ArticleNature methods2024
Improving deep learning protein monomer and complex structure prediction using DeepMSA2 with huge metagenomics data.
Article in Nature methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
75 citing papers in PubMed.
- Massive Sampling Strategy for Antibody-Antigen Targets in CAPRI Round 55 With MassiveFold.Proteins · 2026Article
- In situ evidence of tiered adaptations buffering a chemosynthetic clam holobiont against environmental sulfide fluctuations.Science advances · 2026Article
- The insect effector CSPs activate an atypical plant TNL immune receptor.Plant cell reports · 2026Article
- Reconstitution of multistep recruitment of ULK1 to membranes in autophagy.Science advances · 2026Article
- Cross-protective human antibodies against the Mpox virus discovered through structure-guided screening.Cell discovery · 2026Article
- FusionTarget: Computational framework for drug repurposing against modeled fusion protein structures from genomic breakpoints.iScience · 2026Article
- Whole-proteome structure/function prediction in UropathogenicbioRxiv : the preprint server for biology · 2026Article
- SERPINI1 functions as a tumor suppressor in glioma.Scientific reports · 2026Article
- NEFFy: a versatile tool for computing the number of effective sequences.Bioinformatics (Oxford, England) · 2026Article
- Schistosoma japonicum histone acetyltransferase 1 (SjHAT1): A novel anti-schistosomal drug target.PLoS pathogens · 2026Article
- From possibility to precision in macromolecular ensemble prediction.Nature methods · 2026Article
- Improving protein and protein interactions using pseudo-dimers derived from monomeric proteins.Nature communications · 2026Article
- Multifaceted roles of CcGpi7, a phosphoethanolamine transferase, in physiology and virulence of Corynespora cassiicola.World journal of microbiology & biotechnology · 2026Article
- The nucleoid-associated protein subunit HupA positively regulates the Pqs system and pyocyanin production inApplied and environmental microbiology · 2026Article
- Sequence Display enables large-scale sequence-activity datasets for rapid protein evolution.Nature biotechnology · 2026Article
- Deep-learning-based single-domain and multidomain protein structure prediction with D-I-TASSER.Nature biotechnology · 2026Article
- Clustering the protein universe of life using DIAMOND DeepClust.Nature methods · 2026Article
- HFB301001, an OX40-based immunotherapy, drives Treg clearance and CTL activation through optimized OX40 receptor clustering.Journal for immunotherapy of cancer · 2026Article
- A paired sequence language model for protein-protein interaction modeling.Nature communications · 2026Article
- Artificial intelligence-enabled multi-scale virtual cell: perspective, challenges, and opportunities.Briefings in bioinformatics · 2026Review
15 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
6 authors.
Funding
Abstract
Leveraging iterative alignment search through genomic and metagenome sequence databases, we report the DeepMSA2 pipeline for uniform protein single- and multichain multiple-sequence alignment (MSA) construction. Large-scale benchmarks show that DeepMSA2 MSAs can remarkably increase the accuracy of protein tertiary and quaternary structure predictions compared with current state-of-the-art methods. An integrated pipeline with DeepMSA2 participated in the most recent CASP15 experiment and created complex structural models with considerably higher quality than the AlphaFold2-Multimer server (v.2.2.0). Detailed data analyses show that the major advantage of DeepMSA2 lies in its balanced alignment search and effective model selection, and in the power of integrating huge metagenomics databases. These results demonstrate a new avenue to improve deep learning protein structure prediction through advanced MSA construction and provide additional evidence that optimization of input information to deep learning-based structure prediction methods must be considered with as much care as the design of the predictor itself.
Indexed as
Identifiers
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.