International Journal of Molecular Sciences, Volume (19), No (7), Year (2018-7) , Pages (1-9)

Title : ( Using Spectral Representation to Classify Proteins’ Conformational States )

Authors: Seyed Majid Saberi Fathi , Jack A. Tuszynski ,

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Abstract

Numerous proteins are molecular targets for drug action and hence are important in drug discovery. Structure-based computational drug discovery relies on detailed information regarding protein conformations for subsequent drug screening in silico. There are two key issues in analyzing protein conformations in virtual screening. The first considers the protein’s conformational change in response to physical and chemical conditions. The second is the protein’s atomic resolution reconstruction from X-ray crystallography or nuclear magnetic resonance (NMR) data. In this latter problem, information is needed regarding the sample’s position relative to the source of X-rays. Here, we introduce a new measure for classifying protein conformational states using spectral representation and Wigner’s D-functions. Predictions based on the new measure are in good agreement with conformational states of proteins. These results could also be applied to improve conformational alignment of the snapshots given by protein crystallography.

Keywords

protein; conformational states; spectral representation
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@article{paperid:1069400,
author = {Saberi Fathi, Seyed Majid and Jack A. Tuszynski},
title = {Using Spectral Representation to Classify Proteins’ Conformational States},
journal = {International Journal of Molecular Sciences},
year = {2018},
volume = {19},
number = {7},
month = {July},
issn = {1422-0067},
pages = {1--9},
numpages = {8},
keywords = {protein; conformational states; spectral representation},
}

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%0 Journal Article
%T Using Spectral Representation to Classify Proteins’ Conformational States
%A Saberi Fathi, Seyed Majid
%A Jack A. Tuszynski
%J International Journal of Molecular Sciences
%@ 1422-0067
%D 2018

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