Data mining crystallization databases: Knowledge-based approaches to optimize protein crystal screens
Data mining crystallization databases: Knowledge-based approaches to optimize protein crystal screens
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DOI：
10.1002/prot.10340
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发表时间：
2003-06-01
期刊：
影响因子：
--
通讯作者：
Edwards, AM
中科院分区：
文献类型：
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作者：
Kimber, MS;Vallee, F;Edwards, AM
蛋白质结晶是蛋白质X射线晶体学的主要瓶颈，而蛋白质X射线晶体学是大多数结构蛋白质组学项目的主力。由于对蛋白质结晶的原理知之甚少，无法将其用于强预测意义上，因此最常见的结晶策略需要筛选各种溶液条件，以确定支持晶体成核和生长的小子集。我们测试的假设，更有效的结晶策略，可以制定提取有用的模式和相关性的大型数据集的结晶试验中创建的结构蛋白质组学项目。构建了755种不同蛋白质在均匀条件下纯化和结晶的结晶条件数据库。45%的蛋白质形成晶体。数据挖掘确定了使大多数蛋白质结晶的条件，揭示了许多条件在其行为中高度相关，并表明结晶成功率显著依赖于蛋白质来源的生物体。在48个条件的实验中结晶的蛋白质中，60%可以在6个条件下结晶，94%可以在24个条件下结晶。考虑到来自晶体筛选试验的全方位信息，可以设计出在消耗最少资源的同时具有最大生产力的筛选，并且还建议了扩展现有筛选的进一步有用条件。
Protein crystallization is a major bottleneck in protein X-ray crystallography, the workhorse of most structural proteomics projects. Because the principles that govern protein crystallization are too poorly understood to allow them to be used in a strongly predictive sense, the most common crystallization strategy entails screening a wide variety of solution conditions to identify the small subset that will support crystal nucleation and growth. We tested the hypothesis that more efficient crystallization strategies could be formulated by extracting useful patterns and correlations from the large data sets of crystallization trials created in structural proteomics projects. A database of crystallization conditions was constructed for 755 different proteins purified and crystallized under uniform conditions. Forty-five percent of the proteins formed crystals. Data mining identified the conditions that crystallize the most proteins, revealed that many conditions are highly correlated in their behavior, and showed that the crystallization success rate is markedly dependent on the organism from which proteins derive. Of the proteins that crystallized in a 48-condition experiment, 60% could be crystallized in as few as 6 conditions and 94% in 24 conditions. Consideration of the full range of information coming from crystal screening trials allows one to design screens that are maximally productive while consuming minimal resources, and also suggests further useful conditions for extending existing screens.