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Discovery of Small Molecule Inhibitors that Interact with γ‐Tubulin

2012· article· en· W2107186420 on OpenAlexafffund
Douglas E. Friesen, Khaled Barakat, Valentyna Semenchenko, Rolando Pérez, Bruce W. Fenske, Jonathan Y. Mane, David S. Wishart, Jack A. Tuszyński

Bibliographic record

VenueChemical Biology & Drug Design · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer therapeutics and mechanisms
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsTubulinCombretastatinMicrotubuleColchicineDocking (animal)Drug discoveryComputational biologySmall moleculeBiologyGlioblastomaChemistryCell biologyBiochemistryCancer researchGeneticsMedicine

Abstract

fetched live from OpenAlex

Recent studies have shown an overexpression of γ-tubulin in human glioblastomas and glioblastoma cell lines. As the 2-year survival rate for glioblastoma is very poor, potential benefit exists for discovering novel chemotherapeutic agents that can inhibit γ-tubulin, which is known to form a ring complex that acts as a microtubule nucleation center. We present experimental evidence that colchicine and combretastatin A-4 bind to γ-tubulin, which are to our knowledge the first drug-like compounds known to interact with γ-tubulin. Molecular dynamics simulations and docking studies were used to analyze the hypothesized γ-tubulin binding domain of these compounds. The suitability of the potential binding modes was evaluated and suggests the subsequent rational design of novel targeted inhibitors of γ-tubulin.

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 score0.004

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 head0.020
GPT teacher head0.245
Teacher spread0.225 · 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

Citations36
Published2012
Admission routes2
Has abstractyes

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