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Two-wavelength MAD phasing and radiation damage: a case study.

Ana González1, Frank von Delft, Robert C Liddington

  • 1Stanford Linear Accelerator Center, Menlo Park, CA 94025, USA.

Journal of Synchrotron Radiation
|April 21, 2005
PubMed
Summary
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Two-wavelength multi-wavelength anomalous diffraction (MAD) experiments on radiation-sensitive vinculin crystals successfully overcame radiation damage. This strategy enabled accurate data processing and phasing for structural determination.

Area of Science:

  • Crystallography
  • Structural Biology
  • Biophysics

Background:

  • Radiation damage poses significant challenges in multi-wavelength anomalous diffraction (MAD) experiments, particularly for radiation-sensitive crystals.
  • Damage leads to increased absorption and loss of isomorphism, complicating data scaling and phasing.

Purpose of the Study:

  • To investigate the feasibility of two-wavelength MAD data collection for radiation-sensitive proteins like vinculin.
  • To develop and compare data processing and scaling strategies to mitigate radiation damage effects.

Main Methods:

  • Collected two-wavelength MAD data at the Se absorption-edge inflection and high-energy remote wavelengths.
  • Compared various data-processing and scaling procedures, focusing on local scaling of unmerged reflections.

Related Experiment Videos

  • Utilized identified selenium sites for phasing to generate an electron density map.

    • Main Results:

    • The two-wavelength MAD strategy reduced the total absorbed dose compared to standard three-wavelength methods.
    • Despite reduced dose, some radiation damage effects like increased unit-cell volume were observed.
    • Local scaling of unmerged reflections proved successful in locating most selenium sites.
    • An interpretable electron density map was obtained after phasing with the identified selenium sites.

    Conclusions:

    • Two-wavelength MAD is a feasible approach for studying radiation-sensitive crystals, even with moderate radiation damage.
    • Effective data processing and scaling strategies are crucial for extracting maximum information from damaged datasets.
    • This method facilitates structural determination using conventional software and data collection setups.