REFINEMENT OF FOLDED PROTEIN STRUCTURES

折叠蛋白质结构的细化

• 批准号: 6119216
• 负责人: MATTHEW R LEE
• 金额: $ 0.54万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-07-01 至 2000-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6119216
• 关键词: biological products; biomedical resource

In a collaboration with the Dill group at UCSF, I am working on the ab initio protein structure prediction of small proteins (< 100 amino acids) such as CMTI and endothelin. Starting with the low resolution end point structure of our collaborators' folding algorithms, I use molecular dynamics to perform high resolution conformational sampling in search of the native structure, which we predict to be at the global minimum of our force field. Although homology modelling and threading are postulated to be successful in overall fold prediction within the next decade, and despite the great promise shown by folding algorithms, these techniques clearly lack sufficient detail at the molecular level that will allow structure prediction to have significant practical application. Of interest are the b inding pockets and active sites, where small structural differences lead to notable change in protein activity. Given a successful two-step method that accurately determines the macro- and microscopic structures of proteins, the pharmaceutical industry will benefit tremendously in its efforts to produce therapeutic drugs that are needed to modify protein activity. The Computer Graphics Laboratory has proven to be a valuable tool in enabling me to better analyze my data. I frequently use the visualization software package MidasPlus to look at my protein structures. I have also used the hardware to run other applications that display the trajectories of my dynamics simulations. The CGL staff is a helpful resource as well with their programming expertise.

在与加州大学旧金山分校迪尔小组的合作中，我正在研究 小分子蛋白质（< 100 氨基酸）如CMTI和内皮素。 从最低处开始 我们合作者折叠的解析终点结构 算法，我使用分子动力学来执行高分辨率 构象采样在寻找天然结构，我们 预计会在我们力场的全球最小值 虽然 同源建模和线程被假定为成功的， 未来十年的总体折叠预测，尽管 通过折叠算法显示的前景，这些技术显然缺乏 在分子水平上有足够的细节， 预测具有重要的实际应用价值。 感兴趣 B最好的嵌入口袋和活性位点， 差异导致蛋白质活性的显著变化。 给予 成功的两步法，准确地确定宏观和 蛋白质的微观结构，制药业将 在生产治疗药物的努力中受益匪浅， 来改变蛋白质的活性。 计算机图形 实验室已被证明是一个有价值的工具，使我能够更好地 分析我的数据 我经常使用可视化软件包 MidasPlus查看我的蛋白质结构。 我也用过 硬件运行其他应用程序，显示我的轨迹 动力学仿真 CGL员工也是一个有用的资源 他们的编程专业知识。