Automate Secondary Protein Structure Prediction based on spatial information

JABBAR, NAHLA IBRAHEEM

doi:10.63463/kjes1112

	Automate Secondary Protein Structure Prediction based on spatial information
Kerbala Journal for Engineering Sciences (KJES)
Volume 4, Issue 1, March 2024, Pages 15-24 PDF (1001.83 K)
Document Type: Research Article
DOI: 10.63463/kjes1112
Author
NAHLA IBRAHEEM JABBAR^*
Department of Chemical, College of Engineering, University of Babylon, Iraq
Abstract
This study discusses the prediction of secondary structure protein from features of amino acid images. We define a predication algorithm depending on the spatial information of amino acid sequences. Algorithm A and algorithm B are applied to extract spatial information for clustering types of amino acids in three states: helix(H), strand(E), and coil(C). The accuracy of clustering depends on the improvement of algorithm B and the parameters of algorithms A and B. We apply a novel approach to spatial information extraction from primary protein structure to predicate three states of secondary protein structure. Primary protein sequences are divided into sub-images depending on the win window size. The accuracy of prediction is variable due to the size of the windows. Algorithms A and B are applied to achieve accuracy in each type of secondary protein structure. Helix (H) is 91.93%, Sheet(E) is 93.15%, and Coil (C) is 89.0126 %. In algorithms A and B, spatial information provides automated feature extraction to predict the secondary protein structure ion.
Keywords
: Amino Acid sequence; Bioinformatics; Image processing; Features extraction and Secondary Protein structure

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