Photopharmacology of Ion Channels through the Light of the Computational Microscope
Abstract
:1. Introduction
2. Computational Modeling
- (1)
- In the most straightforward case, a search in the Protein Data Bank (PDB) yields an experimental structure of the target protein in complex with the bioactive molecule to be used as a basic module of the photoswitchable ligand. A structure of the target protein bound to a similar molecule (in terms of chemical structure and activity) or a structure of a homologous protein–ligand complex can also be used as a surrogate, as demonstrated by the examples mentioned in the Introduction.
- (2)
- In the absence of an experimental structure of the target protein–bioactive molecule complex, an experimental structure of the apo protein can alternatively be used; ideally, this structure contains the appropriate subunit composition and was captured in the relevant functional state.
- (3)
- When no experimental structure is available, homology modeling can generate a structural model of the target protein based on the experimental structure of a homologous template protein. When selecting the template structure, one should consider the sequence identity between the target and template and, additionally, other features of the template structure, such as the functional state and the bound ligand(s).
- (4)
- Although the (experimental or computational) structure of the protein alone is already informative, carrying out a computational molecular docking of the bioactive molecule can help to further optimize the photoswitchable ligand design. In particular, the predicted binding mode can be used to identify the optimal position to introduce the photochromic group and/or estimate the length of the linker between the different modules of the PCL or PTL, as well as pinpoint potential residues for Cys screening.
- (5)
- The photoswitchable ligand (PCL or PTL) design follows the modular approach depicted in Figure 1b. As mentioned in steps (1)–(4), structural information on the binding mode of the bioactive module to the target protein can be used to guide such a design.
- (6)
- In the case of PTLs, their design additionally includes an inspection of the structure of the target protein, either experimental or computational, in order to identify putative tethering positions, i.e., residues near the ligand binding site amenable for cysteine mutagenesis screening.
- (7)
- Upon design of the photoswitchable ligand, synthesis and experimental testing can already be performed; the latter includes measuring the modulatory effect of the ligand under different light conditions, as well as site-directed mutagenesis (either Cys mutations for PTL covalent attachment or other mutations to confirm the binding site location and PCL/PTL ligand binding mode).
- (8)
- The observed light-dependent activity (or lack thereof), as well as the effect of mutations, can be rationalized a posteriori by performing a molecular docking of the PCL or virtual Cys mutation combined with covalent docking for the PTL. The resulting model of the target protein–photoswitch complex can be inspected to design additional site-directed mutations to validate the predicted PCL/PTL predicted binding mode. Alternatively, molecular docking can be used a priori (i.e., before experimental testing) to select the best candidate among several possible photoswitchable ligand designs (for subsequent experimental testing), as well as to explore alternative Cys tethering sites.
- (9)
- Though the (static) computational models described so far are already useful to understand the molecular basis of light-controlled ion channel modulation, they can additionally be refined by molecular dynamics. Such simulations, alone or in combination with enhanced sampling and free energy techniques, can provide further dynamical and energetic insights into the photoswitch effect, as explained earlier in this section.
- (10)
- This integrative computational-experimental approach offers a comprehensive understanding of the PCL/PTL effect on ion channel function, including but not limited to the information listed in the last step of the proposed workflow (see Figure 3).
3. Computational Modeling of Photoswitchable Ligands Targeting Voltage-Gated Ion Channels
3.1. Photoswitchable Pore Blockers
3.2. Photoswitchable Modulators
4. Computational Modeling of Photoswitchable Ligands Targeting Ligand-Gated Ion Channels
4.1. Nicotinic Acetylcholine Receptors
4.2. 5-HT3 Receptors
4.3. GABAA Receptors
4.4. Glycine Receptors
4.5. Ionotropic Glutamate Receptors
4.6. P2X Receptors
5. Conclusions and Perspectives
Supplementary Materials
Funding
Acknowledgments
Conflicts of Interest
References and Notes
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Nin-Hill, A.; Mueller, N.P.F.; Molteni, C.; Rovira, C.; Alfonso-Prieto, M. Photopharmacology of Ion Channels through the Light of the Computational Microscope. Int. J. Mol. Sci. 2021, 22, 12072. https://doi.org/10.3390/ijms222112072
Nin-Hill A, Mueller NPF, Molteni C, Rovira C, Alfonso-Prieto M. Photopharmacology of Ion Channels through the Light of the Computational Microscope. International Journal of Molecular Sciences. 2021; 22(21):12072. https://doi.org/10.3390/ijms222112072
Chicago/Turabian StyleNin-Hill, Alba, Nicolas Pierre Friedrich Mueller, Carla Molteni, Carme Rovira, and Mercedes Alfonso-Prieto. 2021. "Photopharmacology of Ion Channels through the Light of the Computational Microscope" International Journal of Molecular Sciences 22, no. 21: 12072. https://doi.org/10.3390/ijms222112072
APA StyleNin-Hill, A., Mueller, N. P. F., Molteni, C., Rovira, C., & Alfonso-Prieto, M. (2021). Photopharmacology of Ion Channels through the Light of the Computational Microscope. International Journal of Molecular Sciences, 22(21), 12072. https://doi.org/10.3390/ijms222112072