Open AccessA modified ACORN to solve protein structures at resolutions of 1.7 Å or better
Author(s) -
Jiaxing Yao,
Woolfson M. M.,
Wilson K. S.,
Dodson E. J.
Publication year - 2005
Publication title -
acta crystallographica section d
Language(s) - English
Resource type - Journals
ISSN - 1399-0047
DOI - 10.1107/s090744490502576x
Subject(s) - fragment (logic) , acorn , algorithm , resolution (logic) , set (abstract data type) , position (finance) , computer science , molecular replacement , extension (predicate logic) , proof of concept , biological system , chemistry , crystallography , artificial intelligence , biology , crystal structure , ecology , finance , economics , programming language , operating system
ACORN has previously been shown to provide an efficient density‐modification procedure for the solution of protein structures using diffraction data to better than 1.3 Å. The initial phase set could be obtained from a variety of sources such as the position of a heavy atom, a set of scatterers such as S that had been positioned from anomalous dispersion measurements, a fragment or a very low homology model placed from a molecular‐replacement search. Several structures solved using the early version of ACORN have been reported in the literature. Here, the effect of applying the original ACORN procedures at lower resolution is reported and new procedures that yield good‐quality maps with data sets of resolution down to 1.7 Å are described. These new procedures involve the artificial extension of data to atomic resolution and new density‐modification processes that develop density at atomic positions that was previously suppressed. The test calculations were aimed firstly towards a proof of principle using a small fragment of a known structure to demonstrate that the procedure could generate correct density and a derived model in initially empty regions of the cell. Further tests addressed the use of more realistic starting models.