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Channel Rhodopsins

Channel Rhodopsins

Most organisms use photoreceptors to sense and respond to light. Examples of photoreceptors include bacteriorhodopsins and bacteriophytochromes in some bacteria, phytochromes in plants, and rhodopsins in the photoreceptor cells of the vertebral retina. The light-sensitive property of these receptors is because of the bound chromophores, such as bilin in the phytochromes and retinal in the rhodopsins.
Rhodopsins belong to the family of cell surface proteins called G-protein coupled receptors,...

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Related Experiment Video

Updated: Jun 5, 2025

A Rhodopsin Transport Assay by High-Content Imaging Analysis

A Rhodopsin Transport Assay by High-Content Imaging Analysis

Published on: January 16, 2019

Investigating the Origin of Automatic Rhodopsin Modeling Outliers Using the Microbial Gloeobacter Rhodopsin as

Darío Barreiro-Lage¹, Vincent Ledentu¹, Jacopo D'Ascenzi^2,3

¹Aix Marseille Univ, CNRS, ICR, 13013 Marseille, France.

The Journal of Physical Chemistry. B

|December 10, 2024

Summary

This summary is machine-generated.

The automatic rhodopsin modeling approach was improved to accurately predict rhodopsin absorption energies. Modifications, including histidine protonation and advanced computational methods, significantly reduced prediction errors for Gloeobacter rhodopsin.

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Area of Science:

Computational chemistry
Biophysics
Spectroscopy

Background:

The automatic rhodopsin modeling (ARM) approach uses hybrid quantum mechanics/molecular mechanics (QM/MM) for rhodopsin modeling.
ARM accurately predicts photophysical properties but has limitations with outlier cases.

Purpose of the Study:

To analyze the origin of outliers in ARM predictions for Gloeobacter rhodopsin (GR) wild-type and mutants.
To improve the accuracy of computational modeling for rhodopsin absorption energies.

Main Methods:

Applied ARM to Gloeobacter rhodopsin (GR) and analyzed deviations from experimental data.
Investigated the impact of histidine (H87) pKa uncertainty on model accuracy.
Tested modifications to ARM: improved pKa prediction, electrostatic potential attenuation, state-specific CAS, and MRSF-TDDFT.

Main Results:

Standard ARM yielded a root-mean-square deviation (RMSD) of 0.42 eV for GR excitation energies.
Modified protocols were tested, with the best performance achieved by combining H87 protonation with MRSF/CAMH-B3LYP.
The optimized approach reduced the RMSD to 0.2 eV.

Conclusions:

The pKa of histidine at position 87 is critical for accurate GR modeling.
Advanced computational methods like MRSF-TDDFT significantly enhance the predictive power of ARM.
The refined ARM protocol offers improved accuracy for rhodopsin photophysical property predictions.