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Record W2063003826 · doi:10.1074/jbc.m504403200

Ligand-assisted Aggregation of Proteins

2005· article· en· W2063003826 on OpenAlexaff
Jason Ho, Pavel I. Kitov, Eugenia Paszkiewicz, Joanna Sadowska, David R. Bundle, Kenneth Ng

Bibliographic record

VenueJournal of Biological Chemistry · 2005
Typearticle
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsChemistryLigand (biochemistry)Computational biologyBiophysicsBiologyBiochemistryReceptor

Abstract

fetched live from OpenAlex

A comprehensive series of solution and crystallographic studies reveal how simple, achiral, bivalent ligands of the cyclic pyruvate of glycerol promote face-to-face complex formation of the pentraxin, serum amyloid P component (SAP) into decamers. SAP, a protein of the human innate immune system, is universally present in amyloids, including cerebral amyloid deposits found in the brain of Alzheimer disease patients. Removal of SAP through a specific aggregation mechanism mediated by multivalent ligands appears to provide therapeutic benefit in the progression of this disease. Crystallographic studies reveal that in our novel series of ligands only the methyl and carboxylate moieties of the pyruvate ketal directly interact with the protein, but the geometric constraints imposed by the tether dictate which of two chair conformations are adopted by the pyruvate dioxane ring. Solution studies, as interpreted through a simple thermodynamic model, account for the distribution of pentameric and decameric bound states at different ligand concentrations and indicate that differences in the flexibility of the tether determine the geometry and stability of the specific aggregates formed between SAP and two different bivalent ligands. The factors affecting the design of ligands promoting face-to-face protein dimerization as well as potential biological implications are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.025
GPT teacher head0.257
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), 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

Citations35
Published2005
Admission routes1
Has abstractyes

Explore more

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