Abstract

An X-ray free electron laser is a new source of x-rays some 10 × 109 times brighter than any previous X-ray source, giving rise to the possibility of structure determination of individual biological particles without crystallization. Some of the earliest samples used in the X-ray free electron laser are viruses because they are about the largest of reproducible bioparticles. We show how common virus near-symmetries can be exploited to find a first approximation to their structures to give a starting point for a perturbation approach to determine their structures.

Highlights

  • Determine these signs more uniquely is that which makes them agree with the magnitudes and signs of the triple correlations11 derived from the ensemble of diffraction patterns

  • Though the method we describe assumes a form of symmetry suggested by Caspar and Klug6 to be usual with regular viruses, we acknowledge that many viruses deviate from this symmetry with their internal genetic material1 or with external features such as spikes7 or hair

  • Where q and q0 refer to two resolution shells, which can be identified with concentric circles on individual diffraction patterns, and hÁ Á Á iDP refers an average over diffraction patterns

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Summary

INTRODUCTION

Determine these signs more uniquely is that which makes them agree with the magnitudes and signs of the triple correlations derived from the ensemble of diffraction patterns. We derive precise expressions for these triple correlations in terms of the relevant expansion coefficients of the diffraction volume, and show how this constraint may be used for determining the signs of the expansion coefficients in the cases of both icosahedral and helical symmetry. The resulting 3D diffraction volume can be phased iteratively with algorithms like charge flipping or standard fiber diffraction phasing algorithms 14 and 15) in the case of a helical virus The resulting 3D diffraction volume can be phased iteratively with algorithms like charge flipping or standard fiber diffraction phasing algorithms (e.g., Refs. 14 and 15) in the case of a helical virus

AVERAGE ANGULAR CORRELATIONS
ICOSAHEDRAL PARTICLE
HELICAL VIRUS
CONCLUSION
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