Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 4 complete abstracts (643 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
Discrete protein structural units that may fold independently of the rest of the protein and have their own functions.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Protein Domain; Domain, Protein; Domains, Protein; Peptide Domain; Domain, Peptide; Domains, Peptide; Peptide Domains.
Where it fits in the MeSH classification
- Broader topics
- Protein Structural Elements; Protein Structure, Tertiary
- Narrower topics
- C2 Domains; Carbohydrate Binding Modules; Catalytic Domain; Discoidin Domain; HMG-Box Domains; Immunoglobulin Domains; Kringles; Methyl CpG Binding Domain; Pleckstrin Homology Domains; PR-SET Domains; Proline-Rich Protein Domains; Protein Interaction Domains and Motifs
Research landscape
PubMed indexes 82,533 records tagged with the MeSH heading “Protein Domains” (counts retrieved 2026-10-29). 21,871 of them (26.5%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 44,065 records.
Reviews account for 5,649 records (6.8%) and meta-analyses for 23. Randomized controlled trials number 17 (0.0%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.
Show the data
| Period | Records |
|---|---|
| through 1999 | 2,346 |
| 2000-2009 | 14,251 |
| 2010-2019 | 44,065 |
| 2020 onward | 21,871 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 5,649 | 6.8% |
| Meta-analyses | 23 | 0.0% |
| Randomized controlled trials | 17 | 0.0% |
Method: PubMed query "Protein Domains"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.
Reading the evidence in molecular biology
Molecular biology establishes mechanisms through controlled experiments, often in simplified systems such as purified proteins, cultured cells or model organisms. Such work can show what is possible in a defined system, but whether a pathway matters in a whole organism or in human disease needs further evidence. Check the experimental system, whether findings were reproduced by independent groups, and whether the authors tested the mechanism directly or inferred it from correlation.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Site-saturation mutagenesis of 500 human protein domains | 2025 | Research article Design not recorded in structured metadata | 125 | cc by PMID 39779847 · DOI · PMC11754108 |
| actifpTM: a refined confidence metric of AlphaFold2 predictions involving flexible regions | 2025 | Research article Design not recorded in structured metadata | 67 | cc by PMID 40080667 · DOI · PMC11925850 |
| Origin and functional diversification of PAS domain, a ubiquitous intracellular sensor | 2023 | Research article Design not recorded in structured metadata | 51 | cc by PMID 37647406 · DOI · PMC10468136 |
| Structural ontogeny of protein-protein interactions | 2026 | Research article Design not recorded in structured metadata | 5 | cc by PMID 41678610 · DOI · PMC12904254 |
Site-saturation mutagenesis of 500 human protein domains [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Missense variants that change the amino acid sequences of proteins cause one-third of human genetic diseases1.
- Closing excerpt
- Our data demonstrate the feasibility of assaying human protein variants at scale and provides a large consistent reference dataset for clinical variant interpretation and training and benchmarking of computational methods.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (175 words)
Missense variants that change the amino acid sequences of proteins cause one-third of human genetic diseases1. Tens of millions of missense variants exist in the current human population, and the vast majority of these have unknown functional consequences. Here we present a large-scale experimental analysis of human missense variants across many different proteins. Using DNA synthesis and cellular selection experiments we quantify the effect of more than 500,000 variants on the abundance of more than 500 human protein domains. This dataset reveals that 60% of pathogenic missense variants reduce protein stability. The contribution of stability to protein fitness varies across proteins and diseases and is particularly important in recessive disorders. We combine stability measurements with protein language models to annotate functional sites across proteins. Mutational effects on stability are largely conserved in homologous domains, enabling accurate stability prediction across entire protein families using energy models. Our data demonstrate the feasibility of assaying human protein variants at scale and provides a large consistent reference dataset for clinical variant interpretation and training and benchmarking of computational methods.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 39779847 · DOI · PMC11754108
actifpTM: a refined confidence metric of AlphaFold2 predictions involving flexible regions [2]
Abstract reading summary — source excerpts
- Opening excerpt
- SummaryOne of the main advantages of deep learning models of protein structure, such as Alphafold2, is their ability to accurately estimate the confidence of a generated structural model, which allows us to focus on highly confident predictions.
- Closing excerpt
- com/sokrypton/ColabFold) repository, installable both locally or usable with Colab notebook.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (191 words)
SummaryOne of the main advantages of deep learning models of protein structure, such as Alphafold2, is their ability to accurately estimate the confidence of a generated structural model, which allows us to focus on highly confident predictions. The ipTM score provides a confidence estimate of interchain contacts in protein-protein interactions. However, interactions, in particular motif-mediated interactions, often also contain regions that remain flexible upon binding. These noninteracting flanking regions are assigned low confidence values and will affect ipTM, as it considers all interchain residue-residue pairs, and two models of the same motif-domain interaction, but differing in the length of their flanking regions, would be assigned very different values. Here, we propose actual interface pTM (actifpTM), a modified ipTM measure, that focuses on the residues participating in the interaction, resulting in a more robust measure of interaction confidence. Besides, actifpTM is calculated both for the full complex as well as for each pair of chains, making it well-suited for evaluating multi-chain complexes with a particularly critical binding interface, such as antibody-antigen interactions.Availability and implementationThe method is available as part of the ColabFold (https://github.com/sokrypton/ColabFold) repository, installable both locally or usable with Colab notebook.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 40080667 · DOI · PMC11925850
Origin and functional diversification of PAS domain, a ubiquitous intracellular sensor [3]
Abstract reading summary — source excerpts
- Opening excerpt
- Signal perception is a key function in regulating biological activities and adapting to changing environments.
- Closing excerpt
- The close relatedness of human PAS domains to those in bacteria provides an opportunity for drug design by exploring potential natural ligands and cofactors for bacterial homologs.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (153 words)
Signal perception is a key function in regulating biological activities and adapting to changing environments. Per-Arnt-Sim (PAS) domains are ubiquitous sensors found in diverse receptors in bacteria, archaea, and eukaryotes, but their origins, distribution across the tree of life, and extent of their functional diversity are not fully characterized. Here, we show that using sequence conservation and structural information, it is possible to propose specific and potential functions for a large portion of nearly 3 million PAS domains. Our analysis suggests that PAS domains originated in bacteria and were horizontally transferred to archaea and eukaryotes. We reveal that gas sensing via a heme cofactor evolved independently in several lineages, whereas redox and light sensing via flavin adenine dinucleotide and flavin mononucleotide cofactors have the same origin. The close relatedness of human PAS domains to those in bacteria provides an opportunity for drug design by exploring potential natural ligands and cofactors for bacterial homologs.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 37647406 · DOI · PMC10468136
Structural ontogeny of protein-protein interactions [4]
Abstract reading summary — source excerpts
- Opening excerpt
- Understanding how protein binding sites evolve interactions with other proteins could hold clues to targeting "undruggable" surfaces.
- Closing excerpt
- Our results suggest that "silent" surfaces have a shallower energy landscape than natural binding sites, disfavoring tight binding, likely owing to evolutionary counterselection.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (124 words)
Understanding how protein binding sites evolve interactions with other proteins could hold clues to targeting "undruggable" surfaces. We used synthetic coevolution to engineer new interactions between naïve surfaces, simulating the de novo formation of protein complexes. We isolated seven distinct structural families of protein Z-domain complexes and found that synthetic complexes explore multiple shallow energy wells through ratchet-like docking modes, whereas complexes formed by natural binding sites converged in a deep energy well with a relatively fixed geometry. Epistasis analysis of a machine learning-estimated fitness landscape revealed "seed" contacts between binding partners that anchored the earliest stages of encounter complex formation. Our results suggest that "silent" surfaces have a shallower energy landscape than natural binding sites, disfavoring tight binding, likely owing to evolutionary counterselection.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41678610 · DOI · PMC12904254
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Small molecules, big targets: drug discovery faces the protein-protein interaction challenge [5]
- Research article The pyruvate dehydrogenase complexes: structure-based function and regulation [6]
- Research article Structure-Based Design of Inhibitors of Protein-Protein Interactions: Mimicking Peptide Binding Epitopes [7]
- Research article Designed ankyrin repeat proteins (DARPins): binding proteins for research, diagnostics, and therapy [8]
- Research article The cullin-RING ubiquitin-protein ligases [9]
- Research article WD40 repeat domain proteins: a novel target class? [10]
References
- Beltran A, Jiang X, Shen Y, Lehner B. Site-saturation mutagenesis of 500 human protein domains. . 2025. PMID 39779847 · DOI · PMC11754108
- Varga JK, Ovchinnikov S, Schueler-Furman O. actifpTM: a refined confidence metric of AlphaFold2 predictions involving flexible regions. . 2025. PMID 40080667 · DOI · PMC11925850
- Xing J, Gumerov VM, Zhulin IB. Origin and functional diversification of PAS domain, a ubiquitous intracellular sensor. . 2023. PMID 37647406 · DOI · PMC10468136
- Yang A, Jiang H, Jude KM, Akpinaroglu D, Allenspach S, Li AJ, et al.. Structural ontogeny of protein-protein interactions. . 2026. PMID 41678610 · DOI · PMC12904254
- Scott DE, Bayly AR, Abell C, Skidmore J. Small molecules, big targets: drug discovery faces the protein-protein interaction challenge. Nat Rev Drug Discov. 2016. PMID 27050677 · DOI
- Patel MS, Nemeria NS, Furey W, Jordan F. The pyruvate dehydrogenase complexes: structure-based function and regulation. J Biol Chem. 2014. PMID 24798336 · DOI · PMC4059105
- Pelay-Gimeno M, Glas A, Koch O, Grossmann TN. Structure-Based Design of Inhibitors of Protein-Protein Interactions: Mimicking Peptide Binding Epitopes. Angew Chem Int Ed Engl. 2015. PMID 26119925 · DOI · PMC4557054
- Plückthun A. Designed ankyrin repeat proteins (DARPins): binding proteins for research, diagnostics, and therapy. Annu Rev Pharmacol Toxicol. 2015. PMID 25562645 · DOI
- Hua Z, Vierstra RD. The cullin-RING ubiquitin-protein ligases. Annu Rev Plant Biol. 2011. PMID 21370976 · DOI
- Schapira M, Tyers M, Torrent M, Arrowsmith CH. WD40 repeat domain proteins: a novel target class?. Nat Rev Drug Discov. 2017. PMID 29026209 · DOI · PMC5975957
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-29.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.