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PEDS Advance Access published online on April 21, 2005
Protein Engineering Design and Selection, doi:10.1093/protein/gzi026
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oupjournals.org
Received November 10, 2004
Revised March 7, 2005
Accepted March 25, 2005

Article

Fold recognition aided by constraints from small angle X-ray scattering data

Wenjun Zheng 1* and Sebastian Doniach 2

1 Departments of Physics and Applied Physics and Laboratory for Advanced Materials, Stanford University, CA 94305, USA; Laboratory of Computational Biology, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
2 Departments of Physics and Applied Physics and Laboratory for Advanced Materials, Stanford University, CA 94305, USA

* To whom correspondence should be addressed.
Wenjun Zheng, E-mail: zhengwj{at}helix.nih.gov


  Abstract

We performed a systematic exploration of the use of structural information derived from small angle X-ray scattering (SAXS) measurements to improve fold recognition. SAXS data provide the Fourier transform of the histogram of atomic pair distances (pair distribution function) for a given protein and hence can serve as a structural constraint on methods used to determine the native conformational fold of the protein. Here we used it to construct a similarity-based fitness score with which to evaluate candidate structures generated by a threading procedure. In order to combine the SAXS scores with the standard energy scores and other 1D profile-based scores used in threading, we made use both of a linear regression method and of a neural network-based technique to obtain optimal combined fitness scores and applied them to the ranking of candidate structures. Our results show that the use of SAXS data with gapless threading significantly improves the performance of fold recognition.

Keywords: fold recognition; linear regression; neural network; small angle X-ray scattering.
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