ArticlePloS one2015
Extending Protein Domain Boundary Predictors to Detect Discontinuous Domains.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Modern resources for intrinsic disorder predictions: protein language models, deep learning, meta-servers, and databases.Cellular and molecular life sciences : CMLS · 2026Review
- SPAED: harnessing AlphaFold output for accurate segmentation of phage endolysin domains.Bioinformatics (Oxford, England) · 2025Article
- Impact of Saturated and Unsaturated Oils on the Nonlinear Viscoelasticity, Microstructure, and 3D Printability of Fish Myofibrillar-Protein-Based Pastes and Gels.Gels (Basel, Switzerland) · 2025Article
- Multimodularity of a GH10 Xylanase Found in the Termite Gut Metagenome.Applied and environmental microbiology · 2021Article
- Protein domain identification methods and online resources.Computational and structural biotechnology journal · 2021Review
- ThreaDomEx: a unified platform for predicting continuous and discontinuous protein domains by multiple-threading and segment assembly.Nucleic acids research · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
A variety of protein domain predictors were developed to predict protein domain boundaries in recent years, but most of them cannot predict discontinuous domains. Considering nearly 40% of multidomain proteins contain one or more discontinuous domains, we have developed DomEx to enable domain boundary predictors to detect discontinuous domains by assembling the continuous domain segments. Discontinuous domains are predicted by matching the sequence profile of concatenated continuous domain segments with the profiles from a single-domain library derived from SCOP and CATH, and Pfam. Then the matches are filtered by similarity to library templates, a symmetric index score and a profile-profile alignment score. DomEx recalled 32.3% discontinuous domains with 86.5% precision when tested on 97 non-homologous protein chains containing 58 continuous and 99 discontinuous domains, in which the predicted domain segments are within ±20 residues of the boundary definitions in CATH 3.5. Compared with our recently developed predictor, ThreaDom, which is the state-of-the-art tool to detect discontinuous-domains, DomEx recalled 26.7% discontinuous domains with 72.7% precision in a benchmark with 29 discontinuous-domain chains, where ThreaDom failed to predict any discontinuous domains. Furthermore, combined with ThreaDom, the method ranked number one among 10 predictors. The source code and datasets are available at https://github.com/xuezhidong/DomEx.
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