Sequence-structure-function relationships in human visual photopigments

人类视觉感光色素中的序列-结构-功能关系

• 批准号: 10811882
• 负责人: Jagdish Suresh Patel
• 金额: $ 3.41万
• 依托单位: UNIVERSITY OF IDAHO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-17 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10811882
• 关键词: Sequence; structure; function; relationships; human

Amino acid mutations in human visual pigments can impair color vision or lead to diseases such as degenerative blinding condition. Human vision requires that these pigments, consisting of a chromophore and associated opsin protein, have distinct peak spectral sensitivities in separate rod and cone photoreceptor populations. Peak spectral sensitivity is determined by the chromophore type and the amino acid sequence of the opsin. Understanding how a single mutation in the opsin protein can lead to anomalous visual function and disease would assist the development of molecular-level therapeutic strategies. Such an understanding is currently not available. The proposed research has an overarching goal of developing novel molecular-level therapeutic strategies to treat human vision deficiencies by unraveling the mysteries of the phototransduction cycle using state-of-the-art modeling approaches. The goal of the proposed research is to build on our molecular modeling framework to develop and test an automated computational pipeline to estimate peak spectral sensitivity for Rh1 rod opsins and use it to elucidate mechanisms for disease-associated mutations. In Aim 1, we will build a machine-learning-based pipeline, which will utilize homology modeling and molecular dynamics simulation, for accurately predicting peak spectral sensitivity from opsin amino acid sequence data. Aim 2 will employ mixed quantum mechanics / molecular mechanics simulations to elucidate molecular mechanisms of spectral shift and improve the pipeline. In Aim 3, we will use the pipeline to determine molecular mechanisms for anomalous visual functions. The proposed research has the potential for high impact in the field of human vision because it will provide a predictive modeling approach for visual pigments, that has remained elusive for decades. This new genome-to-phenome understanding of the molecular function of visual pigments will pave the way for novel strategies to engineer pigments suitable for optogenetics, or to develop targeted therapeutic strategies.

人类视色素中的氨基酸突变会损害色觉或导致疾病，如退行性致盲。人类视觉需要这些由发色团和相关的视蛋白组成的色素，在单独的视杆和视锥光感受器群体中具有不同的峰值光谱灵敏度。峰值光谱灵敏度由视蛋白的发色团类型和氨基酸序列决定。了解视蛋白中的单一突变如何导致异常的视觉功能和疾病将有助于分子水平治疗策略的发展。目前还没有这样的理解。拟议的研究的总体目标是开发新的分子水平的治疗策略，通过使用最先进的建模方法揭开光转导周期的奥秘来治疗人类视力缺陷。拟议研究的目标是建立在我们的分子建模框架上，开发和测试自动计算管道，以估计Rh 1视杆视蛋白的峰值光谱灵敏度，并利用它来阐明疾病相关突变的机制。在目标1中，我们将建立一个基于机器学习的管道，该管道将利用同源建模和分子动力学模拟，用于从视蛋白氨基酸序列数据中准确预测峰值光谱灵敏度。目标2将采用混合量子力学/分子力学模拟来阐明光谱移动的分子机制并改进管道。在目标3中，我们将使用管道来确定异常视觉功能的分子机制。这项研究有可能在人类视觉领域产生巨大影响，因为它将为视觉色素提供一种预测建模方法，这种方法几十年来一直难以实现。这种对视色素分子功能的新的基因组到表型组的理解将为设计适用于光遗传学的色素或开发有针对性的治疗策略的新策略铺平道路。