An In Silico Investigation of the Molecular Interactions between Volatile Anesthetics and Actin.

actins anesthesia cytoskeleton molecular docking simulation tubulin

Journal

Pharmaceuticals (Basel, Switzerland)
ISSN: 1424-8247
Titre abrégé: Pharmaceuticals (Basel)
Pays: Switzerland
ID NLM: 101238453

Informations de publication

Date de publication:
26 Dec 2023
Historique:
received: 25 11 2023
revised: 15 12 2023
accepted: 21 12 2023
medline: 23 1 2024
pubmed: 23 1 2024
entrez: 23 1 2024
Statut: epublish

Résumé

Volatile anesthetics (VAs) are medicinal chemistry compounds commonly used to enable surgical procedures for patients who undergo painful treatments and can be partially or fully sedated, remaining in an unconscious state during the operation. The specific molecular mechanism of anesthesia is still an open issue, but scientific evidence supports the hypothesis of the involvement of both putative hydrophobic cavities in membrane receptors as binding pockets and interactions between anesthetics and cytoplasmic proteins. Previous studies demonstrated the binding of VAs to tubulin. Since actin is the other major component of the cytoskeleton, this study involves an investigation of its interactions with four major anesthetics: halothane, isoflurane, sevoflurane, and desflurane. Molecular docking was implemented using the Molecular Operating Environment (MOE) software (version 2022.02) and applied to a G-actin monomer, extrapolating the relative binding affinities and root-mean-square deviation (RMSD) values. A comparison with the F-actin was also made to assess if the generally accepted idea about the enhanced F-to-G-actin transformation during anesthesia is warranted. Overall, our results confirm the solvent-like behavior of anesthetics, as evidenced by Van der Waals interactions as well as the relevant hydrogen bonds formed in the case of isoflurane and sevoflurane. Also, a comparison of the interactions of anesthetics with tubulin was made. Finally, the short- and long-term effects of anesthetics are discussed for their possible impact on the occurrence of mental disorders.

Identifiants

pubmed: 38256871
pii: ph17010037
doi: 10.3390/ph17010037
pii:
doi:

Types de publication

Journal Article

Langues

eng

Auteurs

Barbara Truglia (B)

DIMEAS, Politecnico di Torino, 10129 Turin, Italy.

Nicola Carbone (N)

DIMEAS, Politecnico di Torino, 10129 Turin, Italy.

Ibrahim Ghadre (I)

DIMEAS, Politecnico di Torino, 10129 Turin, Italy.

Sara Vallero (S)

DIMEAS, Politecnico di Torino, 10129 Turin, Italy.

Marinella Zito (M)

DIMEAS, Politecnico di Torino, 10129 Turin, Italy.

Eric Adriano Zizzi (EA)

DIMEAS, Politecnico di Torino, 10129 Turin, Italy.

Marco Agostino Deriu (MA)

DIMEAS, Politecnico di Torino, 10129 Turin, Italy.

J A Tuszynski (JA)

DIMEAS, Politecnico di Torino, 10129 Turin, Italy.
Department of Data Science and Engineering, The Silesian University of Technology, 44-100 Gliwice, Poland.
Department of Physics, University of Alberta, Edmonton, AB T6G 2E1, Canada.

Classifications MeSH