<i>PHENIX</i>: a comprehensive Python-based system for macromolecular structure solution

Paul D. Adams(Lawrence Berkeley National Laboratory), Pavel V. Afonine(Lawrence Berkeley National Laboratory), G. Bunkóczi(University of Cambridge), Vincent B. Chen(Duke Medical Center), Ian Davis(Duke Medical Center), Nathaniel Echols(Lawrence Berkeley National Laboratory), Jeffrey J. Headd(Duke Medical Center), Li‐Wei Hung(Los Alamos National Laboratory), Gary J. Kapral(Duke Medical Center), Ralf W. Grosse‐Kunstleve(Lawrence Berkeley National Laboratory), Airlie J. McCoy(University of Cambridge), Nigel W. Moriarty(Lawrence Berkeley National Laboratory), Robert D. Oeffner(University of Cambridge), Randy J. Read(University of Cambridge), David Richardson(Duke Medical Center), Jane S. Richardson(Duke Medical Center), Thomas C. Terwilliger(Los Alamos National Laboratory), Peter H. Zwart(Lawrence Berkeley National Laboratory)
Acta Crystallographica Section D Biological Crystallography
January 21, 2010
Cited by 24,443Open Access
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Abstract

Macromolecular X-ray crystallography is routinely applied to understand biological processes at a molecular level. However, significant time and effort are still required to solve and complete many of these structures because of the need for manual interpretation of complex numerical data using many software packages and the repeated use of interactive three-dimensional graphics. PHENIX has been developed to provide a comprehensive system for macromolecular crystallographic structure solution with an emphasis on the automation of all procedures. This has relied on the development of algorithms that minimize or eliminate subjective input, the development of algorithms that automate procedures that are traditionally performed by hand and, finally, the development of a framework that allows a tight integration between the algorithms.


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