Use of strategically designed protein like sequences in structure and function recognition

Abstract

The advent of high fidelity protein sequencing techniques has led to a considerable wealth of sequence data. However, the number of proteins with information on 3-D structure and functional features available is considerably lower. In spite of improvements in structural and functional genomics initiatives, most experimental procedures in use are time consuming. This has led to a formidable gap between the sequence and structure space which continues to increase. The structural coverage of the proteome of most organisms is not complete and limits the information available on function and the implied biological roles. Computational approaches could provide preliminary ideas on the structure and function of proteins. Protein structures are far more conserved than sequences as a consequence of the evolutionary pressure to maintain the structure and thereby its function. Therefore, recognition of evolutionary relationships among proteins could serve as an important step towards inferences on shared structural and functional features between related proteins. Detailed comparative analysis of evolutionarily related proteins could provide clues to protein structure and consequently its function. However, a notorious problem is detection of relationship between proteins characterized by low sequence similarity (less than about 20%) as unrelated proteins too share poor sequence similarity. The detection of relatedness between sequentially distant proteins serves as a nodal point in structure and function recognition. Hence, most sequence search algorithms rely on deriving these non-trivial relationships between distant homologues to further functional annotation. It has been observed that the limitation in identifying distant relatives is due to the sparseness of the protein sequence space. i.e., if sequences intermediately related to the two proteins (or two protein families) are unavailable, then the recognition of such relationships purely using sequence data becomes challenging. The paucity of natural intermediate s...