SPIND : a reference-based auto-indexing algorithm for sparse serial crystallography data

Li, Chufeng; Li, Xuanxuan; Kirian, Richard; Spence, John C. H.; Liu, Haiguang; Zatsepin, Nadia A.

doi:10.1107/S2052252518014951

Title: SPIND : a reference-based auto-indexing algorithm for sparse serial crystallography data

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Abstract

SPIND (sparse-pattern indexing) is an auto-indexing algorithm for sparse snapshot diffraction patterns (`stills') that requires the positions of only five Bragg peaks in a single pattern, when provided with unit-cell parameters. The capability of SPIND is demonstrated for the orientation determination of sparse diffraction patterns using simulated data from microcrystals of a small inorganic molecule containing three iodines, 5-amino-2,4,6-triiodoisophthalic acid monohydrate (I3C) [Beck & Sheldrick (2008), Acta Cryst. E 64 , o1286], which is challenging for commonly used indexing algorithms. SPIND , integrated with CrystFEL [White et al. (2012), J. Appl. Cryst. 45 , 335–341], is then shown to improve the indexing rate and quality of merged serial femtosecond crystallography data from two membrane proteins, the human δ-opioid receptor in complex with a bi-functional peptide ligand DIPP-NH ₂ and the NTQ chloride-pumping rhodopsin (CIR). The study demonstrates the suitability of SPIND for indexing sparse inorganic crystal data with smaller unit cells, and for improving the quality of serial femtosecond protein crystallography data, significantly reducing the amount of sample and beam time required by making better use of limited data sets. SPIND is written in Python and is publicly available under the GNU General Public License from https://github.com/LiuLab-CSRC/SPIND.

Authors:

; Li, Xuanxuan;

;

Publication Date:: Tue Jan 01 00:00:00 EST 2019

Sponsoring Org.:: USDOE

OSTI Identifier:: 1485185

Resource Type:: Published Article

Journal Name:: IUCrJ

Additional Journal Information:: Journal Name: IUCrJ Journal Volume: 6 Journal Issue: 1; Journal ID: ISSN 2052-2525

Publisher:: International Union of Crystallography (IUCr)

Country of Publication:: United Kingdom

Language:: English

Citation Formats


                    Li, Chufeng, Li, Xuanxuan, Kirian, Richard, Spence, John C. H., Liu, Haiguang, and Zatsepin, Nadia A. SPIND : a reference-based auto-indexing algorithm for sparse serial crystallography data.  United Kingdom: N. p., 2019. 
Web.  doi:10.1107/S2052252518014951.

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                    Li, Chufeng, Li, Xuanxuan, Kirian, Richard, Spence, John C. H., Liu, Haiguang, & Zatsepin, Nadia A. SPIND : a reference-based auto-indexing algorithm for sparse serial crystallography data.  United Kingdom.  https://doi.org/10.1107/S2052252518014951

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                    Li, Chufeng, Li, Xuanxuan, Kirian, Richard, Spence, John C. H., Liu, Haiguang, and Zatsepin, Nadia A. Tue .  
"SPIND : a reference-based auto-indexing algorithm for sparse serial crystallography data".  United Kingdom.  https://doi.org/10.1107/S2052252518014951.

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@article{osti_1485185,

  title        = {SPIND : a reference-based auto-indexing algorithm for sparse serial crystallography data},

  author       = {Li, Chufeng and Li, Xuanxuan and Kirian, Richard and Spence, John C. H. and Liu, Haiguang and Zatsepin, Nadia A.},

  abstractNote = {SPIND (sparse-pattern indexing) is an auto-indexing algorithm for sparse snapshot diffraction patterns (`stills') that requires the positions of only five Bragg peaks in a single pattern, when provided with unit-cell parameters. The capability of SPIND is demonstrated for the orientation determination of sparse diffraction patterns using simulated data from microcrystals of a small inorganic molecule containing three iodines, 5-amino-2,4,6-triiodoisophthalic acid monohydrate (I3C) [Beck & Sheldrick (2008), Acta Cryst. E 64 , o1286], which is challenging for commonly used indexing algorithms. SPIND , integrated with CrystFEL [White et al. (2012), J. Appl. Cryst. 45 , 335–341], is then shown to improve the indexing rate and quality of merged serial femtosecond crystallography data from two membrane proteins, the human δ-opioid receptor in complex with a bi-functional peptide ligand DIPP-NH 2 and the NTQ chloride-pumping rhodopsin (CIR). The study demonstrates the suitability of SPIND for indexing sparse inorganic crystal data with smaller unit cells, and for improving the quality of serial femtosecond protein crystallography data, significantly reducing the amount of sample and beam time required by making better use of limited data sets. SPIND is written in Python and is publicly available under the GNU General Public License from https://github.com/LiuLab-CSRC/SPIND.},

  doi          = {10.1107/S2052252518014951},

  journal      = {IUCrJ},

  number       = 1,

  volume       = 6,

  place        = {United Kingdom},

  year         = {Tue Jan 01 00:00:00 EST 2019},

  month        = {Tue Jan 01 00:00:00 EST 2019}

}

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