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Record W2797346936 · doi:10.1080/09687688.2018.1448123

Structural biology of solute carrier (SLC) membrane transport proteins

2017· article· en· W2797346936 on OpenAlexafffund
Xiaoyun Bai, Trevor F. Moraes, Reinhart A.F. Reithmeier

Bibliographic record

VenueMolecular Membrane Biology · 2017
Typearticle
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsAntiportersMajor facilitator superfamilyTransporterSolute carrier familySymporterLactose permeaseMembrane transport proteinTransport proteinSUPERFAMILYMembrane transportBiochemistrySequence homologyHomology modelingChemistryBiologyBiophysicsAmino acidMembrane proteinMembranePeptide sequenceEnzymeReceptorGene

Abstract

fetched live from OpenAlex

) gradients as the driving force for the transport of substrate against its concentration gradient into cells. Other members work as antiporters (exchangers) that typically contain a single substrate-binding site with an alternating access mode of transport, while a few members exhibit channel-like properties. Dysfunction of SLCs is correlated with numerous human diseases and therefore they are potential therapeutic drug targets. In this review, we identified all of the SLC crystal structures that have been determined, most of which are from prokaryotic species. We further sorted all the SLC structures into four main groups with different protein folds and further discuss the well-characterized MFS (major facilitator superfamily) and LeuT (leucine transporter) folds. This review provides a systematic analysis of the structure, molecular basis of substrate recognition and mechanism of action in different SLC family members.

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: Review · Consensus signal: Review
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 communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.276
Teacher spread0.260 · 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
GenreReview

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

Citations179
Published2017
Admission routes2
Has abstractyes

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