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The structural genomics experimental pipeline: Insights from global target lists
Author(s) -
O'Toole Nicholas,
Grabowski Marek,
Otwinowski Zbyszek,
Minor Wladek,
Cygler Miroslaw
Publication year - 2004
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.20060
Subject(s) - structural genomics , pipeline (software) , protein data bank (rcsb pdb) , bottleneck , genomics , computational biology , computer science , data mining , genome , biology , protein structure , genetics , gene , biochemistry , embedded system , programming language
Structural genomics (SG) initiatives are currently attempting to achieve the high‐throughput determination of protein structures on a genome‐wide scale. Here we analyze the SG target data that have been publicly released over a period of 16 months to assess the potential of the SG initiatives. We use statistical techniques most commonly applied in epidemiology to describe the dynamics of targets through the experimental SG pipeline. There is no clear bottleneck among the key stages of cloning, expression, purification and crystallization. An SG target will progress through each of these steps with a probability of approximately 45%. Around 80% of targets with diffraction data will yield a crystal structure, and 20% of targets with HSQC spectra will yield an NMR structure. We also find the overlaps among SG targets: 61% of SG protein sequences share at least 30% sequence identity with one or more other SG targets. There is no significant difference in average structure quality among SG structures and other structures in the PDB determined by “traditional” methods, but on average SG structures are deposited to the PDB twice as quickly after X‐ray data collection. Proteins 2004. © 2004 Wiley‐Liss, Inc.