4.6 Review

Protein crystallography for non-crystallographers, or how to get the best (but not more) from published macromolecular structures

期刊

FEBS JOURNAL
卷 275, 期 1, 页码 1-21

出版社

BLACKWELL PUBLISHING
DOI: 10.1111/j.1742-4658.2007.06178.x

关键词

protein crystallography; Protein Data Bank; restraints; resolution; R-factor; structure determination; structure interpretation; structure quality; structure refinement; structure validation

资金

  1. Intramural NIH HHS Funding Source: Medline
  2. NIGMS NIH HHS [U54 GM074942, R01 GM117080, GM53163, R01 GM053163, GM74942] Funding Source: Medline
  3. NATIONAL CANCER INSTITUTE [ZIABC010378, ZIABC010348] Funding Source: NIH RePORTER
  4. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM053163, U54GM074942] Funding Source: NIH RePORTER

向作者/读者索取更多资源

The number of macromolecular structures deposited in the Protein Data Bank now exceeds 45 000, with the vast majority determined using crystallographic methods. Thousands of studies describing such structures have been published in the scientific literature, and 14 Nobel prizes in chemistry or medicine have been awarded to protein crystallographers. As important as these structures are for understanding the processes that take place in living organisms and also for practical applications such as drug design, many non-crystallographers still have problems with critical evaluation of the structural literature data. This review attempts to provide a brief outline of technical aspects of crystallography and to explain the meaning of some parameters that should be evaluated by users of macromolecular structures in order to interpret, but not over-interpret, the information present in the coordinate files and in their description. A discussion of the extent of the information that can be gleaned from the coordinates of structures solved at different resolution, as well as problems and pitfalls encountered in structure determination and interpretation are also covered.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据