Download Area 4: Molecular recognition in biomolecules Computational

Area 4: Molecular recognition in biomolecules Computational design of peptides binding to a given protein surface
Anna Tramontano
Chair Professor of Biochemistry
Department of Physics
Tel. +39.06.49917916 e-mail: [email protected]
ABSTRACT
There is a wide interest in designing peptides able to bind to a specific region of a protein
with the aim of interfering with a known interaction or as starting point for the design of
inhibitors. We plan to develop and implement a tool for the computational design of
peptides binding to a protein surface. The method will be based on the recent observation
that protein-peptide interactions adopt similar relative backbone arrangements as those
observed between different regions of monomeric proteins, although the similarity is not
necessarily present at the level of the amino acid sequence (Vanhee et al., 2009) (Figure
1). This implies that the backbone interaction motifs present in monomeric structures
could be used to guide the design of protein-binding peptides. Our preliminary results
show that such a strategy can be successful.
Figure 1 – Example of a case where a protein-peptide interactions has a similar
arrangement as that observed between different regions of acmonomeric protein.
The system will use the target protein structure and an approximate definition of the
binding site and provide a list of peptides putatively able to bind to the site. The method
will be validated on cases where the structure of a protein with a bound peptide is known
and applied to projects of biomedical relevance.
GROUP COMPONENTS
Anna Tramontano (PO)
Domenico Raimondo (RTD)
Agnieszka Obarska (Post-doc)
Daniele Di Marino (Post-doc)
Ten recent relevant publications
1. Sanchez-Claros and Tramontano A. (2012) Detecting Mutually Exclusive Interactions
in
Protein-Protein
Interaction
Maps.
PLoS
ONE
7(6):
e38765.
doi:10.1371/journal.pone.0038765 IF:4.411
2. Chailyan, A., Tramontano, A., Marcatili, P. A database of immunogloblins with
integrated tools: DIGIT Nucl. Acids Res. (2011) doi: 10.1093/nar/gkr806 IF: 7.836
3. Cesana, M., Cacchiarelli, D., Legnini, I., Santini, T., Sthandier, O., Chinappi, M.,
Tramontano, A. and Bozzoni, I. A Long Noncoding RNA Controls Muscle
Differentiation by Functioning as a Competing Endogenous RNA. (2011) Cell 147,
358–369. IF: 32.401
4. Sayadi A, Briganti L, Tramontano A, Via A (2011) Exploiting publicly available
biological and biochemical information for the discovery of novel short linear motifs.
PLoS One. 2011;6(7):e22270. IF:4.411
5. Ghiotto, F., Marcatili, P. Tenca, C., Calevo, M.G., Yan, X., Albesiano, E., Bagnara,
D. Colombo, M., Cutrona, G., Chu, C.C., Morabito, F., Bruno, S. Ferrarini, F.,
Tramontano, A. Fais, F.,and Chiorazzi, N. (2011) Analysis of mutation patterns of
paired immunoglobulin heavy and light variable domains expressed by chronic
lymphocytic leukemia B cells, Molecular Medicine, 17:1188-1195 IF: 5.908
6. Floris, M., Raimondo, D., Leoni, G., Orsini, M., Marcaili, P. amd Tramontano,
A.(2011) MAISTAS: a tool for automatic structural evaluation of alternative splicing
products. Bioinformatics, 79(5) 1513–1524 IF: 4.877
7. Leoni, G., Le Pera, L., Ferre', F., Raimondo, D., Tramontano, A. 2011 Coding
potential of the products of alternative splicing in human. Genome Biology 12:R9
doi:10.1186/gb-2011-12-1-r9 IF:6.885
8. Zanzoni A., Carbajo D., Diella F., Gherardini P.F., Tramontano A., Helmer-Citterich
M., Via A. Phospho3D 2.0: An enhanced database of three-dimensional structures
of phosphorylation sites (2011) Nucleic Acid Research, Database issue. 39:d268d271 IF: 7.836
9. Tramontano, A. No protein is an island. Current Opin. Struct. Biol. (2009) 19(3):
310-311 IF:9.903
10. Soro, S., Orecchia, A., Lacal, P.M., Morea, V., Ballmr-Hofer, K., Ruffini, F., Ziche, M.,
Zambruno, G., Tramontano, A. and Failla, C.M. (2007) A proangiogenic peptide
derived from vascular endothelial growth factor receptor-1 acts through
alpha5beta1 integrin (2008) Blood, 111:3479-3488. IF: 10.558