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Updated: Feb 13, 2026

Optimization of Crystal Growth for Neutron Macromolecular Crystallography
Published on: March 13, 2021
Distributed computing for macromolecular crystallography
Evgeny Krissinel1, Ville Uski1, Andrey Lebedev1
1Scientific Computing Department, STFC, Rutherford Appleton Laboratory, Didcot OX11 0FA, England.
Abstract:
Modern crystallographic computing is characterized by the growing role of automated structure-solution pipelines, which represent complex expert systems utilizing a number of program components, decision makers and databases. They also require considerable computational resources and regular database maintenance, which is increasingly more difficult to provide at the level of individual desktop-based CCP4 setups. On the other hand, there is a significant growth in data processed in the field, which brings up the issue of centralized facilities for keeping both the data collected and structure-solution projects. The paradigm of distributed computing and data management offers a convenient approach to tackling these problems, which has become more attractive in recent years owing to the popularity of mobile devices such as tablets and ultra-portable laptops. In this article, an overview is given of developments by CCP4 aimed at bringing distributed crystallographic computations to a wide crystallographic community.
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