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Record W2598099381 · doi:10.1039/c7md00052a

Histone lysine methyltransferase structure activity relationships that allow for segregation of G9a inhibition and anti-Plasmodium activity

2017· article· en· W2598099381 on OpenAlexafffund
Sandeep Sundriyal, Patty B. Chen, Alexandra Lubin, Gregor A. Lueg, Fengling Li, Andrew J. P. White, Nicholas A. Malmquist, Masoud Vedadi, Artur Scherf, Matthew J. Fuchter

Bibliographic record

VenueMedChemComm · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS drug development and treatment
Canadian institutionsUniversity of TorontoStructural Genomics ConsortiumToronto Public Health
FundersNovartis PharmaMinistero dello Sviluppo EconomicoWellcome TrustAgence Nationale de la RechercheWellcomeImperial College LondonCancer Research UKOntario Ministry of Economic Development and InnovationAlliance Française contre les Maladies ParasitairesEuropean Federation of Pharmaceutical Industries and AssociationsFundação de Amparo à Pesquisa do Estado de São PauloGenome CanadaEuropean CommissionPfizer
KeywordsLysineMethyltransferaseHistoneBiologyQuinazolineComputational biologyChemistryBiochemistryMethylationGeneStereochemistryAmino acid

Abstract

fetched live from OpenAlex

G9a selectivity can be achieved by selecting appropriate substituents at position 2, 4 and 7 of the quinazoline ring. We have also, in turn, discovered that potent G9a inhibitors can be identified by employing a 6-carbon 'Nle mimic' at position 7. Together, this data suggests that while broadly similar, the G9a and potential PfHKMT target(s) binding pockets and/or binding modes of the diaminoquinazoline analogues exhibit clear and exploitable differences. Based on this, we believe this scaffold to have clear potential for development into a novel anti-malarial therapeutic.

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 score0.003
Threshold uncertainty score0.010

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)0.0030.001

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 head0.052
GPT teacher head0.315
Teacher spread0.263 · 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

Citations28
Published2017
Admission routes2
Has abstractyes

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