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Record W2147217154 · doi:10.1111/mmi.12648

Probing druggability and biological function of essential proteins in <scp><i>L</i></scp><i>eishmania</i> combining facilitated null mutant and plasmid shuffle analyses

2014· article· en· W2147217154 on OpenAlexaff
Mariko Dacher, Miguel A. Morales, Pascale Pescher, L Olivier, Najma Rachidi, Eric Prina, Mathieu Cayla, Albert Descoteaux, Gérald F. Späth

Bibliographic record

VenueMolecular Microbiology · 2014
Typearticle
Languageen
FieldMedicine
TopicResearch on Leishmaniasis Studies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersAgence Nationale de la Recherche
KeywordsBiologyDruggabilityPlasmidMutantFunction (biology)GeneticsComputational biologyNull (SQL)Gene

Abstract

fetched live from OpenAlex

Leishmania parasites cause important human morbidity and mortality. Essential Leishmania genes escape genetic assessment by loss-of-function analyses due to lethal null mutant phenotypes, even though these genes and their products are biologically most significant and represent validated drug targets. Here we overcome this limitation using a facilitated null mutant approach applied for the functional genetic analysis of the MAP kinase LmaMPK4. This system relies on the episomal expression of the target gene from vector pXNG that expresses the Herpes simplex virus thymidine kinase gene thus rendering transgenic parasites susceptible for negative selection using the antiviral drug ganciclovir. Using this system we establish the genetic proof of LmaMPK4 as essential kinase in promastigotes. LmaMPK4 structure/function analysis by plasmid shuffle allowed us to identify regulatory kinase sequence elements relevant for chemotherapeutic intervention. A partial null mutant, expressing an MPK4 derivative with altered ATP-binding properties, showed defects in metacyclogenesis, establishing a first link of MPK4 function to parasite differentiation. The approaches presented here are broadly applicable to any essential gene in Leishmania thus overcoming major bottlenecks for their functional genetic analysis and their exploitation for structure-informed drug development.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.050
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.025
GPT teacher head0.287
Teacher spread0.262 · 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

Citations34
Published2014
Admission routes1
Has abstractyes

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