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

journal contribution
posted on 2021-01-19, 23:40 authored by D Patel, JE Barnes, WIL Davies, DL Stenkamp, JS Patel
Copyright: © 2020 Patel et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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 λmax 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 λmax values for photopigments derived from Rh1 and Rh2 amino acid sequences. In the present study, we test our novel approach to predict the λmax of phylogenetically distant Sws2 cone opsins. To build a model that can predict the λmax 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 λmax values are known. The final first-order regression model, consisting of three terms associated with chromophore conformation, was sufficient to predict the λmax of Sws2 photopigments with high accuracy. This study further highlights the breadth of our approach in reliably predicting λmax values of Sws2 cone photopigments, evolutionary-more distant from template bovine RH1, and provided mechanistic insights into the role of known spectral tuning sites.


This research was supported by the Center for Modeling Complex Interactions (CMCI) sponsored by the NIGMS under award number NIH P20 GM104420, through a Pilot Grant to JSP that supported JSP, DP, and JB. JSP and JB were also supported in part by National Science Foundation EPSCoR Track-II grant under award number OIA1736253, and DLS was also supported in part by NIH R01 EY012146 and NSF DEB 1638567. Computer resources were provided by the Institute for Bioinformatics and Evolutionary Studies Computational Resources Core sponsored by the National Institutes of Health (NIH P30 GM103324). This research also made use of the computational resources provided by the highperformance computing center at Idaho National Laboratory, which is supported by the Office of Nuclear Energy of the U.S. DOE and the Nuclear Science User Facilities under Contract No. DE-AC07-05ID14517. WILD was supported by the Australian Research Council (ARC) in the form of a Future Fellowship (FT110100176) and a Discovery Project grant (DP140102117), and is currently supported by a JC Kempe Memorial Scholarship from the Kempe Foundation, Sweden. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


Publication Date



PLoS Computational Biology





Article Number

ARTN e1008212







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