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@ARTICLE{NinHill:902331,
author = {Nin-Hill, Alba and Mueller, Nicolas Pierre Friedrich and
Molteni, Carla and Rovira, Carme and Alfonso-Prieto,
Mercedes},
title = {{P}hotopharmacology of {I}on {C}hannels through the {L}ight
of the {C}omputational {M}icroscope},
journal = {International journal of molecular sciences},
volume = {22},
number = {21},
issn = {1422-0067},
address = {Basel},
publisher = {Molecular Diversity Preservation International},
reportid = {FZJ-2021-04185},
pages = {12072 -},
year = {2021},
abstract = {The optical control and investigation of neuronal activity
can be achieved and carried out with photoswitchable
ligands. Such compounds are designed in a modular fashion,
combining a known ligand of the target protein and a
photochromic group, as well as an additional electrophilic
group for tethered ligands. Such a design strategy can be
optimized by including structural data. In addition to
experimental structures, computational methods (such as
homology modeling, molecular docking, molecular dynamics and
enhanced sampling techniques) can provide structural
insights to guide photoswitch design and to understand the
observed light-regulated effects. This review discusses the
application of such structure-based computational methods to
photoswitchable ligands targeting voltage- and ligand-gated
ion channels. Structural mapping may help identify residues
near the ligand binding pocket amenable for mutagenesis and
covalent attachment. Modeling of the target protein in a
complex with the photoswitchable ligand can shed light on
the different activities of the two photoswitch isomers and
the effect of site-directed mutations on photoswitch
binding, as well as ion channel subtype selectivity. The
examples presented here show how the integration of
computational modeling with experimental data can greatly
facilitate photoswitchable ligand design and optimization.
Recent advances in structural biology, both experimental and
computational, are expected to further strengthen this
rational photopharmacology approach.},
cin = {IAS-5 / INM-9},
ddc = {540},
cid = {I:(DE-Juel1)IAS-5-20120330 / I:(DE-Juel1)INM-9-20140121},
pnm = {5241 - Molecular Information Processing in Cellular Systems
(POF4-524) / 5251 - Multilevel Brain Organization and
Variability (POF4-525) / 5252 - Brain Dysfunction and
Plasticity (POF4-525) / DFG project 291198853 - FOR 2518:
Funktionale Dynamik von Ionenkanälen und Transportern -
DynIon -},
pid = {G:(DE-HGF)POF4-5241 / G:(DE-HGF)POF4-5251 /
G:(DE-HGF)POF4-5252 / G:(GEPRIS)291198853},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:34769504},
UT = {WOS:000720497000001},
doi = {10.3390/ijms222112072},
url = {https://juser.fz-juelich.de/record/902331},
}