AUTOMATIC CENTERING OF PROTEIN CRYSTALS USING X-RAYS

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得主要资金， 因此可以在其他CRISP条目中表示。列出的机构是 研究中心，而研究中心不一定是研究者所在的机构。 为了使晶体筛选过程完全自动化，改进了将蛋白质晶体与X射线束自动对齐的方法。 这些方法集中于使用来自在X射线束中的各个晶体位置处拍摄的低剂量衍射图像的平均I/Sig（I）。 使用图像分析程序DISTL分析这些图像，以便估计I/Sig（I），并且基于该分析，在用于最佳晶体对准的特定算法中检查和细化一系列参数，确定并使用晶体的最大衍射功率而不是光学中心。在资助年期间，在每个大分子晶体学光束线上对样品定心的算法进行了彻底的测试。 这些测试表明，不同的光束特性需要进一步完善的算法，这是通过开发自动对齐的光束的角度计的phi轴。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. In order to fully automate the crystal screening process, methods to automatically align protein crystals to the x-ray beam were refined. The approaches focus on using average I/Sig(I) from low-dose diffraction images taken at various crystal positions in the x-ray beam. These images are analyzed using the image analysis program, DISTL, in order to estimate I/Sig(I), and based on this analysis, a range of parameters are examined and refined in specific algorithms for optimal crystal alignment, determining and using the maximum diffracting power of the crystal rather than the optical center. During the grant year, the algorithm for centering samples was thouroughly tested on each macromolecular crystallography beam line. These tests revealed that different beam characteristics necessitated further refinement of the algorithms, which was accomplished through the development of auto-alignment of the beam to the phi axis of the goniometer.