Towards the Sequence and Structural Prediction of Proteases - An in-silico Study

Proteases cut long sequences of amino acids into fragments and regulate many physiological processes, so, it is called by many as "biology's version of swiss army knives". Different types of proteases have different action mechanisms, biological processes and therefore differ in their structures too. Sequence comparison is considered as backbone of bioinformatics and bioinformatics is the computing response to the molecular revolution in biology. Bioinformaticians and molecular biologists often need molecular sequences like DNA, RNA & proteins to compare them with each other in order to determine the degree of similarity on the basis of which various conclusions are derived regarding the features, structures, behavior and functions of an organism or entire species as a whole. Present proposed study here is an attempt to develop a specific algorithm for searching particular pattern (motifs) in the genome sequences of the protein enzyme, proteases. On the basis of these sequence analysis, one can identify their types and also can predict their secondary or tertiary structures. To address these problems, a 3-layer predictor, is proposed to develop by fusing the functional domain and sequential evolution information: the first layer is for identifying the query protein as protease or non protease; if it is a protease, the process will automatically go to the second layer to further identify it amongst the six types of proteases, and the third layer will be for structural analysis. Besides, analysis based on phylogenetic relation of these proteases by constructing their phylogenetic trees in the light of evolution can be done. Storing all the information extracted from these sequences in a new database is another perspective of the present study.