Blinded Testing of Function Annotation for uPE1 Proteins by I-TASSER/COFACTOR Pipeline Using the 2018–2019 Additions to neXtProt and the CAFA3 Challenge
Open accessAbstract
In 2018, we reported a hybrid pipeline that predicts protein structures with I-TASSER and function with COFACTOR. I-TASSER/COFACTOR achieved Gene Ontology (GO) high prediction accuracies of Fmax = 0.69 and 0.57 for molecular function (MF) and biological process (BP), respectively, on 100 comprehensively annotated proteins. Now we report blinded analyses of newly annotated proteins in the critical assessment of function annotation (CAFA) three function prediction challenge and in neXtProt. For CAFA3 results released in May 2019, our predictions on 267 and 912 human proteins with newly annotated MF and BP terms achieved Fmax = 0.50 and 0.42, respectively, on "No Knowledge" proteins, and 0.51 and 0.74, respectively, on "Limited Knowledge" proteins. While COFACTOR consistently outperforms simple homology-based analysis, its accuracy still depends on template availability. Meanwhile, in neXtProt 2019-01, 25 proteins acquired new function annotation through literature curation at UniProt/Swiss-Prot. Before the release of these curated results, we submitted to neXtProt blinded predictions of free-text function annotation based on predicted GO terms. For 10 of the 25, a good match of free-text or GO term annotation was obtained. These blind tests represent rigorous assessments of I-TASSER/COFACTOR. neXtProt now provides links to precomputed I-TASSER/COFACTOR predictions for proteins without function annotation to facilitate experimental planning on "dark proteins".
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?
The I-TASSER/COFACTOR-based protocol accurately assigns functions for many microbial and human proteins and is among top predictors in CAFA3 and CAFA PI.
“This pipeline has been shown to accurately assign functions for many proteins in microbes22 and in humans25 and is among the top predictors in the most recent Critical Assessment of Function Annotation round 3 (CAFA3) and CAFA PI competitions.26”
A C-scoreFunc >0.5 corresponds to a confident function prediction.
“Each predicted function has a confidence score (C-scoreFunc) ranging from 0 to 1, with C-scoreFunc > 0.5 corresponding to a confident function prediction.22,25”
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
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302 · see citing works
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
Comparative Protein Modelling by Satisfaction of Spatial Restraints
Šali, A., & Blundell, T. L. (1993) · Journal of Molecular Biology · doi:10.1006/jmbi.1993.1626 · Cited by 12,977 · see citing works
STRING v10: protein–protein interaction networks, integrated over the tree of life
Szklarczyk, D., Franceschini, A., Wyder, S., Forslund, K., Heller, D., Huerta-Cepas, J., Simonovic, M., Roth, A., Santos, A., Tsafou, K. P., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gku1003 · Cited by 10,436 · see citing works
I-TASSER server for protein 3D structure prediction
Zhang, Y. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-40 · Cited by 5,124 · see citing works
Self-citationUniProt: the universal protein knowledgebase
The UniProt Consortium (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1099 · Cited by 4,436 · 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
Self-citationXSEDE: Accelerating Scientific Discovery
Towns, J. W., Cockerill, T. M., Dahan, M., Foster, I. T., Gaither, K., Grimshaw, A. S., Hazlewood, V., Lathrop, S. A., Lifka, D. A., Peterson, G. D., et al. (2014) · Computing in Science & Engineering · doi:10.1109/mcse.2014.80 · Cited by 3,114 · see citing works
Scoring function for automated assessment of protein structure template quality
Zhang, Y., & Skolnick, J. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20264 · Cited by 2,392 · see citing works
Self-citationPDBsum: Structural summaries of PDB entries
Laskowski, R., Jabłońska, J., Pravda, L., Vareková, R., & Thornton, J. (2017) · Protein Science · doi:10.1002/pro.3289 · Cited by 1,650 · see citing works
LOMETS: A local meta-threading-server for protein structure prediction
Wu, S., & Zhang, Y. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm251 · Cited by 774 · see citing works
Self-citationBioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions
Yang, J., Roy, A., & Zhang, Y. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks966 · Cited by 749 · see citing works
Self-citationZhang, C., Freddolino, L., & Zhang, Y. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx366 · Cited by 606 · see citing works
Self-citationDeepGOPlus: improved protein function prediction from sequence
Kulmanov, M., & Hoehndorf, R. (2019) · bioRxiv · doi:10.1093/bioinformatics/btz595 · Cited by 477 · see citing works
Zhou, N., Jiang, Y., Bergquist, T. R., Lee, A. J., Kacsoh, B. Z., Crocker, A. W., Lewis, K. A., Georghiou, G., Nguyen, H. N., Hamid, M. N., et al. (2019) · Genome Biology · doi:10.1186/s13059-019-1835-8 · Cited by 452 · see citing works
Self-citationProtein length in eukaryotic and prokaryotic proteomes
Brocchieri, L. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki615 · Cited by 414 · see citing works
SPICKER: A clustering approach to identify near‐native protein folds
Zhang, Y., & Skolnick, J. (2004) · Journal of Computational Chemistry · doi:10.1002/jcc.20011 · Cited by 393 · see citing works
Self-citationAn expanded evaluation of protein function prediction methods shows an improvement in accuracy
Jiang, Y., Oron, T. R., Clark, W. T., Bankapur, A., D’Andrea, D., Lepore, R., Funk, C. S., Kahanda, I., Verspoor, K. M., Ben‐Hur, A., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1037-6 · Cited by 390 · see citing works
Zhang, J., Yu, L., & Zhang, Y. (2011) · Structure · doi:10.1016/j.str.2011.09.022 · Cited by 332 · see citing works
Self-citationCritical assessment of methods of protein structure prediction (CASP)—Round XII
Moult, J., Fidelis, K. A., Kryshtafovych, A., Schwede, T. F., & Tramontano, A. L. (2017) · Proteins Structure Function and Bioinformatics · doi:10.1002/prot.25415 · Cited by 327 · see citing works
Dana, J., Gutmanas, A., Tyagi, N., Qi, G., O'Donovan, C., Martin, M., & Velankar, S. (2018) · Nucleic Acids Res. · doi:10.1093/nar/gky1114 · Cited by 258 · see citing works
GOtcha: a new method for prediction of protein function assessed by the annotation of seven genomes
Martin, D. M. A., Berriman, M., & Barton, G. J. (2004) · BMC Bioinformatics · doi:10.1186/1471-2105-5-178 · Cited by 245 · see citing works
Cao, R., Freitas, C., Chan, L., Sun, M., Jiang, H., & Chen, Z. (2017) · Molecules · doi:10.3390/molecules22101732 · Cited by 203 · see citing works
DeepGOPlus: improved protein function prediction from sequence
Kulmanov, M., & Hoehndorf, R. (2021) · Computer applications in the biosciences · doi:10.1093/bioinformatics/btaa763 · Cited by 199 · see citing works
The neXtProt knowledgebase on human proteins: 2017 update
Gaudet, P., Michel, P.-A., Zahn-Zabal, M., Britan, A., Cusin, I., Domagalski, M., Duek, P. D., Gateau, A., Gleizes, A., Hinard, V., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1062 · Cited by 164 · see citing works
Self-citationSchnoes, A. M., Ream, D. C., Thorman, A. W., Babbitt, P. C., & Friedberg, I. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003063 · Cited by 129 · see citing works
I-TASSER gateway: A protein structure and function prediction server powered by XSEDE
Zheng, W. H., Zhang, C., Bell, E. W., & Zhang, Y. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2019.04.011 · Cited by 108 · see citing works
Self-citationTTC39B deficiency stabilizes LXR reducing both atherosclerosis and steatohepatitis
Hsieh, J., Koseki, M., Molusky, M. M., Yakushiji, E., Ichi, I., Westerterp, M., Iqbal, J., Chan, R., Abramowicz, S., Tascau, L., et al. (2016) · Nature · doi:10.1038/nature18628 · Cited by 98 · see citing works
GoFDR: A sequence alignment based method for predicting protein functions
Gong, Q., Ning, W., & Tian, W. (2015) · Methods · doi:10.1016/j.ymeth.2015.08.009 · Cited by 84 · see citing works
Predicting human protein function with multi-task deep neural networks
Fa, R., Cozzetto, D., Wan, C., & Jones, D. T. (2018) · PLoS ONE · doi:10.1371/journal.pone.0198216 · Cited by 82 · see citing works
Zhang, C., Zheng, W., Freddolino, L., & Zhang, Y. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.03.004 · Cited by 80 · see citing works
Self-citationClipping of arginine-methylated histone tails by JMJD5 and JMJD7
Liu, H., Wang, C., Lee, S., Deng, Y. F., Wither, M. J., Oh, S., Ning, F., Dege, C., Zhang, Q., Liu, X., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1706831114 · Cited by 78 · see citing works
Zhou, N., Jiang, Y., Bergquist, T. R., Lee, A. J., Kacsoh, B. Z., Crocker, A. W., Lewis, K. A., Georghiou, G., Nguyen, H. N., Hamid, M.-N., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/653105 · Cited by 62 · see citing works
Self-citationPaik, Y., Lane, L., Kawamura, T., Chen, Y., Cho, J., LaBaer, J., Yoo, J. S., Domont, G. B., Corrales, F. J., Omenn, G. S., et al. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00383 · Cited by 48 · see citing works
Self-citationRELT induces cellular death in HEK 293 epithelial cells
Cusick, J., Mustian, A., Goldberg, K., & Reyland, M. E. (2009) · Cellular Immunology · doi:10.1016/j.cellimm.2009.10.013 · Cited by 44 · see citing works
The Jumonji-C oxygenase JMJD7 catalyzes (3S)-lysyl hydroxylation of TRAFAC GTPases
Markolovic, S., Zhuang, Q., Wilkins, S. E., Eaton, C. D., Abboud, M. I., Katz, M. J., McNeil, H. E., Leśniak, R. K., Hall, C., Struwe, W. B., et al. (2018) · Nature Chemical Biology · doi:10.1038/s41589-018-0071-y · Cited by 44 · see citing works
Exploring the Uncharacterized Human Proteome Using neXtProt
Duek, P. D., Gateau, A., Bairoch, A., & Lane, L. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00537 · Cited by 42 · see citing works
Self-citationRELT family members activate p38 and induce apoptosis by a mechanism distinct from TNFR1
Moua, P., Checketts, M., Xu, L., Shu, H., Reyland, M. E., & Cusick, J. (2017) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2017.07.022 · Cited by 41 · see citing works
Głogowska, A., Kunanuvat, U., Stetefeld, J., Patel, T. R., Thanasupawat, T., Krcek, J. P., Weber, E., Wong, G. W., Bigio, M. R. D., Hoang‐Vu, C., et al. (2013) · The Journal of Pathology · doi:10.1002/path.4257 · Cited by 40 · see citing works
Zhang, C., Wei, X., Omenn, G. S., & Zhang, Y. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00453 · Cited by 34 · see citing works
Self-citationDeepGOPlus: Improved protein function prediction from sequencePreprint
Kulmanov, M., & Hoehndorf, R. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/615260 · Cited by 33 · see citing works
Kacsoh, B. Z., Barton, S., Jiang, Y., Zhou, N., Mooney, S. D., Friedberg, I., Predrag Radivojac, A., Greene, C. S., & Bosco, G. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200867 · Cited by 23 · see citing works
Paik, Y.-K., Overall, C. M., Corrales, F., Deutsch, E. W., Lane, L., & Omenn, G. S. (2018) · Journal of Proteome Research · doi:10.1021/acs.jproteome.8b00885 · Cited by 21 · see citing works
Self-citationA close look at protein function prediction evaluation protocols
Kahanda, I., Funk, C. S., Ullah, F., Verspoor, K. M., & Ben‐Hur, A. (2015) · GigaScience · doi:10.1186/s13742-015-0082-5 · Cited by 17 · see citing works
Beasley, L., & Manda, P. (2018) · doi:10.7287/peerj.preprints.27028v1 · Cited by 7 · see citing works
Wu, J., Yin, Q., Zhang, C., Geng, J., Wu, H., Hu, H., Ke, X., & Zhang, Y. (2019) · ACS Omega · doi:10.1021/acsomega.8b02454 · Cited by 4 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [7]Zhang C; Omenn GS; Zhang Y Structure and Protein Interaction-based Gene Ontology Annotations Reveal Likely Functions of Uncharacterized Proteins on Human Chromosome 17; HUPO World Congress: Orlando, FL, 2018. PMC6438760 30265558
Cited by
Sorted by citations
Zhou, X., Zheng, W. H., Li, Y., Pearce, R., Zhang, C., Bell, E. W., Zhang, G., & Zhang, Y. (2022) · Nature Protocols · doi:10.1038/s41596-022-00728-0 · Cited by 526 · see citing works
Self-citationA high-stringency blueprint of the human proteome
Adhikari, S., Nice, E. C., Deutsch, E. W., Lane, L., Omenn, G. S., Pennington, S. R., Paik, Y.-K., Overall, C. M., Corrales, F. J., Cristea, I. M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19045-9 · Cited by 210 · see citing works
Self-citationOmenn, G. S., Lane, L., Overall, C. M., Cristea, I. M., Corrales, F. J., Lindskog, C., Paik, Y., Eyk, J. E. V., Liu, S., Pennington, S. R., et al. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00485 · Cited by 40 · see citing works
Self-citationOmenn, G. S., Lane, L., Overall, C. M., Corrales, F. J., Schwenk, J. M., Paik, Y.-K., Van Eyk, J. E., Liu, S., Pennington, S., Snyder, M. P., et al. (2019) · Journal of Proteome Research · doi:10.1021/acs.jproteome.9b00434 · Cited by 40 · see citing works
Self-citationOmenn, G. S., Lane, L., Overall, C. M., Paik, Y., Cristea, I. M., Corrales, F. J., Lindskog, C., Weintraub, S. T., Roehrl, M. H. A., Liu, S., et al. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.1c00590 · Cited by 39 · see citing works
Self-citationThe 2024 Report on the Human Proteome from the HUPO Human Proteome Project
Omenn, G. S., Orchard, S. E., Lane, L., Lindskog, C., Pineau, C., Overall, C. M., Budnik, B., Mudge, J. M., Packer, N. H., Weintraub, S. T., et al. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00776 · Cited by 32 · see citing works
Self-citationOmenn, G. S. (2021) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2021.100062 · Cited by 31 · see citing works
Self-citationZhang, C., Zheng, W., Cheng, M., Omenn, G. S., Freddolino, P. L., & Zhang, Y. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00359 · Cited by 27 · see citing works
Self-citationMohan, H. M., Trzeciakiewicz, H., Pithadia, A. S., Crowley, E. V., Pacitto, R., Safren, N., Trotter, B., Zhang, C., Zhou, X., Zhang, Y., et al. (2022) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04170-z · Cited by 21 · see citing works
Self-citationPredicting the structural impact of human alternative splicing
Song, Y., Zhang, C., Omenn, G. S., O’Meara, M. J., & Welch, J. D. (2025) · Genome biology · doi:10.1186/s13059-025-03744-x · Cited by 15 · see citing works
Self-citationPredicting Functions of Uncharacterized Human Proteins: From Canonical to Proteoforms
Poverennaya, E. V., Kiseleva, O. I., Romanova, A., & Pyatnitskiy, M. A. (2020) · Genes · doi:10.3390/genes11060677 · Cited by 12 · see citing works
Identifying Functions of Proteins in Mice With Functional Embedding Features
Li, H., Zhang, S., Chen, L., Pan, X., Li, Z., Huang, T., & Cai, Y. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.909040 · Cited by 11 · see citing works
Duek, P. D., Mary, C., Zahn‐Zabal, M., Bairoch, A., & Lane, L. (2021) · Database · doi:10.1093/database/baab046 · Cited by 11 · see citing works
Self-citationBanerjee, A., Biswas, D., Barpanda, A., Halder, A., Sibal, S., Kattimani, R., Shah, A., Mahadevan, A., Goel, A. H., & Srivastava, S. (2022) · Molecular & Cellular Proteomics · doi:10.1016/j.mcpro.2022.100478 · Cited by 10 · see citing works
The Human Proteome: 90% in the Light, 10% on the Dark Side
Overall, C. M. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00914 · Cited by 9 · see citing works
Bioinformatic Prediction of Gene Ontology Terms of Uncharacterized Proteins from Chromosome 11
Hwang, H., Im, J.-E., Yang, Y., Kim, H., Kwon, K., Kim, Y., Kim, J. Y., & Yoo, J. S. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00482 · Cited by 8 · see citing works
What will neXtProt help us achieve in 2020 and beyond?
Zahn‐Zabal, M., & Lane, L. (2020) · Expert Review of Proteomics · doi:10.1080/14789450.2020.1733418 · Cited by 7 · see citing works
Self-citationEvolution of Protein Functional Annotation: Text Mining Study
Ilgisonis, E. V., Pogodin, P. V., Kiseleva, O. I., Tarbeeva, S. N., & Ponomarenko, E. A. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12030479 · Cited by 6 · see citing works
González-Gomariz, J., Serrano, G., Tilve-Álvarez, C. M., Corrales, F. J., Guruceaga, E., & Segura, V. (2020) · Journal of Proteome Research · doi:10.1021/acs.jproteome.0c00364 · Cited by 5 · see citing works
AI-driven insights into protein misfolding and innate immunity in neurodegenerative diseases
Deng, H. X., Cao, J. L., Yao, W., Jiang, S. J., Fang, Q. Q., Zhu, B. Y., & Jiang, Y. J. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1814357 · Cited by 2 · see citing works
Flashlight into the Function of Unannotated C11orf52 using Affinity Purification Mass Spectrometry
Yang, Y., Hwang, H., Im, J.-E., Lee, K., Bhoo, S. H., Yoo, J. S., Kim, Y., & Kim, J. Y. (2021) · Journal of Proteome Research · doi:10.1021/acs.jproteome.1c00540 · Cited by 2 · see citing works
Margaretha, F., Subagja, M., Putri, A. D., Salam, C. Q., Valenthenardo, L., Adhiwijaya, P. K., Kaitlyn, G. Z., & Parikesit, A. A. (2023) · Berkala Penelitian Hayati · doi:10.23869/bphjbr.29.3.20232 · Cited by 2 · see citing works
- Authors
- Zhang, C., Lane, L., Omenn, G. S., & Zhang, Y.
- Affiliations
- University of Michigan (US)
- University of Geneva (CH)
- Corresponding author
- Omenn, Gilbert S.
- Zhang, Yang
- Venue
- Journal of Proteome Research
- Publisher
- American Chemical Society (ACS)
- Published
- 2019-10-04
- Volume
- 18
- Issue
- 12
- Pages
- 4154-4166
- ISSN
- 1535-3893 (ISSN-L)
- 1535-3907
- PMC
- PMC6900986
- OpenAlex
- W2977445573
- Cited by
- 22
- References
- 45
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2023: 1 · 2022: 5 · 2021: 5 · 2020: 7 · 2019: 1
- FWCI
- 1.49
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Journal of Proteome Research (publishedVersion)
- PubMed (publishedVersion)
- Archive ouverte UNIGE (University of Geneva) (publishedVersion)
- PubMed Central (acceptedVersion)
- Archive ouverte UNIGE (University of Geneva) (submittedVersion)
- Funders
- Universit? de Gen?ve
- National Institutes of Health (GM116960, P30ES017885, U24CA210967, AI134678, GM083107)
- National Science Foundation (DBI1564756)
- SIB Swiss Institute of Bioinformatics
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- protein function prediction, Gene Ontology, I-TASSER, cofactors, neXtProt, protein structure prediction, molecular function, biological processes, homology-based annotation
- MeSH terms
- Humans, Proteins, Computational Biology, Databases, Protein, Molecular Sequence Annotation
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
