Artículo
Structure-Based Virtual Screening Identifies Novobiocin, Montelukast, and Cinnarizine as TRPV1 Modulators with Anticonvulsant Activity In Vivo
Llanos, Manuel
; Enrique, Nicolás Jorge
; Sbaraglini, Maria Laura
; Garofalo, Federico Mariano
; Talevi, Alan
; Gavernet, Luciana
; Martín, Pedro
Fecha de publicación:
06/2022
Editorial:
American Chemical Society
Revista:
Journal of Chemical Information and Modeling
ISSN:
1549-9596
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
The transient receptor potential vanilloid 1 (TRPV1) receptor is a nonselective cation channel, known to be involved in the regulation of many important physiological and pathological processes. In the last few years, it has been proposed as a promising target to develop novel anticonvulsant compounds. However, thermoregulatory effects associated with the channel inhibition have hampered the path for TRPV1 antagonists to become marketed drugs. In this regard, we conducted a structure-based virtual screening campaign to find potential TRPV1 modulators among approved drugs, which are known to be safe and thermally neutral. To this end, different docking models were developed and validated by assessing their pose and score prediction powers. Novobiocin, montelukast, and cinnarizine were selected from the screening as promising candidates for experimental testing and all of them exhibited nanomolar inhibitory activity. Moreover, the in vivo profiles showed promising results in at least one of the three models of seizures tested.
Palabras clave:
TRPV1
,
ANTIEPILEPTIC DRUGS
,
VIRTUAL CAMPAIN
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Articulos(IIFP)
Articulos de INST. DE ESTUDIOS INMUNOLOGICOS Y FISIOPATOLOGICOS
Articulos de INST. DE ESTUDIOS INMUNOLOGICOS Y FISIOPATOLOGICOS
Citación
Llanos, Manuel; Enrique, Nicolás Jorge; Sbaraglini, Maria Laura; Garofalo, Federico Mariano; Talevi, Alan; et al.; Structure-Based Virtual Screening Identifies Novobiocin, Montelukast, and Cinnarizine as TRPV1 Modulators with Anticonvulsant Activity In Vivo; American Chemical Society; Journal of Chemical Information and Modeling; 62; 12; 6-2022; 3008-3022
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