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Macromolecular crystallography: conventional and high-throughput methods

Macromolecular crystallography: conventional and high-throughput methods

Sanderson, Mark R. and Skelly, Jane V. (2007) Macromolecular crystallography: conventional and high-throughput methods. Oxford University Press, Oxford, UK. ISBN 9780198520979 (doi:

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Macromolecular crystallography is the study of macromolecules (proteins and nucleic acids) using X-ray crystallographic techniques in order to determine their molecular structure. The knowledge of accurate molecular structures is a pre-requisite for rational drug design, and for structure-based function studies to aid the development of effective therapeutic agents and drugs. The successful determination of the complete genome (genetic sequence) of several species (including humans) has recently directed scientific attention towards identifying the structure and function of the complete complement of proteins that make up that species; a new and rapidly growing field of study called ‘structural genomics’. There are now several important and well-funded global initiatives in operation to identify all of the proteins of key model species. One of the main requirements for these initiatives is a high-throughput crystallization facility to speed-up the protein identification process. The extent to which these technologies have advanced calls for an updated review of current crystallographic theory and practice. This book features the latest conventional and high-throughput methods, and includes contributions from a team of internationally recognized leaders and experts.

Item Type: Book
Uncontrolled Keywords: macromolecules, proteins, nucleic acids, X-ray, crystallographic techniques, molecular structure, rational drug design, structure-based function studies, therapeutic agents
Subjects: Q Science > Q Science (General)
Faculty / Department / Research Group: Faculty of Engineering & Science
Related URLs:
Last Modified: 14 Oct 2016 09:31
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None

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