Protein Structure Prediction of Stroke Disease Using Artificial Neural Networks

Abstract

This present study involves prediction of Cytochrome P450 2C19 (CYP2C19) protein secondary structure, by using artificial neural network(ANN) through backpropgation. ANN is one of the methods in machine learning algorithm and is implemented to deal with the central nervous system. The results indicate that CYP2C19 has 173 of Alpha helices, 167 of   Beta sheets and 150 of coils in its total length (490 aminoacids). Based on these results we preceded for the homology modeling using modellar and is verified and validated by using Rampage. It showed above 90% through rampage validation.