- Role: Professore Ordinario
- Office:U3 stanza 4066
- Telephone number:02- 64483477
Dettagli Progetti di Ricerca
BIOINFORMATICS OF DRUG-RECEPTOR INTERACTIONS
Computer-Aided Drug Design (CADD) has an increasingly important role in simulating drug-receptor interactions, whose comprehension requires a deep understanding of biophysical and biochemical properties of both the ligand and the protein target at an atomic level. The study of interactions (docking) established between a ligand (possibly a drug molecule) and its protein target is performed at different levels of accuracy: rigid docking (protein structure is held fixed and ligand can freely rototranslate around it) is employed for screening of large virtual libraries of organic compounds (generated in silico by one of the subroutines of DELOS platform), in order to preliminarily sort out bad (non-interacting) molecules whereas more sophisticated approaches (MM, MD, Simulated Annealing) are used to determine and refine more realistic (since no constraint is imposed on system atoms) ligand-receptor complex structures. Identification and characterization of putative active sites according to geometric parameters is another task performed. Finally, the latest developed statistic tools (such as Neural Networks) are also adopted in the validation stage of the proposed interaction models.
Partecipants: De Gioia Luca , Fantucci Piercarlo , Zampella Giuseppe
BIOINORGANIC QUANTUM CHEMISTRY
The research is oriented toward the Density Functional Theory (DFT) based dissection of catalytic mechanism (transition state and possible intermediate structures) of proteins containing metallic cofactors, as well as of their synthetic models. Particular interest is devoted to the mechanism of activation of small molecules such as hydrogen (H2) and hydrogen peroxide (H2O2). The former activity is performed by hydrogenases (Fe-Fe and Ni-Fe, according to the different ions being in the cofactor) whereas the latter is carried out by vanadium haloperoxidase (VHPO). Quantum Mechanics (QM) tools and hybrid Quantum Mechanics/Molecular Mechanics (QM/MM) represent a valid resource to elucidate possible speciation forms in solution of synthetic models of enzymes, permit rationalization at molecular level of experimentally observed lower activity of synthetic models with respect to the natural bio-system. Furthermore they can help in showing alternative routes for catalytic productions and in elucidating the intimate mechanism of the “rate determining step” of enzyme catalysis as well as of that performed by synthetic models. This turns out to be attractive for the design of new and more efficient bio-inspired catalysts. Beside ground state properties, the research is focused on the photochemistry of small bioinorganic systems by modeling their excited state properties using Time-Dependent DFT (TDDFT) techniques.
Partecipants: Bertini Luca , De Gioia Luca , Fantucci Piercarlo , Zampella Giuseppe
COMPUTATIONAL METHODS IN PROTEIN STRUCTURES ANALYSIS AND DYNAMICS
Molecular Dynamics (MD) Simulations are used with the aim of investigating structure-function relationship in enzymes and proteins. In fact, long and multiple simulations of biomolecular systems can allow to obtain insights into biomolecular processes at the atomic level, which are often hardly accessible to experimental methods.
Particular attention is addressed to enzymes isolated from cold-adapted organisms. These enzymes are generally characterized by high flexibility, low thermal stability and high specific activity at low temperatures. Other protein systems have been recently investigated using MD simulations, such as heme-binding proteins; moreover, conformational sampling of small molecules and the effect of metal ion binding in proteins have been addressed. The research is also aimed at developing computational tools to deal with the huge amount of data which can be obtained from MD simulations. Another research area concerns development of methods for validating and refining of protein predicted using homology modelling, fold recognition or ab-initio methods.
Validation consists in assessing the accuracy of the predicted protein models using statistical approaches such as neural networks. A final refinement stage is based on techniques of conformational sampling (e.g. MD, Monte Carlo) and global optimisation approaches.
Partecipants: De Gioia Luca , Fantucci Piercarlo