Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations

Patel, Jagdish Suresh; Brown, Celeste J.; Ytreberg, F. Marty; Stenkamp, Deborah L.

doi:10.1371/journal.pcbi.1005974

Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations

Journal Article · Wed Jan 24 04:00:00 EST 2018 · PLoS Computational Biology (Online)

DOI:https://doi.org/10.1371/journal.pcbi.1005974· OSTI ID:2469597

^[1]; Brown, Celeste J. ^[1]; Ytreberg, F. Marty ^[1]; ^[1]

Univ. of Idaho, Moscow, ID (United States)

Vision is the dominant sensory modality in many organisms for foraging, predator avoidance, and social behaviors including mate selection. Vertebrate visual perception is initiated when light strikes rod and cone photoreceptors within the neural retina of the eye. Sensitivity to individual colors, i.e., peak spectral sensitivities (λ_max) of visual pigments, are a function of the type of chromophore and the amino acid sequence of the associated opsin protein in the photoreceptors. Large differences in peak spectral sensitivities can result from minor differences in amino acid sequence of cone opsins. To determine how minor sequence differences could result in large spectral shifts we selected a spectrally-diverse group of 14 teleost Rh2 cone opsins for which sequences and λ_max are experimentally known. Classical molecular dynamics simulations were carried out after embedding chromophore-associated homology structures within explicit bilayers and water. These simulations revealed structural features of visual pigments, particularly within the chromophore, that contributed to diverged spectral sensitivities. Statistical tests performed on all the observed structural parameters associated with the chromophore revealed that a two-term, first-order regression model was sufficient to accurately predict λ_max over a range of 452–528 nm. The approach was accurate, efficient and simple in that site-by-site molecular modifications or complex quantum mechanics models were not required to predict λ_max. These studies identify structural features associated with the chromophore that may explain diverged spectral sensitivities, and provide a platform for future, functionally predictive opsin modeling.

View Accepted Manuscript (DOE)

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:: 2469597

Journal Information:: PLoS Computational Biology (Online), Journal Name: PLoS Computational Biology (Online) Journal Issue: 1 Vol. 14; ISSN 1553-7358

Publisher:: Public Library of ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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