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

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...

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Autores principales: Patel, Jagdish Suresh, Brown, Celeste J., Ytreberg, F. Marty, Stenkamp, Deborah L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798944/
https://www.ncbi.nlm.nih.gov/pubmed/29364888
http://dx.doi.org/10.1371/journal.pcbi.1005974
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author Patel, Jagdish Suresh
Brown, Celeste J.
Ytreberg, F. Marty
Stenkamp, Deborah L.
author_facet Patel, Jagdish Suresh
Brown, Celeste J.
Ytreberg, F. Marty
Stenkamp, Deborah L.
author_sort Patel, Jagdish Suresh
collection PubMed
description 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.
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spelling pubmed-57989442018-02-23 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. PLoS Comput Biol Research Article 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. Public Library of Science 2018-01-24 /pmc/articles/PMC5798944/ /pubmed/29364888 http://dx.doi.org/10.1371/journal.pcbi.1005974 Text en © 2018 Patel et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Patel, Jagdish Suresh
Brown, Celeste J.
Ytreberg, F. Marty
Stenkamp, Deborah L.
Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations
title Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations
title_full Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations
title_fullStr Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations
title_full_unstemmed Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations
title_short Predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations
title_sort predicting peak spectral sensitivities of vertebrate cone visual pigments using atomistic molecular simulations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798944/
https://www.ncbi.nlm.nih.gov/pubmed/29364888
http://dx.doi.org/10.1371/journal.pcbi.1005974
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