Application of HPD Model for Predicting Protein Mutations

Author:

Fidanova Stefka

Abstract

Abstract The proteins are one of the most important part of the organisms. They are complex macromolecules that perform a vital function in all living beings. They are composed of a chain of amino acids. The biological function of a protein is determined by the way it is folded into a specific 3D structure, known as native conformation. The protein folding problem is a fundamental problem in computational molecular biology. The high resolution 3D structure of a protein is the key to the understanding and manipulating of its biochemical and cellular functions. Protein structure could be calculated from knowledge of its sequence and our understanding of the sequence-structure realizations. Various methods have been applied to solve the protein folding problem. In this paper the protein is represented like a sequence over a 3-letter alphabet according to the specific functions of amino acids. After that the folding problem is defined as an optimization problem. Our protein model is multifunctional. It can be used to predict the 3D structure of the protein from its amino acid sequence. The model can predict the changes in the protein folding when several amino acids are mutated. A protein can be constructed by it with the needed 3D folding. In this paper we have concentrated on predicting protein folding changes when some amino acids are mutated.

Publisher

Walter de Gruyter GmbH

Subject

General Computer Science

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