Please use this identifier to cite or link to this item:
https://hdl.handle.net/11000/35369
Targeting thermoTRP ion channels: in silico
preclinical approaches and opportunities
View/Open: 4-ThermoTRP_EOTT_2020.pdf
5,5 MB
Adobe PDF
Share:
This resource is restricted
Title: Targeting thermoTRP ion channels: in silico
preclinical approaches and opportunities |
Authors: Fernández Ballester, Gregorio Fernández Carvajal, Asia Ferrer-Montiel, Antonio |
Editor: Taylor and Francis Group |
Department: Departamentos de la UMH::Bioquímica y Biología Molecular |
Issue Date: 2020-09-24 |
URI: https://hdl.handle.net/11000/35369 |
Abstract:
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.
|
Keywords/Subjects: ADME artificial intelligence docking ion channel molecular dynamics thermoTRP channels virtual screening |
Knowledge area: CDU: Ciencias puras y naturales: Biología |
Type of document: info:eu-repo/semantics/article |
Access rights: info:eu-repo/semantics/closedAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
DOI: https://doi.org/10.1080/14728222.2020.1820987 |
Appears in Collections: Artículos Biología Aplicada
|
???jsp.display-item.text9???