Institute for Modeling Collaboration and Innovation (IMCI), University of Idaho, Moscow, ID, United States of America.
Department of Physics, University of Idaho, Moscow, ID, United States of America.
PLoS Comput Biol. 2020 Oct 21;16(10):e1008212. doi: 10.1371/journal.pcbi.1008212. eCollection 2020 Oct.
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.
对于许多物种来说，视觉是介导包括导航、捕食和觅食、捕食者回避以及许多社交行为等基本任务的最重要感觉模态之一。脊椎动物的视觉过程始于光子与存在于神经视网膜中的视杆和视锥感光细胞相互作用。脊椎动物的视觉光色素位于这些感光细胞内，对光谱内的广泛波长敏感，后者是所使用的发色团的类型以及它与视蛋白序列中特定氨基酸残基如何相互作用的函数。光色素的氨基酸序列的微小差异已知会导致吸收光谱峰（即 λmax 值）的差异很大。在我们之前的研究中，我们开发了一种新方法，该方法结合同源建模和分子动力学模拟来收集与发色团构象相关的结构信息，然后使用它来生成统计模型，以准确预测源自 Rh1 和 Rh2 氨基酸序列的光色素的 λmax 值。在本研究中，我们测试了我们的新方法来预测系统发育上较远的 Sws2 圆锥感光细胞的 λmax。为了建立一个可以使用我们之前研究中提出的方法预测 λmax 的模型，我们选择了一组光谱多样的 11 种硬骨鱼 Sws2 视蛋白，这些视蛋白具有已知的氨基酸序列信息和实验测量的 λmax 值。由与发色团构象相关的三个术语组成的最终一阶回归模型足以高度准确地预测 Sws2 视蛋白的 λmax。这项研究进一步强调了我们的方法在可靠预测 Sws2 圆锥感光细胞的 λmax 值方面的广泛适用性，与模板牛 RH1 的进化距离更远，并提供了对已知光谱调谐位点作用的机制见解。
