Zheng Heping, Handing Katarzyna B, Zimmerman Matthew D, Shabalin Ivan G, Almo Steven C, Minor Wladek
University of Virginia, Department of Molecular Physiology and Biological Physics , 1340 Jefferson Park Avenue, Charlottesville, VA 22908 , USA +1 434 243 6865 ; +1 434 243 2981 ;
Expert Opin Drug Discov. 2015;10(9):975-89. doi: 10.1517/17460441.2015.1061991. Epub 2015 Jul 15.
Macromolecular X-ray crystallography has been the primary methodology for determining the three-dimensional structures of proteins, nucleic acids and viruses. Structural information has paved the way for structure-guided drug discovery and laid the foundations for structural bioinformatics. However, X-ray crystallography still has a few fundamental limitations, some of which may be overcome and complemented using emerging methods and technologies in other areas of structural biology.
This review describes how structural knowledge gained from X-ray crystallography has been used to advance other biophysical methods for structure determination (and vice versa). This article also covers current practices for integrating data generated by other biochemical and biophysical methods with those obtained from X-ray crystallography. Finally, the authors articulate their vision about how a combination of structural and biochemical/biophysical methods may improve our understanding of biological processes and interactions.
X-ray crystallography has been, and will continue to serve as, the central source of experimental structural biology data used in the discovery of new drugs. However, other structural biology techniques are useful not only to overcome the major limitation of X-ray crystallography, but also to provide complementary structural data that is useful in drug discovery. The use of recent advancements in biochemical, spectroscopy and bioinformatics methods may revolutionize drug discovery, albeit only when these data are combined and analyzed with effective data management systems. Accurate and complete data management is crucial for developing experimental procedures that are robust and reproducible.
大分子X射线晶体学一直是确定蛋白质、核酸和病毒三维结构的主要方法。结构信息为基于结构的药物发现铺平了道路,并为结构生物信息学奠定了基础。然而,X射线晶体学仍然存在一些基本局限性,其中一些局限性可以通过结构生物学其他领域的新兴方法和技术来克服和补充。
本综述描述了从X射线晶体学中获得的结构知识如何被用于推动其他生物物理结构测定方法的发展(反之亦然)。本文还涵盖了将其他生化和生物物理方法产生的数据与从X射线晶体学获得的数据进行整合的当前实践。最后,作者阐述了他们对于结构方法与生化/生物物理方法的结合如何能增进我们对生物过程和相互作用理解的展望。
X射线晶体学一直并将继续作为新药发现中使用的实验结构生物学数据的核心来源。然而,其他结构生物学技术不仅有助于克服X射线晶体学的主要局限性,还能提供在药物发现中有用的补充结构数据。尽管只有当这些数据与有效的数据管理系统相结合并进行分析时,生化、光谱学和生物信息学方法的最新进展才可能彻底改变药物发现,但准确和完整的数据管理对于开发稳健且可重复的实验程序至关重要。