Application of LEDA algorithm for the recognition of P-glycoprotein and Carbonic Anhydrase hybrid inhibitors and evaluation of their plasma stability by HPLC-MS/MS analysis.


Journal

Journal of pharmaceutical and biomedical analysis
ISSN: 1873-264X
Titre abrégé: J Pharm Biomed Anal
Pays: England
ID NLM: 8309336

Informations de publication

Date de publication:
20 Sep 2022
Historique:
received: 28 03 2022
revised: 06 06 2022
accepted: 08 06 2022
pubmed: 27 6 2022
medline: 17 8 2022
entrez: 26 6 2022
Statut: ppublish

Résumé

Design and synthesis of new candidate drugs produces a large number of compounds that must be qualified and tested to evaluate their characteristics and potential applications. Therefore, many studies will be scheduled and, consequently, it will be necessary to arrange specific, reliable, fast and relatively cheap analytic methods to support this research. The manuscript proposes a new approach in the HPLC-MS/MS analysis by using a sole chromatographic set up, tuned to minimize the run time, without requiring high efficiency or resolution between the analytes. The chromatographic column was used only to avoid or limit the interference of sample matrix towards the analyte ionization process (matrix-effects). Then, the MS/MS properties were explored to solve the signal assignment, by performing a series of energy resolved experiments to optimize the parameters and applying an interesting post-processing data elaboration tool (LEDA). The reliability of the new approach was evaluated in a chemical stability study in PBS and human plasma samples of a series of isomeric compounds P-glycoprotein/Carbonic Anhydrase (P-gp/CA) hybrid inhibitors. The obtained results demonstrated the effectiveness (reliability 97%-100%) of the LEDA algorithm to recognize and to separate the possible isomers present in the samples. The obtained matrix-effects values (ME 96%-106%) established that the chromatographic set up (short column and fast elution gradient) was proper to avoid the matrix interferences, while recovery values (RE 88%-108%) indicate a suitable sample preparation, despite only a protein precipitation was carried out. The quantitative performances of proposed HPLC-MS/MS methods showed an accuracy ranging between 92% and 108% and a precision lower than 13% that allows to be confident on the determination of new P-gp/CA hybrid inhibitors in the degradation study. Therefore, the general procedure proposed was found adequate to study a series of isomeric compounds without their chromatographic separation but only by applying and developing the MS/MS features.

Identifiants

pubmed: 35753165
pii: S0731-7085(22)00308-9
doi: 10.1016/j.jpba.2022.114887
pii:
doi:

Substances chimiques

ATP Binding Cassette Transporter, Subfamily B 0
ATP Binding Cassette Transporter, Subfamily B, Member 1 0
Carbonic Anhydrase Inhibitors 0
Carbonic Anhydrases EC 4.2.1.1

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

114887

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Auteurs

Marco Pallecchi (M)

NEUROFARBA Department, Department of Neuroscience, Psychology, Drug Research and Child Health-Neurofarba-Pharmaceutical and Nutraceutical Sciences Section, University of Florence, Via U. Schiff 6, 50019 Sesto Fiorentino, Italy.

Marta Menicatti (M)

NEUROFARBA Department, Department of Neuroscience, Psychology, Drug Research and Child Health-Neurofarba-Pharmaceutical and Nutraceutical Sciences Section, University of Florence, Via U. Schiff 6, 50019 Sesto Fiorentino, Italy.

Laura Braconi (L)

NEUROFARBA Department, Department of Neuroscience, Psychology, Drug Research and Child Health-Neurofarba-Pharmaceutical and Nutraceutical Sciences Section, University of Florence, Via U. Schiff 6, 50019 Sesto Fiorentino, Italy.

Claudiu T Supuran (CT)

NEUROFARBA Department, Department of Neuroscience, Psychology, Drug Research and Child Health-Neurofarba-Pharmaceutical and Nutraceutical Sciences Section, University of Florence, Via U. Schiff 6, 50019 Sesto Fiorentino, Italy.

Silvia Dei (S)

NEUROFARBA Department, Department of Neuroscience, Psychology, Drug Research and Child Health-Neurofarba-Pharmaceutical and Nutraceutical Sciences Section, University of Florence, Via U. Schiff 6, 50019 Sesto Fiorentino, Italy.

Elisabetta Teodori (E)

NEUROFARBA Department, Department of Neuroscience, Psychology, Drug Research and Child Health-Neurofarba-Pharmaceutical and Nutraceutical Sciences Section, University of Florence, Via U. Schiff 6, 50019 Sesto Fiorentino, Italy.

Gianluca Bartolucci (G)

NEUROFARBA Department, Department of Neuroscience, Psychology, Drug Research and Child Health-Neurofarba-Pharmaceutical and Nutraceutical Sciences Section, University of Florence, Via U. Schiff 6, 50019 Sesto Fiorentino, Italy. Electronic address: gianluca.bartolucci@unifi.it.

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Classifications MeSH