Development of a Tool for Comparision of Protein 3D Structure using graph theoretic approachh

Abstract

Today, large volume of sequence and structural data is publically available in the form of biological databases based on integrated effort of molecular biology laboratories throughout the world and advances in information technology. A global challenge in bioinformatics is the rationalization of the huge amount of sequences and structural data with a view not only to derive efficient and useful meaning from this data, but also for designing sharper analytical tools. The analytical tools are required for conversion of sequence data/information into biochemical and biophysical properties and to decipher the structural, functional and evolutionary clues encoded in the data. Pattern matching is one of main important aspects in the analysis of biological sequence and structure data. The alignment and comparison of protein 3D structures are very important and fundamental task in structural biology to study evolutionary and structural relatedness with other proteins and helps biologists to understand various functions and evolution from these structures to identify its structural neighbors. In addition to this, databases of three-dimensional protein structures became so large that fast search tools and comparison methods are required. The 3D structure comparison play a key role in understanding the diversity of structure space by analyzing and deriving interesting scientific insights in the existing vast structural databases. It is important to note that an increase in deposited structures does not just contain quantity, but also variety, complexity, vulnerability, and singularity. Hence, comparison tools are essentially required not only to improve accuracy and coverage but also reduce time complexity. Protein sequence uniquely determines a structure in its native environment. This structural information is vital in understanding the function of a protein. In last one and an half decade, the research on protein structure comparison has been taken up on priority basis and numbers of research articles were exists in literature. There are incremental advances over previous efforts, and still methods are being development for further improvement. The graph theory approaches can be used for protein 3D structure comparison. Graph models can be created using various graph parameters. Generally, graph theory is used to represent/decipher complex spatial structures which are mutually connected and dependent. The 3D structure of protein is a complex structure. The atom level analysis may yield better result in 3D structure analysis than any other method. Considering these important points, the project has been formulated to develop a tool for comparison of protein 3D structure using graph theoretic approach. We have developed two novel methods for comparison of 3D structure based on (1) graph partition and (2) graph properties. Both methods have been implemented in MATLAB by writing codes for various functions. The performance of the developed methodologies is tested with two existing best methods such as CE and jFATCAT on 100 proteins benchmark dataset with SCOP (Structural Classification Of Proteins) database. The proposed methods performed better in terms of classification accuracy and time complexity.