Organisers

• Paolo Carloni (German Research School for Simulation Sciences, Aachen & Julich, Germany)
• Michele Parrinello (Swiss Federal Institute of Technology Zurich, Lugano, Switzerland)
• Ursula Roethlisberger (Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland)

Supports

   CECAM

   Psi-k

Description

Cellular functions - like growth, (programmed) cell death, metabolism etc - ultimately depend of interactions between macromolecules encoded by DNA. Proteins and RNA directly control the cell and regulate its functions through the reactions they perform, by allosteric changes driven by endogeneous and exogeneous factors and by their mutual interactions.

All of these processes involve molecular recognition, i.e. the process by which two or more biological molecules interact to form a specific complex. Molecular recognition is dominated by short-range, often transient, interactions at the contact surface of the interacting molecules. Even conformational changes and assembly of very large macromolecular aggregates, which can be propagated through long distances (tens of Angstroms), are the sum of local interactions between small molecules (like messengers) or macromolecules with their cellular targets.

Ultimately, therefore, even the understanding of the integration of biological complexes into cellular pathways (the so called 'systems biology') requires mechanistic understanding of the physical basis of molecular recognition. A quantitative description of cellular pathways in molecular terms is still mostly missing, although it would strongly impact on pharmaceutical sciences, as drugs target (and mutations affect) pathways, rather than single biomolecules. Such information is also crucial in nanobiotechnology, e.g. to design artificial sensing devices, which in Nature involve entire cascades of events and not only a single protein.

Molecular simulation constitute a key field to contribute to this issue. It can predict structure, dynamics, energetics, reactivity and spectroscopic properties of the cellular components (i.e. large macromolecular aggregates) involved in these pathways.

Tremendous challenges have to be taken before this ambitious goal can be reached. First, the systems are very complex and so are the interactions involved. In addition, ligand-protein processes involve small changes of free energies (less than 1 eV for non-covalent protein-protein interactions), and they are often entropy-driven. Next, the environment is very complex: cell membranes are far from being a simple lipid bilayer whilst the cytoplasm is far from being a simple aqueous solution. Finally, most often experimental structural information is partially or totally lacking.

<h2>Website</h2>

More information available in the <a href='http://www.sissa.it/sbp/SSSAPMCB/' target='_blank' class='t12'>School website</a><br/>

References

[1] Fenollar-Ferrer C., Carnevale V., Raugei S., Carloni P., HIV-1 integrase-DNA interactions investigated by molecular modelling. Comp. Math. Met. Med. 2008, 9(3-4): 231

[2] Laio A, Parrinello M., Escaping free-energy minima. Proc. Natl. Acad. Sci. USA 2002, 99(20):12562.

[3] Biarnés X, Ardèvol A, Planas A, Rovira C, Laio A, Parrinello M., The conformational free energy landscape of beta-D-glucopyranose. Implications for substrate preactivation in beta-glucoside hydrolases. J. Am. Chem. Soc. 2007, 129(35):10686.

[4] Fiorin G, Pastore A, Carloni P, Parrinello M., Using Metadynamics to Understand the Mechanism of Calmodulin/Target Recognition at Atomic Detail. Biophys. J. 2006, 91(8): 2768.

[5] Mantz Y.A., Gervasio F.L., Laino T, Parrinello M., Solvent effects on charge spatial extent in DNA and implications for transfer Phys Rev Lett. 2007, 99(5):058104.

[6] Cascella M, Magistrato A, Tavernelli I, Carloni P, Rothlisberger U. Free in PMC Role of protein frame and solvent for the redox properties of azurin from Pseudomonas aeruginosa. Proc. Natl. Acad. Sci. U S A. 2006, 103(52):19641

[7] Sulpizi M, Raugei S, VandeVondele J, Carloni, P. Sprik, M., Calculation of redox properties: Understanding short- and long-range effects in rubredoxin. J. Phys. Chem. B 2007, 111(15): 3969.

[8] Miguel A. L. Marques, and Eberhard K. U., Gross, Time-Dependent Density Functional Theory, Springer-VerlagmBerlin Heidelberg (2003).

[9] Sulpizi M., Roehrig U. F., Hutter J., and Roethlisberger U., Optical properties of molecules in solution via hybrid TDDFT/MM simulations. Int. J. Quantum Chem. 2004, 101: 671.

[10] Vidossich P., Piana S., Miani A. Carloni P., Deuterium isotope effects in A : T and A : U base pairs: A computational NMR study. Am. Chem. Soc. 2006, 128(22):7215.

[11] Miani A., Raugei S., Carloni P., Helfand M. S., Structure and Raman spectrum of clavulanic acid in aqueous solution. J. Phys. Chem. B 2007, 111(10):2621.

[12] Dal Peraro M., Ruggerone P., Raugei S., Gervasio F. L., Carloni P., Investigating biological systems using first principles Car-Parrinello molecular dynamics simulations, Curr. Opin. Struct. Biol. 2007, 17(2):149.

[13] Neri M., Anselmi C., Cascella M., Maritan A., Carloni P., Coarse-grained model of proteins incorporating atomistic detail of the active site. Phys. Rev. Lett. 2005, 95(21)218102

[14] Ayton G. S., Izvekov S., Noid W. G., Voth, G. A.,Multiscale simulation of membranes and membrane proteins: Connecting molecular interactions to mesoscopic behavior. Computational Modeling of Membrane bilayers, in Current Topics In Membranes 2008, 60:181

[15] Tozzini V., Rocchia W., McCammon J. A. Mapping all-atom models onto one-bead coarse-grained models: General properties and applications to a minimal polypeptide model. J. Chem. Th. Comp. 2006, 2(3)667.

[16] Zanuy D., Gunasekaran K., Lesk A. M., Nussinov R., Computational study of the fibril organization of polyglutamine repeats reveals a common motif identified in beta-helices. J. Mol. Biol. 2006, 358(1)330.

[17] Maurer P., Laio A., Hugosson H. W., Colombo M. C., Rothlisberger U., Automated parametrization of biomolecular force fields from quantum mechanics/molecular mechanics (QM/MM) simulations through force matching. J. Chem. Theory Comput. 2007, 3(2), 628.