Neural Network Method for Protein Structure Search using Cell-to-Cell Adhesion
Date Issued
2007
Date
2007
Author(s)
Ho, Cheng-Jung
DOI
en-US
Abstract
Protein structure analysis and alignment is a topic receiving public focus now due to the important applications in biological and medical fields. We introduce a neural network based protein structure search method using the cell-to-cell adhesion property of the feature cells in this article. This method aims to find protein structures consisting of a target segment structure of interest from the protein structure database. By extending the basic idea from a handprinted Chinese character recognition method, we design this method for protein structure matching by taking advantage of the speed and performance of the character recogntion method. The method is a coarse one that aims to identify the protein structure that may contain the substructure of interest and needs further post-processing on the candidates to locate the exact location of the substructure.
We design a new feature extraction method that generates rotation and translation invariant features and use the Procrustes algorithm to find the key substructures which are denoted by radicals. The Procrustes algorithm is originally designed for linguistic analysis and we modify it without loss of its characteristics to apply on the protein structures. Compatibility measurements between the protein structure and radical substructures is of key importance in the process and is formulated as an optimization problem solvable by a Hopfield network. The searching work is performed by a trained backpropagation network that takes in the compatibilty scores of the query substructure and outputs the reference to the candidate protein structures. Finally we compare this method to another index-based method that uses a modified suffix tree algorithm.
We hope that this work can contribute to the biomedical researches in finding cures for a new virus by searching for the similar viral protein structures of viruses with existing cures. Since similar protein structures may have similar functions, the existing cures found by this method may be effective against the new virus too.
This work was partially supported by National Science Council, ROC under contract number NSC 94-2213-E-002-105.
Subjects
蛋白質結構搜尋
類神經網路
霍普菲爾網路
倒傳遞網路
特徵相連關係
protein structure search
neural network
hop eld network
backpropgation
cell-to-cell adhesion
Type
thesis
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