TSRI Administrative Core Ian Wilson Peter Kuhn Marc Elsliger Frank von Delft Tina Montgomery

1. CollectData.xml Trace.xml Xsolve Processing Steps • Create working directory (e.g. resolve/p3221/nmol1/lambda12 ) • Assemble input.xml files (e.g. from target.xml, scale.xml, solve.xml) • Copy input files to work directory (e.g. solve.mtz, ha.pdb) • XSLT to create shell script (e.g. input_resolve.xml -> resolve.csh) • Execute shell script (e.g. resolve.csh) • Monitor execution (error messages, timeout, file size limits,…) • Parse log file (e.g. resolve.log -> resolve.xml) New workflow for Crystallographer Instead of trying to find the structure solution with an iterative approach, 1.) Provide one time all fundamental information about the data collection 2.) Run all possible processing strategies in parallel without any human intervention 3.) Evaluate the results to determine the best solution Percent of residues built for 44 datasets using 12 different processing strategies Conclusion Xsolve is already a valuable component of the JCSG high-throughput structure determination pipeline. Xsolve supports a non-iterative workflow for crystallographers by trying all possible solutions in parallel. None of the processing strategies outperforms the others for all datasets. However they are often complementing each other and Xsolve can maximize the number of automatically built residues by running several processing strategies in parallel. Xsolve is open for extensions with additional crystallography programs. The first Xsolve version for public release will be available in November 2005. Xsolve will be available for some of the SSRL users outside of JCSG with the start of the next run at SSRL in November 2005. Acknowledgements UCSD Bioinformatics Core John Wooley Adam Godzik Susan Taylor Slawomir Grzechnik Bill West Andrew Morse Jie Quyang Xianhong Wang Jaume Canaves Lukasz Jaroszewski Robert Schwarzenbacher Marc Robinson Rechavi Chris Edwards Olga Kirillova Ray Bean, Josie Alaoen GNF & TSRI Crystallomics Core Ray Stevens Scott Lesley Rebbeca Page Carina Grittini Glen Spraggon Andreas Kreusch Michael DiDonato Daniel McMullan Heath Klock Polat Abdubek Eileen Ambing Tanya Biorac Joanna C. Hale Justin Haugen Mike Hornsby Eric Koesema Edward Nigoghossian Kevin Quijano Megan Wemmer Aprilfawn White Juli Vincent Jeff Velasquez Kin Moy Vandana Sridhar Bernard Collins Thomas Clayton Percent of residues built for 44 datasets using 3 different processing strategies Percent of residues built by ARP/wARP using 3 different processing strategies Stanford /SSRL Structure Determination Core Keith Hodgson Ashley Deacon Britt Hedman Hsiu-Ju Chiu Mitchell D. Miller Henry van den Bedem Qingping Xu Herbert Axelrod Christopher Rife Kevin Jin Silvya Oommachen Amanda Prado Ron Reyes Irimpan Mathews R. Paul Phizackerley Michael Solits Best model for different wavelength combinations of 3 wavelength MAD datasets Scientific Advisory Board Carl-Ivar Brändén, Karolinska Inst., Stockholm (retired 2003) Elbert Branscomb, DOE Joint Genome Inst., Walnut Creek Stephen Cusack, EMBL – Outstation Grenoble Leroy Hood, Inst. for Systems Biology, Seattle John Kuriyan, U.C. Berkeley Erkki Ruoslahti, The Burnham Institute James Wells, Sunesis Pharmaceuticals, Inc. Charles Cantor. Sequenom, Inc. Todd Yeates, UCLA-DOE, Inst. for Genomics and Proteomics James Paulson, Consortium for Functional Glycomics, The Scripps Research Institute TSRI Administrative Core Ian Wilson Peter Kuhn Marc Elsliger Frank von Delft Tina Montgomery Gye Won Han Rong Chen Angela Walker Exploratory Projects Kurt Wüthrich (NMR) Linda Columbus Touraj Etezady-Esfarjani Wolfgang Peti Virgil Woods (DXMS) Two different data collection strategies for 3 wavelength MAD. Using REFMAC without phase restrain is statistically significant better (Paired t-Test p<0.01) NIH Protein Structure Initiative Grant P50 GM62411 The JCSG is funded by the Protein Structure Initiative of the National Institutes of Health, National Institute of General Medical Sciences.SSRL operations is funded by DOE BES, and the SSRL Structural Molecular Biology program by DOE BER, NIH NCRR BTP and NIH NIGMS.