Bio-QuBIC: Optimized Bacteriorhodopsin Proteins for Photonic and Holographic Memory Storage

Bio-QuBIC：用于光子和全息存储存储的优化细菌视紫红质蛋白

• 批准号: 0129731
• 负责人: Robert Birge
• 金额: $ 40万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-15 至 2004-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0129731&HistoricalAwards=false
• 关键词: Bio; QuBIC; Optimized; Bacteriorhodopsin; Proteins

EIA-0129731Robert R. BirgeSyracuse UniversityTitle: Optimized Bacteriorhodopsin Proteins for Photonic and HolographicMemory StorageThe protein bacteriorhodopsin is being optimized for bioelectronic and photonic applications through site directed mutagenesis, random mutagenesis and directed evolution. The native protein has many characteristics that make it a nearly optimal photonic material, but further optimization is necessary to achieve competitive performance in computer applications. The goal is to generate protein variants that are optimized for holographic associative memories and large scale volumetric memories. The former memory system is based on Fourier-transform holography, and the protein will be optimized for thermal stability, quantum efficiency and holographic efficiency. The large scale volumetric memory is based on a branching reaction out of the main photocycle. The protein is being optimized for this application by increasing thermal stability, branching efficiency and long-term stability of the branched photoproduct. Genetic engineering is the best method for achieving all three goals simultaneously, and directed evolution is being studied as one possible method of rapidly achieving these goals simultaneously. This is a collaborative project involving researchers at the W. M. Keck Center for Molecular Electronics at Syracuse University and molecular biologists at the University of Connecticut.

题目：优化的细菌视紫红质蛋白用于光子和全息记忆存储通过定点诱变、随机诱变和定向进化，细菌视紫红质蛋白正在被优化用于生物电子和光子应用。天然蛋白质具有许多特性，使其成为一种近乎最佳的光子材料，但进一步的优化是必要的，以实现在计算机应用中的竞争性性能。目标是生成针对全息联想记忆和大规模体积记忆进行优化的蛋白质变体。前一种存储系统基于傅里叶变换全息，蛋白质将在热稳定性、量子效率和全息效率方面进行优化。大规模体积记忆是基于主光循环外的分支反应。通过提高支化光产物的热稳定性、支化效率和长期稳定性，对该蛋白进行了优化。基因工程是同时实现这三个目标的最佳方法，而定向进化作为同时快速实现这些目标的一种可能方法正在被研究。这是一个合作项目，涉及锡拉丘兹大学w·m·凯克分子电子学中心的研究人员和康涅狄格大学的分子生物学家。