ContaMiner and ContaBase: a webserver and database for early identification of unwantedly crystallized protein contaminants

Autor: Kay Diederichs, Stefan T. Arold, Afaque Ahmad Imtiyaz Momin, Arnaud Hungler
Jazyk: angličtina
Rok vydání: 2016
Předmět:
Zdroj: Journal of Applied Crystallography
ISSN: 1600-5767
0021-8898
Popis: A webserver, titled ContaMiner, has been established, which allows fast molecular-replacement-based screening of crystallographic data against a database (ContaBase) of currently 62 potential contaminants. ContaMiner enables systematic screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for ‘crystallization and preliminary X-ray analysis’ publications.
Solving the phase problem in protein X-ray crystallography relies heavily on the identity of the crystallized protein, especially when molecular replacement (MR) methods are used. Yet, it is not uncommon that a contaminant crystallizes instead of the protein of interest. Such contaminants may be proteins from the expression host organism, protein fusion tags or proteins added during the purification steps. Many contaminants co-purify easily, crystallize and give good diffraction data. Identification of contaminant crystals may take time, since the presence of the contaminant is unexpected and its identity unknown. A webserver (ContaMiner) and a contaminant database (ContaBase) have been established, to allow fast MR-based screening of crystallographic data against currently 62 known contaminants. The web-based ContaMiner (available at http://strube.cbrc.kaust.edu.sa/contaminer/) currently produces results in 5 min to 4 h. The program is also available in a github repository and can be installed locally. ContaMiner enables screening of novel crystals at synchrotron beamlines, and it would be valuable as a routine safety check for ‘crystallization and preliminary X-ray analysis’ publications. Thus, in addition to potentially saving X-ray crystallographers much time and effort, ContaMiner might considerably lower the risk of publishing erroneous data.
Databáze: OpenAIRE