECOD uniquely emphasizes distantly related homologs that are difficult to detect, and thus catalogs the largest number of evolutionary links among structural domain classifications. Placing distant homologs together underscores the ancestral similarities of these proteins and draws attention to the most important regions of sequence and structure, as well as conserved functional sites. ECOD also recognizes closer sequence-based relationships between protein domains. Currently, approximately 100,000 protein structures are classified in ECOD into 9,000 sequence families clustered into close to 2,000 evolutionary groups. The classification is assisted by an automated pipeline that quickly and consistently classifies weekly releases of PDB structures and allows for continual updates. This synchronization with PDB uniquely distinguishes ECOD among all protein classifications. Finally, we present several case studies of homologous proteins not recorded in other classifications, illustrating the potential of how ECOD can be used to further biological and evolutionary studies.
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The ECOD homology level is a strict similarity criterion because it clusters domains even if they only have distant relationships.
“The ECOD homology level (“H level”) is a strict similarity criterion since it clusters domains even if they only have distant relationships.”
From Deep geometric representations for modeling effects of mutations on protein-protein binding affinity (2021) · cites this paper as [37]
The training structures of the geometric encoder share no ECOD homology domain with the benchmark datasets.
“we used the ECOD classifier [37] (file: “ecod.develop277.domains.txt”, version: “develop277”) to remove the similar complexes and ensure the training complexes share no ECOD homology domain with the benchmark datasets.”
From Deep geometric representations for modeling effects of mutations on protein-protein binding affinity (2021) · cites this paper as [37]
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InfluentialClustering predicted structures at the scale of the known protein universe
Barrio-Hernandez, I., Yeo, J., Jänes, J., Mirdita, M., Gilchrist, C. L. M., Wein, T., Varadi, M., Velankar, S., Beltrao, P., & Steinegger, M. (2023) · Nature · doi:10.1038/s41586-023-06510-w · Cited by 362 · see citing works
“We therefore investigated the evolutionary relationships within clusters produced by our method using the Evolutionary Classification of Protein Domains (ECOD) database 24 .”
MethodThe SUPERFAMILY 2.0 database: a significant proteome update and a new webserver
Pandurangan, A. P., Stahlhacke, J., Oates, M. E., Smithers, B., & Gough, J. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1130 · Cited by 224 · see citing works
“SUPERFAMILY 2.0 profile HMM model library In this update, we have created a new profile HMM library using sequences taken from the structural domain database SCOPe (13), CATH (14), ECOD (15) and PDB (16).”
MethodInfluentialUpadhyay, A. A., Fleetwood, A. D., Adebalı, O., Finn, R. D., & Zhulin, I. B. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004862 · Cited by 193 · see citing works
“Satisfactorily, homologous relationships between Cache, PAS, and GAF were also captured in a new database ECOD (Evolutionary Classification of Protein Domains) [37], which also included most of the related “orphan” families described above into the same superfamily. doi:10.1371/journal.pcbi.1004862.g003 PLOS Computati…”
BackgroundMethodInfluentialJones, D. T., & Kandathil, S. M. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty341 · Cited by 184 · see citing works
Chandonia, J., Guan, L., Lin, S., Yu, C., Fox, N. K., & Brenner, S. E. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab1054 · Cited by 173 · see citing works
“Comparisons of SCOPe to other structural classifications of proteins including SCOP2 (10), CATH (11) and ECOD (12), as well as to the sequence-based Pfam classification (13) are provided elsewhere (6,7,14).”
DeepSF: deep convolutional neural network for mapping protein sequences to folds
Hou, J., Adhikari, B., & Cheng, J. J. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx780 · Cited by 179 · see citing works
A Structurally-Validated Multiple Sequence Alignment of 497 Human Protein Kinase Domains
Modi, V., & Dunbrack, R. L. (2019) · Scientific Reports · doi:10.1038/s41598-019-56499-4 · Cited by 171 · see citing works
Haas, J., Barbato, A., Behringer, D., Studer, G., Roth, S., Bertoni, M., Mostaguir, K., Gumienny, R., & Schwede, T. (2018) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.25431 · Cited by 168 · see citing works
“In CASP this problem is addressed by splitting the target structures into actual assessment units (AUs) [21] by human intervention with the support of computational approaches[22, 23].”
BackgroundChandonia, J., Fox, N. K., & Brenner, S. E. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1134 · Cited by 167 · see citing works
“The relationship of SCOPe to other structural classifications including SCOP2 (10), CATH (11), and ECOD (12) is discussed in detail elsewhere (7,13).”
BackgroundThe impact of AlphaFold2 one year on
Jones, D. T., & Thornton, J. M. (2022) · Nature Methods · doi:10.1038/s41592-021-01365-3 · Cited by 152 · see citing works
“One other interesting application of AlphaFold2 has been inverse protein folding, or protein design 16,17 .”
Accurate prediction of protein structures and interactions using a three-track neural network
Baek, M., DiMaio, F., Anishchenko, I. V., Dauparas, J., Ovchinnikov, S., Lee, G. R., Wang, J., Cong, Q., Kinch, L. N., Schaeffer, R. D., et al. (2022) · Yearbook of pediatric endocrinology · doi:10.1530/ey.19.15.15 · Cited by 199 · see citing works
Design of metalloproteins and novel protein folds using variational autoencoders
Greener, J. G., Moffat, L., & Jones, D. T. (2018) · Scientific Reports · doi:10.1038/s41598-018-34533-1 · Cited by 135 · see citing works
Deep geometric representations for modeling effects of mutations on protein-protein binding affinity
Liu, X., Luo, Y., Li, P., Song, S., & Peng, J. (2021) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1009284 · Cited by 140 · see citing works
“[36], we used the ECOD (Evolutionary Classification of Domains) homology level [37] to divide the data points to make different folds share no protein domain.”
Exploring structural diversity across the protein universe with The Encyclopedia of Domains
Lau, A. M., Bordin, N., Kandathil, S. M., Sillitoe, I., Waman, V. P., Wells, J., Orengo, C. A., & Jones, D. T. (2024) · Science · doi:10.1126/science.adq4946 · Cited by 140 · see citing works
“Although early comparisons across domain databases showed agreement for fold level assignments (10, 18, 19), significant differences exist for the definition of a protein domain.”
Harnessing Conformational Plasticity to Generate Designer Enzymes
Crean, R., Gardner, J. M., & Kamerlin, S. C. L. (2020) · Journal of the American Chemical Society · doi:10.1021/jacs.0c04924 · Cited by 129 · see citing works
Extending the small-molecule similarity principle to all levels of biology with the Chemical Checker
Duran-Frigola, M., Pauls, E., Guitart-Pla, O., Bertoni, M., Alcalde, V., Amat, D., Juan-Blanco, T., & Aloy, P. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0502-7 · Cited by 126 · see citing works
Rational design of α-helical tandem repeat proteins with closed architectures
Doyle, L., Hallinan, J. P., Bolduc, J. M., Parmeggiani, F., Baker, D. A., Stoddard, B. L., & Bradley, P. H. (2015) · Nature · doi:10.1038/nature16191 · Cited by 126 · see citing works
Mosaic origin of the eukaryotic kinetochore
Tromer, E. C., van Hooff, J. J. E., Kops, G. J. P. L., & Snel, . (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1821945116 · Cited by 107 · see citing works
“edu/ ecod/) (74), RCSB Protein Data Bank (https://www.”
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
Predicting protein-protein interactions in the human proteome
Zhang, J., Humphreys, I. R., Pei, J., Kim, J., Choi, C., Yuan, R., Durham, J., Liu, S., Choi, H.-J., Baek, M., et al. (2025) · Science · doi:10.1126/science.adt1630 · Cited by 87 · see citing works
Laurino, P., Tóth-Petróczy, Á., Meana‐Pañeda, R., Lin, W., Truhlar, D. G., & Tawfik, D. S. (2016) · PLoS Biology · doi:10.1371/journal.pbio.1002396 · Cited by 110 · see citing works
“However, based amongst other considerations on the shared β2-Asp/Glu motif, other classifiers such as ECOD (Evolutionary Classification of Protein Domains) [30] or Interpro [47] classify all three classes (NAD(P), FAD, and SAM-dependent Rossmann enzymes) in the same homology group [31,32,35,38,39].”
BackgroundMethodResultInfluentialCroessmann, S., Formisano, L., Kinch, L. N., Ericsson, P. I. G., Sudhan, D. R., Nagy, R. J., Mathew, A., Bernicker, E., Cristofanilli, M., He, J., et al. (2018) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-18-1544 · Cited by 107 · see citing works
Wang, Y., Gallagher, L. A., Andrade, P. A., Liu, A., Humphreys, I. R., Turkarslan, S., Cutler, K. J., Arrieta-Ortiz, M. L., Li, Y., Radey, M. C., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.017 · Cited by 108 · see citing works
“Domain Parser for AF Models (DPAM) is a recently developed tool that parses structural domains from AF-modeled structures and integrates both structure and sequence searches to map protein domains to evolutionary classification of protein domains (ECOD).(48,49) Using DPAM, we detected homologous ECOD domains for 80% o…”
MethodA tissue injury sensing and repair pathway distinct from host pathogen defense
Liu, S., Hur, Y. H., Cai, X., Cong, Q., Yang, Y., Xu, C., Bilate, A. M., Gonzales, K. A. U., Parigi, S. M., Cowley, C. J., et al. (2023) · Cell · doi:10.1016/j.cell.2023.03.031 · Cited by 108 · 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
Deep convolutional networks for quality assessment of protein folds
Derevyanko, G., Grudinin, S., Bengio, Y., & Lamoureux, G. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty494 · Cited by 101 · see citing works
“We have also compared the structures in the training and test sets using the ECOD database [30].”
ResultOn the emergence of P-Loop NTPase and Rossmann enzymes from a Beta-Alpha-Beta ancestral fragment
Longo, L. M., Jabłońska, J., Vyas, P., Kanade, M., Kolodny, R., Ben‐Tal, N., & Tawfik, D. S. (2020) · eLife · doi:10.7554/elife.64415 · Cited by 100 · see citing works
Sequence-structure-function relationships in the microbial protein universe
Leman, J. K., Szczerbiak, P., Renfrew, P. D., Gligorijević, V., Berenberg, D., Vatanen, T., Taylor, B. C., Chandler, C., Janssen, S., Pataki, A., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37896-w · Cited by 100 · see citing works
Chandonia, J., Fox, N. K., & Brenner, S. E. (2016) · Journal of Molecular Biology · doi:10.1016/j.jmb.2016.11.023 · Cited by 99 · see citing works
“06-stable), finding that 153,553 protein chains classified in both databases have consistent domain partitioning (which we define as the same number of domains, with no N- or C-terminal domain boundary changed by more than 10 residues), perhaps because early versions of ECOD were partially derived from SCOP [17].”
BackgroundMethodThe Origin and Evolution of Ribonucleotide Reduction
Lundin, D., Berggren, G., Logan, D. T., & Sjöberg, B. (2015) · Life · doi:10.3390/life5010604 · Cited by 100 · see citing works
“Besides several RNR structures in two families “Ribonuc_red_IgC” (class I and II) and “NRDD” (class III), the ECOD [84] “Ten stranded β/α barrel” superfamily (in ECOD termed X-level), contains structures from two non-RNR families: The “PflGly_m” and the “DUF711”.”
BackgroundECOD: new developments in the evolutionary classification of domains
Schaeffer, R. D., Liao, Y., Cheng, H., & Grishin, N. V. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1137 · Cited by 91 · see citing works
“We developed the Evolutionary Classification Of protein Domains (or ECOD) (7) as a hierarchal classification, which emphasizes distantly related homologs that are difficult to detect (H- and X-groups) and takes into account closer sequence-based relationships between protein domains that are placed in families.”
MethodSelf-citationAbriata, L. A., Tamò, G. E., Monastyrskyy, B., Kryshtafovych, A., & Peraro, M. D. (2017) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25423 · Cited by 90 · see citing works
Kaminski, K., Ludwiczak, J., Pawlicki, K., Alva, V., & Dunin-Horkawicz, S. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad579 · Cited by 84 · see citing works
“In benchmarks using domain pairs from the ECOD protein classification database (Cheng et al. 2014), pLM-BLAST demonstrated its suitability for fast pairwise comparisons and database searches to detect distant homology and produce highly precise alignments.”
MethodInfluentialA Fifth of the Protein World: Rossmann-like Proteins as an Evolutionarily Successful Structural unit
Medvedev, K. E., Kinch, L. N., Schaeffer, R. D., Pei, J., & Grishin, N. V. (2020) · Journal of Molecular Biology · doi:10.1016/j.jmb.2020.166788 · Cited by 81 · see citing works
“The mapping of RLM ECOD families to Pfam families was derived from ECOD database.(25,26) At the third step we use BLAST(119) on the remaining UniProt sequences in the human”
MethodEvaluation of free modeling targets in CASP11 and ROLL
Kinch, L. N., Li, W., Monastyrskyy, B., Kryshtafovych, A., & Grishin, N. V. (2015) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24973 · Cited by 80 · see citing works
“Each of these targets exemplified structures remotely related to their closest template fold in the evolutionary classification of protein domains (ECOD) database,24 retaining secondary structure elements that define the core fold common to all existing members of the ECOD homology groups.”
BackgroundNepomnyachiy, S., Ben‐Tal, N., & Kolodny, R. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1707642114 · Cited by 77 · see citing works
“, Class Architecture Topology Homology (CATH), Structural Classification of Proteins (SCOP), and Evolutionary Classification of Protein Domains (ECOD) (9, 35, 36)], and these were generally selected for inclusion based on reuse.”
PLINDER: The protein-ligand interactions dataset and evaluation resourcePreprint
Durairaj, J., Adeshina, Y. O., Cao, Z., Zhang, X., Oleinikovas, V., Duignan, T. J., McClure, Z. D., Robin, X., Studer, G., Kovtun, D., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.17.603955 · Cited by 82 · see citing works
“As shown in Table 2, the PLINDER -PL50 split exhibits the lowest leakage levels between training and test sets compared to PLINDER -TIME and PLINDER -ECOD.”
InfluentialKrishnan, S. M. (2018) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2018.02.008 · Cited by 74 · see citing works
Medvedev, K. E., Kinch, L. N., Schaeffer, R. D., & Grishin, N. V. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007569 · Cited by 73 · see citing works
“This level corresponds to CATH homologous superfamily level, which groups together somewhat distant domains, and SCOP superfamily level, which groups together more similar domains [15] (See S1 Table for comparison of RLM-containing domains classification in ECOD, SCOP and CATH).”
BackgroundMethodMEDUSA: Prediction of Protein Flexibility from Sequence
Meersche, Y. V., Cretin, G., de Brevern, A. G., Gelly, J., & Galochkina, T. V. (2021) · Journal of Molecular Biology · doi:10.1016/j.jmb.2021.166882 · Cited by 72 · see citing works
Novel machine learning approaches revolutionize protein knowledge
Bordin, N., Dallago, C., Heinzinger, M., Kim, S., Littmann, M., Rauer, C., Steinegger, M., Rost, B., & Orengo, C. (2023) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2022.11.001 · Cited by 72 · see citing works
“Various resources emerged to classify domain structures in evolutionary families and fold groups (e.g., SCOP ii [7], CATH iii [8], SCOPe iv [9], and ECOD v [10]), and these have saturated at about 5000 structural families and about 1300 folds over the past decade, despite structural genomics initiatives targeting prot…”
BackgroundManual classification strategies in the ECOD database
Cheng, H., Liao, Y., Schaeffer, R. D., & Grishin, N. V. (2015) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24818 · Cited by 71 · see citing works
“Manual curators then apply multiple considerations to identify homologs for a query structure: (1) the domain assignments attempted by the pipeline, as the pipeline can still suggest correct hits (that is, homologs) for part of the query (for example, one domain in a multi-domain protein); (2) scientific literature; (…”
BackgroundMethodSelf-citationStructural Patching Fosters Divergence of Mitochondrial Ribosomes
Petrov, A. S., Wood, E. C., Bernier, C. R., Norris, A., Brown, A., & Amunts, A. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy221 · Cited by 69 · see citing works
“To determine the possible origins of this subset of mitoribosomal proteins, we queried the sequence and structure of each member against the ECOD (Cheng et al. 2014) and NCBI’s nonredundant protein sequence (Benson et al. 2000) databases.”
MethodZhou, Y., Myung, Y., Rodrigues, C. H. M., & Ascher, D. B. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae412 · Cited by 65 · see citing works
“Additionally, the distinct interaction patterns observed in MDM2– p53, T55 and T56, which fall into specific ECOD H-level groups ( 35 , 45 , 46 ) (totalling 3751 groups across 206 556 PDB structures as of 28 November 2023), were not represented in the SKEMPI 2.0 training dataset.”
BackgroundInfluentialBridging Themes: Short Protein Segments Found in Different Architectures
Kolodny, R., Nepomnyachiy, S., Tawfik, D. S., & Ben‐Tal, N. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab017 · Cited by 63 · see citing works
“To detect these bridging themes, we search for sequence similarity in a (non redundant) set of domains that are classified as evolutionarily distinct (Cheng et al. 2014).”
BackgroundMethodReal time structural search of the Protein Data Bank
Guzenko, D., Burley, S. K., & Duarte, J. M. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007970 · Cited by 62 · see citing works
“Retrieval of similar structures was evaluated on a non-redundant subset of ECOD [5] and on a set of biological assemblies with distinct density shapes.”
BackgroundMethodRecent developments in deep learning applied to protein structure prediction
Kandathil, S. M., Greener, J. G., & Jones, D. T. (2019) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25824 · Cited by 59 · see citing works
“In fact, a convolutional network can be made even more robust by 81,82 and ECOD 83-85 can be used for this very purpose, as some studies have wisely done.”
BackgroundChSeq : A database of chameleon sequences
Li, W., Kinch, L. N., Karplus, P. A., & Grishin, N. V. (2015) · Protein Science · doi:10.1002/pro.2689 · Cited by 59 · see citing works
“59 As a cross-check of our homology assignments, we applied the ECOD classification to our BLAST-based ChSeq homologs.”
MethodKamiński, K., Ludwiczak, J., Jasiński, M., Bukala, A., Madaj, R., Szczepaniak, K., & Dunin-Horkawicz, S. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab371 · Cited by 60 · see citing works
“From 44 representative Rossmann structures selected based on the literature [4] and the ECOD [21] classification (Supplementary Table 1), we extracted C atoms corresponding to 3-2-1-4-5 -sheets and the -helix connecting 1 and 2 (Figure 1).”
BackgroundMethodThe Small β-Barrel Domain: A Survey-Based Structural Analysis
Youkharibache, P., Veretnik, S., Li, Q., Stanek, K. A., Mura, C., & Bourne, P. E. (2018) · Structure · doi:10.1016/j.str.2018.09.012 · Cited by 58 · see citing works
Evolution, folding, and design of TIM barrels and related proteins
Romero‐Romero, S., Kordes, S., Michel, F., & Höcker, B. (2021) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2020.12.007 · Cited by 57 · see citing works
DPAM : A domain parser for AlphaFold models
(2022) · doi:10.1002/pro.4548 · Cited by 49 · see citing works
Merizo: a rapid and accurate protein domain segmentation method using invariant point attention
Lau, A. M., Kandathil, S. M., & Jones, D. T. (2023) · Nature Communications · doi:10.1038/s41467-023-43934-4 · Cited by 48 · see citing works
Rossmann-Fold Methyltransferases: Taking a “β-Turn” around Their Cofactor, S -Adenosylmethionine
Chouhan, B. S., Maimaiti, S., Gade, M., & Laurino, P. (2018) · Biochemistry · doi:10.1021/acs.biochem.8b00994 · Cited by 54 · see citing works
Chainsaw: protein domain segmentation with fully convolutional neural networks
Wells, J., Hawkins-Hooker, A., Bordin, N., Sillitoe, I., Paige, B., & Orengo, C. (2023) · doi:10.1101/2023.07.19.549732 · Cited by 53 · see citing works
Mudgal, R., Sandhya, S., Chandra, N. R., & Srinivasan, N. (2015) · Biology Direct · doi:10.1186/s13062-015-0069-2 · Cited by 50 · see citing works
“Amongst the remaining 29 DUF families, where predictions belong to different SCOP folds, some included examples such as 6-bladed β -propeller, 7-bladed β -propeller and 8-bladed β -propeller which are believed to be evolutionarily related [55].”
BackgroundChainsaw: protein domain segmentation with fully convolutional neural networks
Wells, J., Hawkins-Hooker, A., Bordin, N., Sillitoe, I., Paige, B., & Orengo, C. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae296 · Cited by 53 · see citing works
“Structural protein domain databases such as CATH (Orengo et al. 1997), SCOP (Murzin et al. 1995), SCOPe (Chandonia et al. 2021), and ECOD (Cheng et al. 2014) are essential for advancing scientific understanding of the protein universe.”
MethodEnzyme function and evolution through the lens of bioinformatics
Ribeiro, A. J. M., Riziotis, I. G., Borkakoti, N., & Thornton, J. M. (2023) · Biochemical Journal · doi:10.1042/bcj20220405 · Cited by 50 · see citing works
Smug, B. J., Szczepaniak, K., Rocha, E. P. C., Dunin-Horkawicz, S., & Mostowy, R. J. (2023) · Nature Communications · doi:10.1038/s41467-023-43236-9 · Cited by 49 · see citing works
Zhao, K., Xia, Y., Zhang, F., Zhou, X., Li, S. Z., & Zhang, G. (2023) · Communications Biology · doi:10.1038/s42003-023-04605-8 · Cited by 46 · see citing works
An ambiguity principle for assigning protein structural domains
Postic, G., Ghouzam, Y., Chebrek, R., & Gelly, J. (2017) · Science Advances · doi:10.1126/sciadv.1600552 · Cited by 48 · see citing works
Singh, J., Litfin, T., Paliwal, K. K., Singh, J., Hanumanthappa, A. K., & Zhou, Y. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab316 · Cited by 47 · see citing works
Histones predate the split between bacteria and archaea
Alva, V., & Lupas, A. N. (2019) · Bioinformatics · doi:10.1093/bioinformatics/bty1000 · Cited by 43 · see citing works
Goldtzvik, Y., Sen, N., Lam, S. D., & Orengo, C. A. (2023) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2023.102640 · Cited by 48 · see citing works
Diversity in protein domain superfamilies
Das, S., Dawson, N. L., & Orengo, C. A. (2015) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2015.09.005 · Cited by 46 · see citing works
Cold seeps are potential hotspots of deep-sea nitrogen loss driven by microorganisms across 21 phyla
Jiang, Q., Cao, L., Han, Y., Li, S., Zhao, R., Zhang, X., Ruff, S. E., Zhao, Z., Peng, J., Liao, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56774-1 · Cited by 45 · see citing works
Longo, L. M., Petrović, D., Kamerlin, S. C. L., & Tawfik, D. S. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911742117 · Cited by 44 · see citing works
“Interacting residues were mapped to their corresponding evolutionary lineages (X-groups, F-groups) using the ECOD database (14) version develop255, accessed onDecember 8, 2019 (http://prodata.”
BackgroundMethodInfluentialKinch, L. N., Pei, J.-M., Kryshtafovych, A., Schaeffer, R. D., & Grishin, N. V. (2021) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26172 · Cited by 43 · see citing works
Protein function annotation using protein domain family resources
Das, S., & Orengo, C. A. (2015) · Methods · doi:10.1016/j.ymeth.2015.09.029 · Cited by 43 · see citing works
“They are known to switch their functions as a consequence of different cellular localisation, cell type, oligomeric state, or cellular concentration of molecules.”
A proteome-wide map of chaperone-assisted protein refolding in a cytosol-like milieu
To, P., Xia, Y., Lee, S. O., Devlin, T., Fleming, K. G., & Fried, S. D. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2210536119 · Cited by 42 · see citing works
“situations (but not always) correspond to deep evolutionary relationships (10).”
RUPEE: A fast and accurate purely geometric protein structure search
Ayoub, R., & Lee, Y. (2019) · PLoS ONE · doi:10.1371/journal.pone.0213712 · Cited by 39 · see citing works
“2 [3], ECOD develop210 [4], or among whole chains defined in the PDB.”
BackgroundFerruz, N., Lobos, F., Lemm, D., Toledo‐Patiño, S., Farías‐Rico, J. A., Schmidt, S., & Höcker, B. (2020) · Journal of Molecular Biology · doi:10.1016/j.jmb.2020.04.013 · Cited by 41 · see citing works
Fold Evolution before LUCA: Common Ancestry of SH3 Domains and OB Domains
Álvarez-Carreño, C., Penev, P. I., Petrov, A. S., & Williams, L. D. (2021) · Molecular Biology and Evolution · doi:10.1093/molbev/msab240 · Cited by 34 · see citing works
Skipper genome sheds light on unique phenotypic traits and phylogeny
Cong, Q., Borek, D., Otwinowski, Z., & Grishin, N. V. (2015) · BMC Genomics · doi:10.1186/s12864-015-1846-0 · Cited by 40 · see citing works
“This hypothesis is based on the following four facts: (1) Lac and most skippers in the Hesperiinae subfamily feed on the cellulose-rich grasses; (2) the Lac genome and other Lepidoptera genomes do not encode proteins that belong to the families of known cellulases; (3) endochitinases are homologs of cellulases and the…”
MethodDetecting similar binding pockets to enable systems polypharmacology
Duran‐Frigola, M., Siragusa, L., Ruppin, E., Barril, X., Cruciani, G., & Aloy, P. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005522 · Cited by 40 · see citing works
Deep Confident Steps to New Pockets: Strategies for Docking GeneralizationPreprint
Corso, G., Deng, A., Fry, B. N., Polizzi, N. F., Barzilay, R., & Jaakkola, T. (2024) · PubMed · doi:10.48550/arxiv.2402.18396 · Cited by 63 · see citing works
“To classify each domain, we used the ECOD [Cheng et al., 2014] To obtain a more sizable test set without retraining the models on a reduced set, we turn to the Binding MOAD dataset [Hu et al., 2005].”
MethodDecoding disease-causing mechanisms of missense mutations from supramolecular structures
Hijikata, A., Tsuji, T., Shionyu, M., & Shirai, T. (2017) · Scientific Reports · doi:10.1038/s41598-017-08902-1 · Cited by 39 · see citing works
Kinch, L. N., Schaeffer, D. R., Kryshtafovych, A., & Grishin, N. (2021) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.26202 · Cited by 38 · see citing works
Beaudoin, C. A., Jamasb, A. R., Alsulami, A. F., Copoiu, L., van Tonder, A. J., Hala, S. M., Bannerman, B. P., Thomas, S. E., Vedithi, S. C., Torres, P. H. M., et al. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.06.041 · Cited by 36 · see citing works
“RUPEE allows the specific comparison of a query protein to the CATH, SCOP, PDB, and ECOD databases (Andreeva et al., 2020; Burley et al., 2019; Cheng et al., 2014; Sillitoe et al., 2019).”
CASP13 target classification into tertiary structure prediction categories
Kinch, L. N., Kryshtafovych, A., Monastyrskyy, B., & Grishin, N. V. (2019) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25775 · Cited by 36 · see citing works
“Assignment of CASP13 EUs as distant homologs required expert curation 6,8 that considered sequence/structure scores, unusual structure features, or shared functional properties as evidence for homology.”
BackgroundA unified approach to protein domain parsing with inter-residue distance matrix
Zhu, K., Su, H. L., Peng, Z., & Yang, J. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad070 · Cited by 35 · see citing works
von Kügelgen, A., van Dorst, S., Yamashita, K., Sexton, D. L., Tocheva, E. I., Murshudov, G., Alva, V., & Bharat, T. A. M. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2215808120 · Cited by 35 · see citing works
“Despite this variability, all seven Ig-like domains of HPI are structurally similar and resemble the topology group (T-group) “immunoglobulin/ fibronectin type III/E set domains/PapD-like” in the Evolutionary Classification of Protein Domains (ECOD) database (28).”
BackgroundECOD: integrating classifications of protein domains from experimental and predicted structures
Schaeffer, R. D., Medvedev, K. E., Andreeva, A. E., Chuguransky, S., Pinto, B. L., Zhang, J., Cong, Q., Bateman, A. G., & Grishin, N. V. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1029 · Cited by 36 · see citing works
“These classifications have been divided into two categories: (i) those principally based on sequence such as Pfam ( 1 ), PAN-THER ( 2 ), SMART ( 3 ) and CDD ( 4 ) and (ii) those principally based on structure such as SCOP ( 5 ), CATH ( 6 ) and ECOD ( 7 ,8 ).”
Kinch, L. N., Li, W., Schaeffer, R. D., Dunbrack, R. L., Monastyrskyy, B., Kryshtafovych, A., & Grishin, N. V. (2016) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.24982 · Cited by 36 · see citing works
“from (1) domain swaps, where an exchange of secondary”
BackgroundMethodInfluentialDawson, N. L., Sillitoe, I., Lees, J. G., Lam, S. D., & Orengo, C. A. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-6783-4_4 · Cited by 36 · see citing works
Bradshaw, N., Levdikov, V. M., Zimanyi, C. M., Gaudet, R., Wilkinson, A. J., & Losick, R. M. (2017) · eLife · doi:10.7554/elife.26111 · Cited by 36 · see citing works
“Structural comparison by the ECOD database, which classifies the evolutionary relationships of protein folds places PP2C phosphatases and the proteasome proteases in the same ‘Xgroup’, which is consistent with homology (Cheng et al., 2014).”
BackgroundMethodInfluentialOn the evolution of protein–adenine binding
Narunsky, A., Kessel, A., Solan, R., Alva, V., Kolodny, R., & Ben‐Tal, N. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1911349117 · Cited by 36 · see citing works
“The colors of the nodes encode the ECOD F-group classification (45), which is equivalent to PFAM’s protein family assignment (46).”
- Authors
- Cheng, H., Schaeffer, R. D., Liao, Y., Kinch, L. N., Pei, J., Shi, S., Kim, B.-H., & Grishin, N. V.
- Affiliations
- Howard Hughes Medical Institute (US)
- The University of Texas Southwestern Medical Center (US)
- Corresponding author
- Grishin, Nick V.
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-12-04
- Volume
- 10
- Issue
- 12
- Pages
- e1003926
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC4256011
- OpenAlex
- W1965827393
- Cited by
- 426
- References
- 61
- Citations by year
- 2026: 34 · 2025: 48 · 2024: 62 · 2023: 46 · 2022: 46 · 2021: 46 · 2020: 31 · 2019: 24 · 2018: 40 · 2017: 20 · 2016: 14 · 2015: 14
- FWCI
- 6.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Howard Hughes Medical Institute
- Welch Foundation (I-505)
- National Institutes of Health
- National Institute of General Medical Sciences (R01GM094575, GM-094575)
- 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 › Genomics and Phylogenetic Studies
- Keywords
- protein domain evolution, protein structure classification, homology, distant homologs, protein structure evolution, sequence families, PDB structures, protein domains, online databases
- MeSH terms
- Models, Molecular, Proteins, Protein Structure, Tertiary, Evolution, Molecular, Computational Biology, Databases, Protein
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.
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