ASSP; the Antibody Secondary Structure Profile search tool.

Antibodies constitute the first line of defense against harmful invaders. In the post genomics era the sheer size of antibody related NGS information is a major bottleneck in the quest of understanding and tackling complex genetic diseases and immunological disorders. Bioinformatics is becoming hugely involved in the processing of this data with the development of new, more accurate and e cient algorithms. However, one of the major drawbacks of modern bioinformatics is the fact that protein similarity and blast searches are still based on primary amino acid sequence rather than structural data. Primary sequence searches are inadequate, as they fail to provide a realistic fingerprint for the query protein. Antibody function is much more related to its 3D structure and physicochemical profile rather than its primary amino acid sequence. After all, structure is much more conserved than sequence in nature. In this direction, a novel platform has been developed, which is capable of performing a customized hydropathy blast using traditional sequence blast filtering and an integrated fast similarity search algorithm that uses protein secondary structure information. The Antibody Secondary Structure Profile (ASSP) tool will use secondary structural information from the PDB database when available, whereas if the query antibody is not indexed in the RCSB PDB database, it will automatically determine the secondary elements of the given antibody by performing an “on the fly” secondary structure prediction. All query antibodies are then blasted against the RCSB PDB secondary elements database. Hits are scored, ranked and returned to the user via a well-organized and user friendly graphical interface. Copyright c by the paper’s authors. Copying permitted only for private and academic purposes. In: Costas S. Iliopoulos, Alessio Langiu (eds.): Proceedings of the 2nd International Conference on Algorithms for Big Data, Palermo, Italy, 7-9 April 2014, published at http://ceur-ws.org/ † These authors have contributed equally to this study. ⇤ Corresponding author: Sophia Kossida, Bioinformatics & Medical Informatics Team, Biomedical Research Foundation, Academy of Athens, Soranou Efessiou 4, Athens 11527, Greece Tel: + 30 210 6597 199, Fax: +30 210 6597 545 E-mail: skossida@bioacademy.gr