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Talk by Dr. Aurelie Tomczak on the "Discovery of novel Chemokines by a Computational 3D Profile-based Approach"

On Friday, March 23 2012, Dr. Aurelie Tomczak (Molecular Signaling Section, Laboratory of  Molecular Immunology, NIAID, National Institutes of Health, Bethesda,  MD, USA) will give a talk on the "Discovery of novel Chemokines by a Computational 3D Profile-based Approach". The talk will take place at 4pm (sharp) in room 007 at the CBI (building E 2.1).



Chemokines are small secreted signal proteins with important roles in immune responses. They share a conserved 3D structure, the so-called IL8-like chemokine fold, which is supported by characteristic disulfide bonds. Sequence- and profile-based computational methods have been proficient in discovering novel chemokines utilizing their sequence-conserved cysteine patterns. However, it has recently been shown that some chemokines escaped annotation by these methods due to low sequence similarity to known chemokines and to different arrangement of cysteines in sequence and 3D.

To overcome this limitation, we developed a novel computational approach for proteome-wide identification of remote homologs of the chemokine family that uses fold recognition in combination with an automatic scaffold-based mapping of disulfide bonds to define a 3D profile of the chemokine family. By applying our methodology to all currently uncharacterized human protein sequences, we have discovered two proteins that, without having significant sequence similarity to known chemokines or characteristic cysteine patterns, show strong structural resemblance to known anti-HIV chemokines. Detailed computational analysis and experimental structural investigations support our structural predictions and highlight several other chemokine-like features of those two proteins. Our obtained results support their functional annotation as putative novel chemokines and encourage further experimental characterization.

The identification of remote human chemokines homologs may provide new insights into the molecular mechanisms causing pathologies such as cancer or AIDS, and may contribute to the development of novel treatments. Besides, the genome-wide applicability of our methodology based on 3D protein family profiles may open up new possibilities for improving and accelerating protein function annotation processes.