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Photopharmacology of Ion Channels through the Light of the Computational Microscope.

Alba Nin-HillNicolas Pierre Friedrich MuellerCarla MolteniCarme RoviraMercedes Alfonso-Prieto
Published in: International journal of molecular sciences (2021)
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.
Keyphrases
  • molecular dynamics
  • molecular docking
  • high resolution
  • electronic health record
  • binding protein
  • molecular dynamics simulations
  • protein protein
  • amino acid
  • big data
  • machine learning
  • drug delivery
  • deep learning