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Enregistrement W4396881691 · doi:10.3389/fphar.2024.1423979

Editorial: Advancing therapeutic strategies: exploring ABC transporters and chemicals affecting their expression and function for disease treatment

2024· editorial· en· W4396881691 sur OpenAlexaff
Guido Veit, Michinori Matsuo, Tsukasa Okiyoneda

Notice bibliographique

RevueFrontiers in Pharmacology · 2024
Typeeditorial
Langueen
DomaineMedicine
ThématiqueDrug Transport and Resistance Mechanisms
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésATP-binding cassette transporterDiseaseFunction (biology)PharmacologyComputational biologyTransporterMedicineBiologyBioinformaticsCell biologyInternal medicineBiochemistryGene

Résumé

récupéré en direct d'OpenAlex

ATP-binding cassette (ABC) transporters are ubiquitously expressed multipass membrane proteins that transport ligands across biological membranes, providing multiple critical functions for cellular and organismal physiology. In humans, 48 members of this superfamily are present, of which at least 21 are linked to rare monogenetic disorders, and many are implicated in complex diseases (Moore et al., 2023). These monogenetic disorders result from loss-of-function caused by nonsense or frameshift causing mutations that lead to loss of protein expression, or missense mutations that either cause folding/processing defects or defects in protein function (Dean et al., 2022;Moore et al., 2023).For the cystic fibrosis transmembrane conductance regulator (CFTR/ABCC7), the more than 2100 identified mutants have been classified according to their molecular cell biological and functional phenotypes into six distinct classes: Class I -protein synthesis defect, Class II -maturation defect, Class III -gating defect, Class IV -conductance defect, Class V -reduced quantity, and Class VI -reduced PM stability, with many mutants exhibiting characteristics of more than one class (Veit et al., 2016). CFTR is so far the only ABC transporter targeted by approved modulator drugs that either promote the folding (correctors) or the function (potentiators) of cystic fibrosis (CF)-causing mutants carrying missense mutations. The most efficacious of these modulator drugs, Trikafta, containing the folding corrector tezacaftor, the gating potentiator ivacaftor, and the dual-acting corrector and potentiator elexacaftor, provides unprecedented clinical benefit to patients carrying the most common CF causing mutation F508del and has also been FDA-approved for >170 rare missense mutants (Heijerman et al., 2019;Middleton et al., 2019;Lopes-Pacheco et al., 2021;Veit et al., 2021). The physiological effects of Trikafta therapy are so far incompletely understood, and some rare missense mutants attain no or insufficient correction, thus requiring further modulator development. For CFTR nonsense mutants, predominantly owed to their complex molecular therapeutic phenotypes, modulator therapy is not yet available.It is hoped that similar strategies as for the development of CFTR modulators can be employed to isolate gain-of-function modulators for other ABC transporters. This is exemplified by the responsiveness of a variety of mutant ABC transporters to approved CFTR modulator drugs and 4phenylbutyrate in cell assays (Vauthier et al., 2017). A prerequisite for the wide adoption of such approaches, however, is a better understanding of the structure-function relationship of ABC transporters.In this special Research Topic we collected four studies that use different perspectives on advancing therapeutic strategies for ABC transporters. Three of these studies explore different aspects of modulator therapy for CF.Zajac et al. (Zajac et al., 2023) reported that Trikafta rescues the defective HCO 3 -secretion in F508del homozygous CF airway epithelia to a level corresponding to 80% of that of wild-type (WT) epithelia, which, however did not result in an increase in the airway-surface liquid pH to the WT level. In contrast, treatment with the pro-inflammatory cytokines TNFα and IL-17 dramatically increased the mRNA expression of the Cl -/HCO 3 -exchanger SLC26A4 as well as normalized HCO 3 --secretion and ASL pH, which was further augmented by Trikafta. These results therefore provide further insights into the mechanism that underlies increased CFTR modulator efficacy in the presence of inflammation (Gentzsch et al., 2021;Rehman et al., 2021).Taniguchi et al. isolated novel corrector molecules that are additive to Trikafta for the correction of F508del and rare CFTR missense mutants. The authors used a training set of known CFTR modulators and a machine-learning model to virtually screen over 4 million compounds. This approach identified one compound (FR3) with a distinct mechanism to approved modulators, stabilizing the nucleotidebinding domain 1 of CFTR. FR3 also corrected the defective PM expression of a misfolded mutant ABCB1, thus providing further credence to the idea that modulators can target multiple ABC transporters. FR3 may also show efficacy for ABCA3 mutants with established responsiveness to CFTR correctors (Kinting et al., 2018). Therefore, evaluating the FR3 effect on various misfolded ABC transporters could prove valuable.To study a subset of nonsense mutations, Premchandar et al. developed an affinity purification tandem mass spectrometry pipeline that allows the selective isolation of full-length CFTR molecules to determine the read-through efficacy and to determine the relative incorporation percentages of nearcognate amino acids at the premature termination codons. The authors observed different amino acid misincorporation ratios compared to those found in short reporter constructs, suggesting that the transcript sequence beyond the proximity of PTCs can impact the amino acid incorporation. The consequence of misincorporated amino acids on the CFTR folding and function was investigated and aided in optimizing CFTR modulator combinations. The study, therefore, provides a basis for refined mutation-dependent therapeutic strategies for various CF-causing nonsense mutations.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,033
Score d'incertitude au seuil0,109

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,017
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0030,003
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,002
Communication savante0,0050,005
Science ouverte0,0030,001
Intégrité de la recherche0,0140,015
Charge utile insuffisante (le modèle a refusé de juger)0,0330,023

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,293
Écart entre enseignants0,278 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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