Soft Report - Dipartimento di Fisica - Sapienza

Scientific Report – Self Assembly, Clustering, Structural arrestMulti-Scale Simulations of Macromolecular SystemsMathematical modelling and computer simulation ofmacromolecular and biological systems is in a stageof burgeoning progress. Such systems raisenonetheless a great challenge to computationalscientists, mostly on account of the wide anddisparate range of spatio-temporal scales involved intheir dynamical evolution. Typically both problemsinvolve space and time-scale separation calling formulti-scale modelling and proper theoreticalmethodologies derived from statistical mechanics.We tackle the problem with two distinct strategies. Afirst approach, typically applied to colloidal andbiological polymers, is based on a multi-scaleseparation between degrees of freedom, namelyheavy solutes in presence of a light surroundingsolvent. The solvent hydrodynamics is treated at thelevel of the lattice Boltzmann method while thesolutes are treated by means of Molecular Dynamics.The connection between the two descriptions isestablished by introducing thermal noise in theframework of fluctuating hydrodynamics and by amomentum balance technique [1]. Alternatively, wehave developed a numerical scheme to directly solvethe time-dependent Fokker-Planck equation in orderto account for the liquid state of the solvent at thelevel of the collision operators [2]. Our secondstrategy focuses on rare events and complex freeenergylandscapes. The goal here is to reduce thetemporal diversity (restriction of internal modes,spectrum compression, and similar techniques) andartificially induce the process under study (the socalledrare event) in order to investigate itsspontaneous evolution. The two approachesdeveloped in our group are the so-called Blue MoonEnsemble [3] and Mass Rescaling [4] which eitherintroduce a constraint to explore the veryunprobable regions of phase space or alter thevisiting frequency of the low probability regions.Our laboratory is specialized in large-scale simulationof complex systems by developing innovativeFig.1: Transition path of Alanine dipeptide inducedby enhanced conformational sampling.numerical techniques. In the past years we havedeveloped an open-source simulation platformnamed DLPROTEIN which allows for parallel andcross-platform simulation of complex macromolecularsystems [5]. The inclusion of multi-scalemethods into the package is currently in progress.Hydration states is a major actor in stabilizingproteins in aqueous environments. A particularlyinteresting class of proteins are the thermophilicones, which, in contrast to the mesophilic variants,present a smaller heat capacity upon unfolding. Inout studies we have found that the water-exposedsurface area is larger for the thermophile, probablydue to a peculiar corrugation of the exposed surfaceof this species with a larger number of intramolecular hydrogen bonds, stronger electrostaticinteractions and a flatter free energy landscape. Thiswork suggest that the specific hydration stateenhances macromolecular fluctuations but, at thesame time, increases thermal stability [6].Biomolecules embedded in sugar matrices canovercome adverse conditions such as dehydrationand/or high temperatures. Among sugars, trehalosehas been found the most effective protectant.Notwithstanding the large attention devoted, thetrehalose peculiarity is still poorly understood.Experiments show how the size and the hydrogenbonding capability of different saccharides affectprotein dynamics and the protein-matrix coupling ina subtle way. MD simulations have been performedon carboxy myoglobin/water/saccharide (trehalose,sucrose, maltose, glucose) systems. Atomicfluctuations, heme pocket structures, protein-solventhydrogen bonding have been analyzed and compared[7]. Results suggest the action of saccharides be dueto protein-water-sugar interactions via the presenceof interfacial structures containing excess water withrespect to the bulk, and few sugar molecules boundto protein via single hydrogen bonds,in agreementwith the "preferential hydration model".References[1] M. Fyta, S. Melchionna, S. Succi, E. Kaxiras, inpreparation.[2] S. Melchionna, S. Succi, J.-P. Hansen, Intl. J.Mod. Phys. (2006), in press.[3] E.A.Carter, G.Ciccotti, J.T.Hynes, R. Kapral,Chem.Phys.Lett. 156, 472 (1989).[4] S.Melchionna, Phys.Rev.E 62, 8762 (2000).[5] http://www.sissa.it/cm/DLPROTEIN.[6] S. Melchionna, G. Briganti, R. Sinibaldi, Biophys.J. (2006) in press.[7] G. Cottone, S. Giuffrida, G. Ciccotti, L. Cordone,Proteins 59, 291 (2005).AuthorsS. Melchionna, G. CiccottiSOFT-INFM, Dipartimento di Fisica, Università diRoma La Sapienza.SOFT Scientific Report 2004-0692