Computational characterization of the glutamate receptor antagonist perampanel and its close analogs: density functional exploration of conformational space and molecular docking study.
J Mol Model
; 25(10): 312, 2019 Sep 11.
Article
em En
| MEDLINE
| ID: mdl-31511986
ABSTRACT
Perampanel approved by FDA in 2012 is a first-in-class antiepileptic drug which inhibits α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor currents. It is markedly more active than many of its close analogs, and the reasons for this activity difference are not quite clear. Recent crystallographic studies allowed the authors to identify the location of its binding site. Unfortunately, the resolution is low, and the detailed description of perampanel binding mode is still in part speculative. Here we provide a detailed DFT-level conformational analysis of perampanel in a vacuum and in the solvents, mimicking the protein environment, followed by quantum theory of atoms in molecules (QTAIM), non-covalent interactions (NCI), and natural bond orbital (NBO) analyses. The findings indicate the electrostatic nature of the intramolecular interactions which contribute to energy differences of the conformations in a vacuum whereas the increase of dielectric constant leads to the energy equalization of conformations. Based on these results, the docking study was performed to investigate possible binding modes of perampanel and its close analogs in AMPA receptors. The influence of the pyridine nitrogen and cyano group position was explained based on the results of conformational analysis and molecular docking. These findings may contribute to the design of novel antiepileptic drugs and the development of novel approaches to treat neurodegenerative diseases and major depressive disorder.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Piridonas
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Antagonistas de Aminoácidos Excitatórios
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Simulação de Acoplamento Molecular
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Teoria da Densidade Funcional
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Conformação Molecular
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
J Mol Model
Assunto da revista:
BIOLOGIA MOLECULAR
Ano de publicação:
2019
Tipo de documento:
Article