ArticlePLoS computational biology2022
Mining folded proteomes in the era of accurate structure prediction.
Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- Chromosomal rearrangements and segmental deletions contribute to gene loss in squamates.BMC biology · 2026Article
- The complete catalog of antimicrobial resistance secondary active transporters inComputational and structural biotechnology journal · 2024Article
- AlphaFold and Protein Folding: Not Dead Yet! The Frontier Is Conformational Ensembles.Annual review of biomedical data science · 2024Review
- Exploring Scoring Function Space: Developing Computational Models for Drug Discovery.Current medicinal chemistry · 2024Review
- Updated protein domain annotation of the PARP protein family sheds new light on biological function.Nucleic acids research · 2023Article
- Unanticipated broad phylogeny of BEN DNA-binding domains revealed by structural homology searches.Current biology : CB · 2023Article
- Novel machine learning approaches revolutionize protein knowledge.Trends in biochemical sciences · 2023Review
- Integrative modeling reveals the molecular architecture of the intraflagellar transport A (IFT-A) complex.eLife · 2022Article
- The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database.Molecular biology and evolution · 2022Article
- Article
- Dali server: structural unification of protein families.Nucleic acids research · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein structure fundamentally underpins the function and processes of numerous biological systems. Fold recognition algorithms offer a sensitive and robust tool to detect structural, and thereby functional, similarities between distantly related homologs. In the era of accurate structure prediction owing to advances in machine learning techniques and a wealth of experimentally determined structures, previously curated sequence databases have become a rich source of biological information. Here, we use bioinformatic fold recognition algorithms to scan the entire AlphaFold structure database to identify novel protein family members, infer function and group predicted protein structures. As an example of the utility of this approach, we identify novel, previously unknown members of various pore-forming protein families, including MACPFs, GSDMs and aerolysin-like proteins.
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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.