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Record W2006415889 · doi:10.1021/bi034726u

Mass Spectrometric Based Mapping of the Disulfide Bonding Patterns of Integrin α Chains

2003· article· en· W2006415889 on OpenAlexaff
Oleg V. Krokhin, Keding Cheng, Sandra Sousa, Werner Ens, Kenneth G. Standing, John A. Wilkins

Bibliographic record

VenueBiochemistry · 2003
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsUniversity of Manitoba
FundersNational Institute of General Medical Sciences
KeywordsDisulfide bondChemistryIntegrinBiochemistryCombinatorial chemistryReceptor

Abstract

fetched live from OpenAlex

Integrins are one of the major mediators of cellular adherence. Structurally the component alpha and beta chains are characterized by extensive intrachain disulfide bonding. The assignment of these bonds is currently based on homology with the chains of the integrin alphaIIbbeta3. However, recent crystallographic analysis of the soluble alphaVbeta3 construct indicates that the alphaV chain displays bonding patterns different from those predicted for alphaIIb. In an effort to define the disulfide bonding patterns in integrins, we have used mass spectrometric based approaches to map the human alpha3, alpha5, alphaV, and alphaIIb. The results indicate that there are differences in the disulfide patterns of the alpha chains. These do not correlate with the integrin capacity to bind ligands as all integrins used in the present study displayed functional activity. The differences were observed in the bonding patterns linking the heavy (H) and light (L) components of the of the alpha chains. It was also possible to assign the location in alpha5 of an additional disulfide bond involving a pair of cysteines not present in alphaV or alphaIIb. This second bond between the H and L chains of alpha5 has not been previously described. These results indicate that not all integrin species display the same disulfide bonding patterns. They also highlight the need for caution in the use of assignments based on sequence homology.

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.

How this classification was reachedexpand

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.274
Teacher spread0.252 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations29
Published2003
Admission routes1
Has abstractyes

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