Short-wavelength-sensitive 2 (Sws2) visual photopigment models combined with atomistic molecular simulations to predict spectral peaks of absorbance

Journal Article · Wed Oct 21 04:00:00 EDT 2020 · PLoS Computational Biology (Online)

DOI:https://doi.org/10.1371/journal.pcbi.1008212· OSTI ID:2469596

Patel, Dharmeshkumar ^[1]; Barnes, Jonathan E. ^[1]; Davies, Wayne I. L. ^[2]; Stenkamp, Deborah L. ^[1]; Patel, Jagdish Suresh ^[1]

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1. Univ. of Idaho, Moscow, ID (United States)
2. Umea Univ. (Sweden); Univ. of Western Australia, Perth, WA (Australia)

For many species, vision is one of the most important sensory modalities for mediating essential tasks that include navigation, predation and foraging, predator avoidance, and numerous social behaviors. The vertebrate visual process begins when photons of the light interact with rod and cone photoreceptors that are present in the neural retina. Vertebrate visual photopigments are housed within these photoreceptor cells and are sensitive to a wide range of wavelengths that peak within the light spectrum, the latter of which is a function of the type of chromophore used and how it interacts with specific amino acid residues found within the opsin protein sequence. Minor differences in the amino acid sequences of the opsins are known to lead to large differences in the spectral peak of absorbance (i.e. the λ_max value). In our prior studies, we developed a new approach that combined homology modeling and molecular dynamics simulations to gather structural information associated with chromophore conformation, then used it to generate statistical models for the accurate prediction of λ_max values for photopigments derived from Rh1 and Rh2 amino acid sequences. In the present study, we test our novel approach to predict the λ_max of phylogenetically distant Sws2 cone opsins. To build a model that can predict the λ_max using our approach presented in our prior studies, we selected a spectrally-diverse set of 11 teleost Sws2 photopigments for which both amino acid sequence information and experimentally measured λ_max values are known. The final first-order regression model, consisting of three terms associated with chromophore conformation, was sufficient to predict the λ_max of Sws2 photopigments with high accuracy. This study further highlights the breadth of our approach in reliably predicting λ_max values of Sws2 cone photopigments, evolutionary-more distant from template bovine RH1, and provided mechanistic insights into the role of known spectral tuning sites.

• Research Organization: Idaho National Laboratory (INL), Idaho Falls, ID (United States)
• Sponsoring Organization: USDOE Office of Nuclear Energy (NE)
• Grant/Contract Number: AC07-05ID14517
• OSTI ID: 2469596
• Journal Information: PLoS Computational Biology (Online), Journal Name: PLoS Computational Biology (Online) Journal Issue: 10 Vol. 16; ISSN 1553-7358
• Publisher: Public Library of Science
• Country of Publication: United States
• Language: English

Related Subjects

59 BASIC BIOLOGICAL SCIENCES
biochemical simulations
chromophores
molecular dynamics
photoreceptors
protein sequencing
vision
zebrafish