ArticleJournal of molecular biology2018
MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.
Article in Journal of molecular biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed, 83 citations in OpenAlex.
- Artificial Intelligence Powers Protein Functional Annotation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Deep-learning-based single-domain and multidomain protein structure prediction with D-I-TASSER.Nature biotechnology · 2026Article
- A graphic and command line protocol for quick and accurate comparisons of protein and nucleic acid structures with US-align.Nature protocols · 2026Review
- Assessing Structural Classification Using AlphaFold2 Models Through ECOD-Based Comparative Analysis.Proteins · 2025Article
- EZpred: improving deep learning-based enzyme function prediction using unlabeled sequence homologs.bioRxiv : the preprint server for biology · 2025Article
- FINCHES: A Computational Framework for Predicting Intermolecular Interactions in Intrinsically Disordered Proteins.International journal of molecular sciences · 2025Review
- Machine Learning for Protein Function Prediction.Methods in molecular biology (Clifton, N.J.) · 2025Review
- The Historical Evolution and Significance of Multiple Sequence Alignment in Molecular Structure and Function Prediction.Biomolecules · 2024Review
- Intelligence model on sequence-based prediction of PPI using AISSO deep concept with hyperparameter tuning process.Scientific reports · 2024Article
- FURNA: A database for functional annotations of RNA structures.PLoS biology · 2024Article
- A large-scale assessment of sequence database search tools for homology-based protein function prediction.Briefings in bioinformatics · 2024Article
- Learning a generalized graph transformer for protein function prediction in dissimilar sequences.GigaScience · 2024Article
- Identification of Peptidoglycan Glycosyltransferase FtsI as a Potential Drug Target againstCurrent pharmaceutical design · 2024Article
- A large-scale assessment of sequence database search tools for homology-based protein function prediction.bioRxiv : the preprint server for biology · 2023Article
- TEMPROT: protein function annotation using transformers embeddings and homology search.BMC bioinformatics · 2023Article
- NetGO 3.0: Protein Language Model Improves Large-scale Functional Annotations.Genomics, proteomics & bioinformatics · 2023Article
- Improving automatic GO annotation with semantic similarity.BMC bioinformatics · 2022Article
- I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction.Nature protocols · 2022Review
- TripletGO: Integrating Transcript Expression Profiles with Protein Homology Inferences for Gene Function Prediction.Genomics, proteomics & bioinformatics · 2022Article
- US-align: universal structure alignments of proteins, nucleic acids, and macromolecular complexes.Nature methods · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.