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Record W2109685531 · doi:10.1002/jmr.961

Protein dynamics and conformational disorder in molecular recognition

2009· review· en· W2109685531 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Molecular Recognition · 2009
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Structure and Dynamics
Canadian institutionsCanada Research ChairsUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsIntrinsically disordered proteinsBiophysicsProtein structureConformational isomerismMolecular recognitionMolecular dynamicsChemistryProtein domainPlasma protein bindingComputational biologyBiologyBiochemistryComputational chemistry

Abstract

fetched live from OpenAlex

Recognition requires protein flexibility because it facilitates conformational rearrangements and induced-fit mechanisms upon target binding. Intrinsic disorder is an extreme on the continuous spectrum of possible protein dynamics and its role in recognition may seem counterintuitive. However, conformational disorder is widely found in many eukaryotic regulatory proteins involved in processes such as signal transduction and transcription. Disordered protein regions may in fact confer advantages over folded proteins in binding. Rapidly interconverting and diverse conformers may create mean electrostatic fields instead of presenting discrete charges. The resultant "polyelectrostatic" interactions allow for the utilization of post-translational modifications as a means to change the net charge and thereby modify the electrostatic interaction of a disordered region. Plasticity of disordered protein states enables steric advantages over folded proteins and allows for unique binding configurations. Disorder may also have evolutionary advantages, as it facilitates alternative splicing, domain shuffling and protein modularity. As proteins exist in a continuous spectrum of disorder, so do their complexes. Indeed, disordered regions in complexes may control the degree of motion between domains, mask binding sites, be targets of post-translational modifications, permit overlapping binding motifs, and enable transient binding of different binding partners, making them excellent candidates for signal integrators and explaining their prevalence in eukaryotic signaling pathways. "Dynamic" complexes arise if more than two transient protein interfaces are involved in complex formation of two binding partners in a dynamic equilibrium. "Disordered" complexes, in contrast, do not involve significant ordering of interacting protein segments but rely exclusively on transient contacts. The nature of these interactions is not well understood yet but advancements in the structural characterization of disordered states will help us gain insights into their function and their implications for health and disease.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.266
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it