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: 10813692
• 负责人: Jagdish Suresh Patel
• 金额: $ 15.66万
• 依托单位: UNIVERSITY OF IDAHO
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-03-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10813692
• 关键词: 3-Dimensional; Amino Acid Sequence; Amino Acids; Chemicals; Color Visions; Complex; Data; Data Set; Development; Disease; Electronics; Engineering; Foundations; Genome; Goals; Homology Modeling; Human; Impairment; Lead; Machine Learning; Modeling; Molecular; Molecular Conformation; Mutation; Opsin; Pathologic; Phototransduction; Pigments; Population; Process; Property; Proteins; Quantum Mechanics; Research; Retinal Cone; Retinal Pigments; Running; Series; Statistical Models; Structure; Structure-Activity Relationship; Testing; Therapeutic; Vertebrate Photoreceptors; Vision; Visual; chromophore; computational pipelines; disease-causing mutation; improved; machine learning pipeline; molecular dynamics; molecular mechanics; molecular modeling; novel; novel strategies; optogenetics; phenome; predictive modeling; simulation; targeted treatment

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.

人类视觉色素中的氨基酸突变会损害色觉或导致退行性失明等疾病。人类视觉要求这些由发色团和相关视蛋白组成的色素在不同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。峰值光谱灵敏度由发色团类型和视蛋白的氨基酸序列决定。了解视蛋白的单一突变如何导致视觉功能异常和疾病将有助于分子水平治疗策略的开发。目前还没有这样的理解。拟议研究的总体目标是开发新的分子水平治疗策略，通过使用最先进的建模方法解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的基础上，开发和测试自动化计算管道，以估计 Rh1 杆视蛋白的峰值光谱灵敏度，并用它来阐明疾病相关突变的机制。在目标 1 中，我们将构建一个基于机器学习的管道，它将利用同源建模和分子动力学模拟，根据视蛋白氨基酸序列数据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偏移的分子机制并改进管道。在目标 3 中，我们将使用该流程来确定异常视觉功能的分子机制。拟议的研究可能会对人类视觉领域产生重大影响，因为它将提供一种视觉色素的预测建模方法，而这种方法几十年来一直难以捉摸。这种对视色素分子功能的从基因组到表型的新理解将为设计适合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。