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Record W2119189796 · doi:10.1021/bi400522b

Role of the Central Arginine R133 toward the Ion Selectivity of the Phosphate Specific Channel OprP: Effects of Charge and Solvation

2013· article· en· W2119189796 on OpenAlexafffund
Niraj Modi, Iván Bárcena‐Uribarri, Manjeet Bains, Roland Benz, Robert E. W. Hancock, Ulrich Kleinekathöfer

Bibliographic record

VenueBiochemistry · 2013
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsPorinChemistrySelectivityIon channelBiophysicsIonBacterial outer membraneBiochemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The outer membrane porin OprP of Pseudomonas aeruginosa forms a highly specific phosphate selective channel. This channel is responsible for the high-affinity uptake of phosphate ions into the periplasmic space of the bacteria. A detailed investigation of the structure-function relationship of OprP is inevitable to decipher the anion and phosphate selectivity of this porin in particular and to broaden the present understanding of the ion selectivity of different channels. To this end we investigated the role of the central arginine of OprP, R133, in terms of its effects in selectivity and ion transport properties of the pore. Electrophysiological bilayer measurements and free-energy molecular dynamics simulations were carried out to probe the transport of different ions through various R133 mutants. For these mutants, the change in phosphate binding specificity, ion conduction, and anion selectivity was determined and compared to previous molecular dynamic calculations and electrophysiological measurements with wild-type OprP. Molecular analysis revealed a rather particular role of arginine 133 and its charge, while at the same time this residue together with the network of other residues, namely, D94 and Y114, has the ability to dehydrate the permeating ion. These very specific features govern the ion selectivity of OprP.

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 score0.051
Threshold uncertainty score0.251

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 head0.003
GPT teacher head0.152
Teacher spread0.148 · 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

Citations29
Published2013
Admission routes2
Has abstractyes

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