通过使用多层次方法识别蛋白质上的连接体结合点
Meir Glick1, Daniel D Robinson, Guy H Grant
1Department of Chemistry, Central Chemistry Laboratory, University of Oxford, South Parks Road, Oxford, OX1 3QH, UK.
Journal of the American Chemical Society
|March 7, 2002
概括
这项研究引入了一种自动化,高效的方法来识别蛋白质连接体结合位,这对于药物发现至关重要. 这种新的方法减少了计算力度,加速了潜在药物点的识别.
科学领域:
- 计算化学是一种计算化学.
- 结构生物学是结构生物学.
- 药物发现 药物发现
背景情况:
- 识别蛋白质上的连接体结合点对于药物发现至关重要.
- 现有的方法缺乏可靠性和一般应用的计算可行性.
研究的目的:
- 提出一种自动化和高效的方法来确定蛋白质连接体结合点.
- 允许在没有事先知识的情况下识别绑定站点.
主要方法:
- 使用一个多尺度概念,通过k-means集群生成模型的层次结构.
- 代表具有越来越多特征点的潜在连接体.
- 采用非结合性能量功能来评分分子相互作用和修剪潜在位置.
主要成果:
- 已成功应用于七个蛋白质 - 配体复合体.
- 显著减少了计算力度.
- 该算法有效地识别了绑定站点.
结论:
- 开发的方法提供了一个计算上可行的和通用的方法,用于绑定站点识别.
- 这种技术对药物发现和结构基因组学有重大影响.
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