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Title: AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery

Abstract

New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the executionmore » of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully demonstrated. This workflow was run once on the same 96 samples that the group had examined manually and the workflow cycled successfully through all of the samples, collected data from the same samples that were selected manually and located the same peaks of unmodeled density in the resulting difference Fourier maps.« less

Authors:
 [1]; ; ;  [1];  [2];  [1]; ;  [3]; ;  [4];  [5]; ;  [1]
  1. Stanford University, 2575 Sand Hill Road, Menlo Park, CA 94025 (United States)
  2. LogicBlox Inc., 1349 West Peachtree Street NW, Atlanta, GA 30309 (United States)
  3. Cocrystal Discovery Inc., 19805 North Creek Parkway, Bothell, WA 98011 (United States)
  4. The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 (United States)
  5. University of California, One Shields Avenue, Davis, CA 95616 (United States)
Publication Date:
OSTI Identifier:
22351284
Resource Type:
Journal Article
Journal Name:
Acta Crystallographica. Section D: Biological Crystallography
Additional Journal Information:
Journal Volume: 69; Journal Issue: Pt 5; Other Information: PMCID: PMC3640469; PMID: 23633588; PUBLISHER-ID: en5533; OAI: oai:pubmedcentral.nih.gov:3640469; Copyright (c) International Union of Crystallography 2013; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0907-4449
Country of Publication:
Denmark
Language:
English
Subject:
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND SUPERFLUIDITY; CAPACITY; CRYSTALLOGRAPHY; CRYSTALS; DATA ANALYSIS; DENSITY; DESIGN; DIFFRACTION; ELECTRON DENSITY; INTERACTIONS; PEAKS; PROTEINS; SCREENING; SIMULATION; SYNCHROTRON RADIATION

Citation Formats

Tsai, Yingssu, Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080, McPhillips, Scott E., González, Ana, McPhillips, Timothy M., Zinn, Daniel, Cohen, Aina E., Feese, Michael D., Bushnell, David, Tiefenbrunn, Theresa, Stout, C. David, Ludaescher, Bertram, Hedman, Britt, Hodgson, Keith O., Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080, and Soltis, S. Michael, E-mail: soltis@slac.stanford.edu. AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery. Denmark: N. p., 2013. Web. doi:10.1107/S0907444913001984.
Tsai, Yingssu, Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080, McPhillips, Scott E., González, Ana, McPhillips, Timothy M., Zinn, Daniel, Cohen, Aina E., Feese, Michael D., Bushnell, David, Tiefenbrunn, Theresa, Stout, C. David, Ludaescher, Bertram, Hedman, Britt, Hodgson, Keith O., Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080, & Soltis, S. Michael, E-mail: soltis@slac.stanford.edu. AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery. Denmark. https://doi.org/10.1107/S0907444913001984
Tsai, Yingssu, Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080, McPhillips, Scott E., González, Ana, McPhillips, Timothy M., Zinn, Daniel, Cohen, Aina E., Feese, Michael D., Bushnell, David, Tiefenbrunn, Theresa, Stout, C. David, Ludaescher, Bertram, Hedman, Britt, Hodgson, Keith O., Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080, and Soltis, S. Michael, E-mail: soltis@slac.stanford.edu. 2013. "AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery". Denmark. https://doi.org/10.1107/S0907444913001984.
@article{osti_22351284,
title = {AutoDrug: fully automated macromolecular crystallography workflows for fragment-based drug discovery},
author = {Tsai, Yingssu and Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080 and McPhillips, Scott E. and González, Ana and McPhillips, Timothy M. and Zinn, Daniel and Cohen, Aina E. and Feese, Michael D. and Bushnell, David and Tiefenbrunn, Theresa and Stout, C. David and Ludaescher, Bertram and Hedman, Britt and Hodgson, Keith O. and Stanford University, 333 Campus Drive, Mudd Building, Stanford, CA 94305-5080 and Soltis, S. Michael, E-mail: soltis@slac.stanford.edu},
abstractNote = {New software has been developed for automating the experimental and data-processing stages of fragment-based drug discovery at a macromolecular crystallography beamline. A new workflow-automation framework orchestrates beamline-control and data-analysis software while organizing results from multiple samples. AutoDrug is software based upon the scientific workflow paradigm that integrates the Stanford Synchrotron Radiation Lightsource macromolecular crystallography beamlines and third-party processing software to automate the crystallography steps of the fragment-based drug-discovery process. AutoDrug screens a cassette of fragment-soaked crystals, selects crystals for data collection based on screening results and user-specified criteria and determines optimal data-collection strategies. It then collects and processes diffraction data, performs molecular replacement using provided models and detects electron density that is likely to arise from bound fragments. All processes are fully automated, i.e. are performed without user interaction or supervision. Samples can be screened in groups corresponding to particular proteins, crystal forms and/or soaking conditions. A single AutoDrug run is only limited by the capacity of the sample-storage dewar at the beamline: currently 288 samples. AutoDrug was developed in conjunction with RestFlow, a new scientific workflow-automation framework. RestFlow simplifies the design of AutoDrug by managing the flow of data and the organization of results and by orchestrating the execution of computational pipeline steps. It also simplifies the execution and interaction of third-party programs and the beamline-control system. Modeling AutoDrug as a scientific workflow enables multiple variants that meet the requirements of different user groups to be developed and supported. A workflow tailored to mimic the crystallography stages comprising the drug-discovery pipeline of CoCrystal Discovery Inc. has been deployed and successfully demonstrated. This workflow was run once on the same 96 samples that the group had examined manually and the workflow cycled successfully through all of the samples, collected data from the same samples that were selected manually and located the same peaks of unmodeled density in the resulting difference Fourier maps.},
doi = {10.1107/S0907444913001984},
url = {https://www.osti.gov/biblio/22351284}, journal = {Acta Crystallographica. Section D: Biological Crystallography},
issn = {0907-4449},
number = Pt 5,
volume = 69,
place = {Denmark},
year = {2013},
month = {5}
}