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Solving protein structure from sparse serial microcrystal diffraction data at a storage-ring synchrotron source.

Ti-Yen Lan1, Jennifer L Wierman2,3, Mark W Tate1

  • 1Laboratory of Atomic and Solid State Physics, Cornell University, Ithaca, NY 14853, USA.

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Summary
This summary is machine-generated.

A new expand-maximize-compress (EMC) algorithm solves protein structures from weak X-ray diffraction data, enabling serial microcrystallography with smaller crystals and reducing sample waste.

Keywords:
EMC algorithmX-ray serial microcrystallographyprotein microcrystallographysparse datastorage-ring synchrotron sources

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Area of Science:

  • Structural Biology
  • Biophysics
  • Crystallography

Background:

  • Serial microcrystallography (SMC) at synchrotron sources faces challenges with small crystals due to radiation damage and weak diffraction.
  • Conventional indexing methods often fail for small crystals, leading to data loss.

Purpose of the Study:

  • To introduce and validate a novel method, the expand-maximize-compress (EMC) algorithm, for analyzing weak diffraction data in SMC.
  • To enable structure determination from data frames typically discarded by standard indexing software.

Main Methods:

  • Development and application of the expand-maximize-compress (EMC) algorithm.
  • Testing the EMC algorithm on a serial microcrystallography dataset with weak diffraction signals and significant background scatter.

Main Results:

  • Successfully solved a protein structure at 2.1 Å resolution using the EMC algorithm on weak data.
  • Demonstrated the algorithm's effectiveness despite challenging background noise from the sample delivery medium.

Conclusions:

  • The EMC algorithm enhances serial microcrystallography by enabling analysis of weak diffraction data from small crystals.
  • This method reduces sample consumption and expands the feasibility of SMC at storage-ring sources.