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Record W4402645719 · doi:10.1134/s199074782470017x

Structural Studies of Ion Channels: Achievements, Problems, and Perspectives

2024· article· en· W4402645719 on OpenAlexaff
Boris S. Zhorov, Denis B. Tikhonov

Bibliographic record

VenueBiochemistry (Moscow) Supplement Series A Membrane and Cell Biology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIon channel regulation and function
Canadian institutionsMcMaster University
Fundersnot available
KeywordsIon channelComputer scienceChemistryComputational biologyBiologyGenetics

Abstract

fetched live from OpenAlex

The superfamily of membrane proteins known as P-loop channels encompasses potassium, sodium, and calcium channels, as well as TRP channels and ionotropic glutamate receptors. An increasing number of crystal and cryo-EM structures are uncovering both general and specific features of these channels. Fundamental folding principles, the arrangement of structural segments, key residues that influence ionic selectivity, gating, and binding sites for toxins and medically relevant ligands have now been firmly established. The advent of AlphaFold2 models represents another significant step in computationally predicting protein structures. Comparison of experimental P-loop channel structures with their corresponding AlphaFold2 models shows consistent folding patterns in experimentally resolved regions. Despite this remarkable progress, many crucial structural details, particularly important for predicting the outcomes of mutations and designing new medically relevant ligands, remain unresolved. Certain methodological challenges currently hinder the direct assessment of such details. Until the next methodological breakthrough occurs, a promising approach to analyzing ion channel structures in greater depth involves integrating various experimental and theoretical methods.

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 score0.046
Threshold uncertainty score0.821

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 head0.022
GPT teacher head0.263
Teacher spread0.241 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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