Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm

The expand development in the area of scientific researches, especially on biological field, leads to the emergence and discovery of many new chemical compounds. Proteins are one of the hot topics and main concern among the biological subjects for the researchers; due to its complexity, diversity an...

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Bibliographic Details
Main Author: Al-Qattan, Zakaria Noor Aldeen Mahmood
Format: Thesis
Language:English
English
Published: 2010
Subjects:
Online Access:http://etd.uum.edu.my/2312/1/Zakaria_Noor_Aldeen_Mahmood_Al-Qattan.pdf
http://etd.uum.edu.my/2312/2/1.Zakaria_Noor_Aldeen_Mahmood_Al-Qattan.pdf
http://etd.uum.edu.my/2312/
http://lintas.uum.edu.my:8080/elmu/index.jsp?module=webopac-l&action=fullDisplayRetriever.jsp&szMaterialNo=0000764994
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Summary:The expand development in the area of scientific researches, especially on biological field, leads to the emergence and discovery of many new chemical compounds. Proteins are one of the hot topics and main concern among the biological subjects for the researchers; due to its complexity, diversity and it participate in each biological structure. In order to perform their function they tend to fold into their tertiary structure. There are two main ways to determine their structure, one is by laboratory experiment which is very expensive and time subsuming, and the second is by computation. In computation way the operation is known as optimization problem and the optimum solution is to find the conformation with the lowest free energy. In this project, angles based control with Bees Optimization search algorithm were adopted to search with guidance the protein conformational space in order to find the optimum solution. The experiment was conducted on short sequence protein (Met-enkephaline) which has been used in previous researches. The prototype system was built using Visual C# 2008 to fulfill the protein 3D structure prediction requirements. WEKA program application was used for main chain angles (Phi and Psi) data classification. The experiment shows a good accuracy in term of prediction and lowest free energy identification.