Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/11000/35369

Targeting thermoTRP ion channels: in silico preclinical approaches and opportunities


no-thumbnailVer/Abrir:

 4-ThermoTRP_EOTT_2020.pdf



5,5 MB
Adobe PDF
Compartir:

Este recurso está restringido

Título :
Targeting thermoTRP ion channels: in silico preclinical approaches and opportunities
Autor :
Fernández Ballester, Gregorio
Fernández Carvajal, Asia
Ferrer-Montiel, Antonio  
Editor :
Taylor and Francis Group
Departamento:
Departamentos de la UMH::Bioquímica y Biología Molecular
Fecha de publicación:
2020-09-24
URI :
https://hdl.handle.net/11000/35369
Resumen :
Introduction: A myriad of cellular pathophysiological responses are mediated by polymodal ion channels that respond to chemical and physical stimuli such as thermoTRP channels. Intriguingly, these channels are pivotal therapeutic targets with limited clinical pharmacology. In silico methods offer an unprecedented opportunity for discovering new lead compounds targeting thermoTRP channels with improved pharmacological activity and therapeutic index. Areas covered: This article reviews the progress on thermoTRP channel pharmacology because of (i) advances in solving their atomic structure using cryo-electron microscopy and, (ii) progress on computational techniques including homology modeling, molecular docking, virtual screening, molecular dynamics, ADME/Tox and artificial intelligence. Together, they have increased the number of lead compounds with clinical potential to treat a variety of pathologies. We used original and review articles from Pubmed (1997–2020), as well as the clinicaltrials.gov database, containing the terms thermoTRP, artificial intelligence, docking, and molecular dynamics. Expert opinion: The atomic structure of thermoTRP channels along with computational methods constitute a realistic first line strategy for designing drug candidates with improved pharmacology and clinical translation. In silico approaches can also help predict potential side-effects that can limit clinical development of drug candidates. Together, they should provide drug candidates with upgraded therapeutic properties.
Palabras clave/Materias:
ADME
artificial intelligence
docking
ion channel
molecular dynamics
thermoTRP channels
virtual screening
Área de conocimiento :
CDU: Ciencias puras y naturales: Biología
Tipo de documento :
info:eu-repo/semantics/article
Derechos de acceso:
info:eu-repo/semantics/closedAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.1080/14728222.2020.1820987
Aparece en las colecciones:
Artículos Biología Aplicada



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.