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Record W2922702782 · doi:10.1073/pnas.1814685116

Lysyl-tRNA synthetase as a drug target in malaria and cryptosporidiosis

2019· article· en· W2922702782 on OpenAlexaff
Beatriz Baragaña, Barbara Forte, Ryan Choi, Stephen N. Hewitt, Juan A. Bueren‐Calabuig, João Pedro Pisco, Caroline Peet, David M. Dranow, David A. Robinson, Chimed Jansen, Neil R. Norcross, Sumiti Vinayak, Mark Anderson, Carrie F. Brooks, Caitlin Cooper, Sebastian Damerow, Michael J. Delves, Karen Dowers, James Duffy, Thomas E. Edwards, Irene Hallyburton, Benjamin G. Horst, Matthew A. Hulverson, Liam Ferguson, Marı́a Belén Jiménez-Dı́az, Rajiv S. Jumani, Donald D. Lorimer, Melissa S. Love, Steven P. Maher, Holly Matthews, Case W. McNamara, Peter G. Miller, Sandra M. O’Neill, Kayode K. Ojo, Maria Osuna‐Cabello, Érika G. Pinto, John Post, Jennifer Riley, Matthias Rottmann, Laura M. Sanz, Paul Scullion, Arvind Sharma, Sharon M. Shepherd, Yoko Shishikura, Frederick R. C. Simeons, Erin E. Stebbins, Laste Stojanovski, Ursula Straschil, Fábio K. Tamaki, J. Tamjar, Leah S. Torrie, Amélie Vantaux, Benoît Witkowski, Sergio Wittlin, M. Yogavel, Fabio Zuccotto, Íñigo Angulo‐Barturen, Robert E. Sinden, Jake Baum, Francisco‐Javier Gamo, Pascal Mäser, Dennis E. Kyle, Elizabeth A. Winzeler, Peter J. Myler, Paul G. Wyatt, David Floyd, David J. Matthews, Amit Sharma, Boris Striepen, Christopher D. Huston, David W. Gray, Alan H. Fairlamb, Andrei V. Pisliakov, Chris Walpole, Kevin D. Read, Wesley C. Van Voorhis, Ian H. Gilbert

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicParasitic Infections and Diagnostics
Canadian institutionsMcGill University Health CentreStructural Genomics ConsortiumUniversity of Toronto
FundersNational Center for Research ResourcesNational Institute of General Medical SciencesNational Institutes of HealthMedicines for Malaria VentureUniversity of DundeeWellcome TrustUniversity of California, San DiegoGlaxoSmithKlineDiamond Light SourceNational Institute of Allergy and Infectious DiseasesBill and Melinda Gates Foundation
KeywordsMalariaVirologyDrugMicrobiologyBiologyMedicineImmunologyPharmacology

Abstract

fetched live from OpenAlex

Malaria and cryptosporidiosis, caused by apicomplexan parasites, remain major drivers of global child mortality. New drugs for the treatment of malaria and cryptosporidiosis, in particular, are of high priority; however, there are few chemically validated targets. The natural product cladosporin is active against blood- and liver-stage Plasmodium falciparum and Cryptosporidium parvum in cell-culture studies. Target deconvolution in P. falciparum has shown that cladosporin inhibits lysyl-tRNA synthetase ( Pf KRS1). Here, we report the identification of a series of selective inhibitors of apicomplexan KRSs. Following a biochemical screen, a small-molecule hit was identified and then optimized by using a structure-based approach, supported by structures of both Pf KRS1 and C. parvum KRS ( Cp KRS). In vivo proof of concept was established in an SCID mouse model of malaria, after oral administration (ED 90 = 1.5 mg/kg, once a day for 4 d). Furthermore, we successfully identified an opportunity for pathogen hopping based on the structural homology between Pf KRS1 and Cp KRS. This series of compounds inhibit Cp KRS and C. parvum and Cryptosporidium hominis in culture, and our lead compound shows oral efficacy in two cryptosporidiosis mouse models. X-ray crystallography and molecular dynamics simulations have provided a model to rationalize the selectivity of our compounds for Pf KRS1 and Cp KRS vs. (human) Hs KRS. Our work validates apicomplexan KRSs as promising targets for the development of drugs for malaria and cryptosporidiosis.

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)0.001
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 score0.184
Threshold uncertainty score0.179

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.012
GPT teacher head0.271
Teacher spread0.258 · 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

Citations139
Published2019
Admission routes1
Has abstractyes

Explore more

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