Improving group integration for protein structure retrieval

Proteins are the main building blocks of life. They are involved in virtually all cell functions. Each protein within the living organism has a specific function, but in most of the cases the protein functions can´t be known a priori. In bioinformatics, a lot of effort is made to unravel the functions of an unknown protein. Most of the computational approaches predict the functions based on the protein´s tertiary similarity. In this paper we will present an optimization of an existing algebraic method for protein structural comparison based on features extracted by using group integration with spherical harmonics and D-Wigner matrices [1]. We have optimized this existing method to achieve faster descriptor extraction, while with the introduction of additional methods for measuring similarity between protein descriptors we have increased the precision of the comparison process between protein structures. By measuring classification precision of the existing and improved algorithm we proof the introduced justification of the algorithm.