Structure-based drug design approaches have been an integral part of the drug discovery process and have made a profound contribution at many pharmaceutical companies. As more and more structural information becomes available, a variety of practical structure-based techniques have been developed to accelerate the development at all stages of the drug discovery process. In spite of that, structure-based drug design requires a significant amount of structural resources from experimental methods. The recent explosion in genomic data has resulted in millions of protein sequences and researchers cannot afford to perform XRAY or NMR analysis on every protein. Currently, only 40 000 structures are stored in the PDB database. Consequently, pharmaceutical companies are increasingly turning to bioinformatics technologies which can reduce drug discovery and development costs. The practical role of protein structure prediction is now more important than ever.
Given a target protein sequence, if there is a homologous protein with known 3D structure, it can be found by using sequence search tools like PSI-BLAST or BLASTP. The target's structure is then built from the known structure. However, when the sequence homology is not significant, i.e. less than 25%, PSI-BLAST and BLASTP can not come up with a confident hit. Unlike PSI-BLAST or BLASTP, which simply does a sequence search, protein threading (fold recognition) makes use of both homology and structure information. It scans the protein sequence with an unknown structure against a database of known structures. By using a scoring function and conducting compatibility analysis between three-dimensional structures and linear protein sequences, the best structural template will be identified from which to build the sequence's structure. As a result, protein threading gives a superior prediction than homology modeling when there is marginal sequence homology. A comparison between RAPTOR and PSI-BLAST in CASP competitions can be found here.
RAPTOR is an innovative software tool designed for accurate protein structure prediction. It combines advanced analysis tools in one integrated software solution and provides three different threading methods. RAPTOR's unique integer programming optimization approach is most effective for finding structure templates of targets with low sequence homology and is able to generate high quality models. The easy-to-use interface and easy-to-understand E values are ideal for beginners and experts. Above all, the intuitive display of the output enables users to understand the results simply at a glance.
Software Link: RAPTOR - Protein Structure Prediction Software
