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Record W2105429424 · doi:10.1002/cmdc.201000162

Structure‐Based Virtual Screening and Electrophysiological Evaluation of New Chemotypes of K<sub>v</sub>1.5 Channel Blockers

2010· article· en· W2105429424 on OpenAlexaff
Qian Yang, David Fedida, Hongjian Xu, Binghe Wang, Lüpei Du, Xiaojian Wang, Minyong Li, Qidong You

Bibliographic record

VenueChemMedChem · 2010
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversity of British Columbia
FundersNational Major Science and Technology Projects of China
KeywordsElectrophysiologyAtrial fibrillationVirtual screeningCardiologyChannel blockerMedicineInternal medicinePharmacologyBioinformaticsDrug discoveryBiology

Abstract

fetched live from OpenAlex

Atrial fibrillation (AF) is the most prevalent nonfatal cardiac rhythm disorder associated with an increased risk of heart failure and stroke. Considering the ventricular side effects induced by anti-arrhythmic agents in current use, K(v)1.5 channel blockers have attracted a great deal of deliberation owing to their selective actions on atrial electrophysiology. Herein we report new chemotypes of K(v)1.5 channel blockers that were identified through a combination of structure-based virtual screening and in silico druglike property prediction including six scoring functions, as well as electrophysiological evaluation. Among them, five of the 18 compounds exhibited >50 % blockade ratio at 10 microM, and have structural features different from conventional K(v)1.5 channel blockers. These novel scaffolds could serve as hits for further optimization and SAR studies for the discovery of selective agents to treat AF.

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)0.000
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 score0.016
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.019
GPT teacher head0.268
Teacher spread0.249 · 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

Citations11
Published2010
Admission routes1
Has abstractyes

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