ReviewNature protocols2022
I-TASSER-MTD: a deep-learning-based platform for multi-domain protein structure and function prediction.
Review in Nature protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 240 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
240 citing papers in PubMed, 492 citations in OpenAlex.
- MultilevelCurrent research in structural biology · 2026Article
- Integrated multi-omics identifies lineage-dependent myeloid cells recruitment and the APP-CD74 axis as an immunoregulatory target in pediatric high-grade glioma.Acta neuropathologica · 2026Article
- TKL3 regulates blood-stage fitness, male gamete fertility, and transmission-stage development in Plasmodium berghei.PLoS pathogens · 2026Article
- Upcycling Vegetable Waste Into Functional Food Ingredients via Synergistic Microbial Engineering and Artificial Intelligence.Comprehensive reviews in food science and food safety · 2026Review
- Immunization with the Tc85-Derived Peptide Displayed on Virus-like Particles Confers Protection againstACS omega · 2026Article
- Potent IgE-Mediated Allergenic Reduction in Human Serum by Casein-Polyphenol Conjugates Makes Personalized Oral Immunotherapy Credible.ACS food science & technology · 2026Article
- In Silico and Molecular Docking Analysis of Benzyl Isothiocyanate fromCurrent issues in molecular biology · 2026Article
- In Silico Characterization and Molecular Docking of the L-Arginase Gene From Alcaligenes aquatilis BC2.Biotechnology and applied biochemistry · 2026Article
- ETTAS: a modular aptamer-recruited platform for programmable translational activation.Nucleic acids research · 2026Article
- IMMUND: A Diagnostic and Therapeutic Pipeline to Uncover the Convergence in Functional Perturbation at Early Stages of Neurodegenerative Diseases and Multiple Sclerosis Based on Protein Markers.International journal of molecular sciences · 2026Article
- Immunoinformatics-based design of artificial chimeric proteins as universal vaccine candidates against foot-and-mouth disease virus serotypes A, O, and SAT2.Scientific reports · 2026Article
- Association of a Homozygous TYMP c.131G>C Variant With MNGIE in a Chinese Pedigree: Insights From Genetic Analysis and Computational Modeling.Molecular genetics & genomic medicine · 2026Article
- Computational analysis of non-synonymous SNPs in the sheep MC4R gene.Journal, genetic engineering & biotechnology · 2026Article
- HES3-dependent regulatory functions in development and fusion-positive rhabdomyosarcoma.bioRxiv : the preprint server for biology · 2026Article
- Advances and opportunities for computational interrogation of plant proteins.The Plant journal : for cell and molecular biology · 2026Review
- A bioinformatics pipeline for the design of a SART3-targeted cancer vaccine with enhanced immunogenicity.Genomics & informatics · 2026Article
- Restorative macrophage-derived RNAseT2 stimulates muscle stem cell fusion via an SLK/N-WASP/actin bundling dependent axis.Nature communications · 2026Article
- Spider peptides from Brachypelma smithi with slightly different amino acids at their C-terminal loops exert different insecticidal activities.Amino acids · 2026Article
- Sequence Display enables large-scale sequence-activity datasets for rapid protein evolution.Nature biotechnology · 2026Article
- Integrative Genomic and Structural Analysis Reveals Diversity and Stability of yefM-yoeBCurrent microbiology · 2026Article
180 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
Most proteins in cells are composed of multiple folding units (or domains) to perform complex functions in a cooperative manner. Relative to the rapid progress in single-domain structure prediction, there are few effective tools available for multi-domain protein structure assembly, mainly due to the complexity of modeling multi-domain proteins, which involves higher degrees of freedom in domain-orientation space and various levels of continuous and discontinuous domain assembly and linker refinement. To meet the challenge and the high demand of the community, we developed I-TASSER-MTD to model the structures and functions of multi-domain proteins through a progressive protocol that combines sequence-based domain parsing, single-domain structure folding, inter-domain structure assembly and structure-based function annotation in a fully automated pipeline. Advanced deep-learning models have been incorporated into each of the steps to enhance both the domain modeling and inter-domain assembly accuracy. The protocol allows for the incorporation of experimental cross-linking data and cryo-electron microscopy density maps to guide the multi-domain structure assembly simulations. I-TASSER-MTD is built on I-TASSER but substantially extends its ability and accuracy in modeling large multi-domain protein structures and provides meaningful functional insights for the targets at both the domain- and full-chain levels from the amino acid sequence alone.
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What OpenQuestion holds
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.