A Comparison of Suffix Tree based Indexing and Search Techniques for Querying Protein Structures

Biological research comes across different protein structures inside a cell which may be required to map to known proteins to quickly determine their functionality. Efficient techniques for searching a protein structure in a database containing all the known proteins are needed to classify the protein and predict its function. Comparing the structure of unknown protein individually with every protein in the database can be highly inefficient. Database indexing methods are therefore best suited for matching an unknown protein structure with the existing set of proteins. Various indexing techniques have been proposed till date that uses various features of protein structure. Indexing techniques based on suffix tree data structure are of prime importance as they provide efficient querying algorithms. In this report we are going to do a comparison of three such techniques that extracts features from protein structures, encode them to create a sequence, build a suffix tree index and provide algorithm to query the index for unknown protein.