DMP Final Report: Geometric Analysis of Multiple Protein Structures for the Design of Optimized 3D Protein Motifs

Understanding the function of proteins continues to be a fundamental problem of biology[7]. Functional annotation of proteins through biological experimentation, however, is time-consuming and expensive. Many computational methods for prediction of protein function have been developed. Some tools, such as PSI-BLAST[2], EMATRIX[13], and PROSITE[6], use sequence similarity to help predict function, while others, such as JESS[12], PINTS[1], webFEATURE[10], Geometric Hashing[11], and Match Augmentation[3], predict function using comparisons of geometric structure. Although these computational techniques are accurate and efficient in determining geometric similarity, the choice of protein components to compare is important as well. These components must be both functionally significant and a geometrically distinct representation of that protein relative to other protein structures to prevent matches with proteins that are not functionally similar. Here we explore methods for choosing protein components that will increase the sensitivity and specificity of searching.