Protein-protein Interactions



We focused not only in the individual characterization of molecular systems but as well in the development of new and crucial methodologies to tackle specific problems in the area of structural computational biology. In the past we have developed a new methodological approach to calculate the binding free energy upon alanine mutation of residues at a protein-protein interface – compASM (Computational Alanine Scanning Mutagenesis). It has been applied since then very successfully to interfaces in a variety of systems (e.g. MDM2/P53, HEL/antibody FvD1.3, HEL/HyHEL-10, ZipA/FtsZ, IgG1/Streptococcal Protein G) allowing to highlight key features of complex formation.  We compared our approach against Thermodynamic Integration (TI), and our results demonstrated that the much faster compASM protocol gives results at the same level of accuracy as the TI method, but at a fraction of the computational time required to run TI. We have also studied in detail the physio-chemical characteristics of the aromatic residues due to their high prevalence as HS at protein-protein interfaces. A new VMD plugin was built and is now available for the scientific community (CompASM). Several Solvent Accessible Surface Area (SASA) features were measured and their role in the determination of the binding Hot-Spots statistically evaluated. The combination of these features was also analyzed by a support vector machine learning (SVM) algorithm, which led to an accurate new model for predicting these crucial residues: SBHD (SASA-Based Hot-Spot Detection)


Our general interest is in protein-based systems and especially interactions involving G-Protein Coupled Receptors (GPCRs). We focus in particular on the dopamine receptor type 2 (D2R) as this is a key hub in neurotransmission in the brain, involved in multiple cognitive, emotional and motor functions. The physiological function of GPCRs involves signalling through interaction with two major classes of signal transduction systems: the G-proteins and the Arrestin proteins (Arr-s). We aim at a comprehensive description of the signalling systems and of the dynamics underlying their functions, investigating fundamental aspects that cannot be inferred or explained solely from the structures of the component parts.