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PROSPERO : online prediction of crystallographic success from experimental results and sequence
Author(s) -
Zucker Frank H.,
Kim Hae Young,
Merritt Ethan A.
Publication year - 2012
Publication title -
journal of applied crystallography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.429
H-Index - 162
ISSN - 1600-5767
DOI - 10.1107/s002188981201775x
Subject(s) - bottleneck , computer science , sample (material) , sequence (biology) , computational biology , process (computing) , biology , crystallography , data mining , bioinformatics , chemistry , genetics , chromatography , embedded system , operating system
The growth of diffracting crystals from purified proteins is often a major bottleneck in determining structures of biological and medical interest. The PROSPERO web server, http://skuld.bmsc.washington.edu/prospero, is intended both to provide a means of organizing the potentially large numbers of experimental characterizations measured from such proteins, and to provide useful guidance for structural biologists who have succeeded in purifying their target protein but have reached an impasse in the difficult and poorly understood process of turning purified protein into well diffracting crystals. These researchers need to decide which of many possible rescue options are worth pursuing, given finite resources. This choice is even more crucial when attempting to solve high-priority but relatively difficult structures of eukaryotic proteins. The site currently uses the HyGX1 predictor, which was trained and validated on protein samples from pathogenic protozoa (eukaryotes) using results from six types of experiment. PROSPERO allows users to store, analyze and display multiple results for each sample, to group samples into projects, and to share results and predictions with collaborators.