Stewart Patrick Shaw, Mueller-Dieckmann Jochen
Douglas Instruments Ltd, Douglas House, East Garston, Hungerford, Berkshire RG17 7HD, England.
Biocenter Klein Flottbek, University of Hamburg, Ohnhorststrasse 18, 22609 Hamburg, Germany.
Acta Crystallogr F Struct Biol Commun. 2014 Jun;70(Pt 6):686-96. doi: 10.1107/S2053230X14011601. Epub 2014 May 28.
Crystallization remains the bottleneck in the crystallographic process leading from a gene to a three-dimensional model of the encoded protein or RNA. Automation of the individual steps of a crystallization experiment, from the preparation of crystallization cocktails for initial or optimization screens to the imaging of the experiments, has been the response to address this issue. Today, large high-throughput crystallization facilities, many of them open to the general user community, are capable of setting up thousands of crystallization trials per day. It is thus possible to test multiple constructs of each target for their ability to form crystals on a production-line basis. This has improved success rates and made crystallization much more convenient. High-throughput crystallization, however, cannot relieve users of the task of producing samples of high quality. Moreover, the time gained from eliminating manual preparations must now be invested in the careful evaluation of the increased number of experiments. The latter requires a sophisticated data and laboratory information-management system. A review of the current state of automation at the individual steps of crystallization with specific attention to the automation of optimization is given.
从基因到编码蛋白质或RNA的三维模型的晶体学过程中,结晶仍然是瓶颈。为解决这一问题,人们对结晶实验的各个步骤进行了自动化处理,从用于初始筛选或优化筛选的结晶混合液的制备到实验成像。如今,大型高通量结晶设施,其中许多对普通用户群体开放,每天能够进行数千次结晶试验。因此,有可能在生产线基础上测试每个靶标的多种构建体形成晶体的能力。这提高了成功率,使结晶更加便捷。然而,高通量结晶并不能免除用户制备高质量样品的任务。此外,从消除手动制备中节省的时间现在必须投入到对增加的实验数量进行仔细评估中。后者需要一个复杂的数据和实验室信息管理系统。本文对结晶各个步骤的自动化现状进行了综述,特别关注优化的自动化。