Solvent in biomolecular systems

Smith P E and B M Pettitt 1994. Modelling Solvent in Biomolecular Systems. Journal of Physical Chemistry 98 9700-9711. 

Smith PE, Pettit BM (1994) Modeling Solvent in Biomolecular Systems, J Phys Chem, 98 9700... 

Orozco, M. Luque, F. J. Theoretical methods for the description of the solvent effect in biomolecular systems, Chem. Rev. 2000,100,4187-4226. 

Multilevel Finite Element Solution of the Poisson-Boltzmann Equation. II. Refinement at Solvent-accessible Surfaces in Biomolecular Systems. 

N. Baker, M. Holst, and F. Wang,. Comput. Chem., 21,1343 (2000). Adaptive Multilevel Finite Element Solution of the Poisson-Boltzmann Equation II. Refinement at Solvent-Accessible Surfaces in Biomolecular Systems. 

Proper condensed phase simulations require that the non-bond interactions between different portions of the system under study be properly balanced. In biomolecular simulations this balance must occur between the solvent-solvent (e.g., water-water), solvent-solute (e.g., water-protein), and solute-solute (e.g., protein intramolecular) interactions [18,21]. Having such a balance is essential for proper partitioning of molecules or parts of molecules in different environments. For example, if the solvent-solute interaction of a glutamine side chain were overestimated, there would be a tendency for the side chain to move into and interact with the solvent. The first step in obtaining this balance is the treatment of the solvent-solvent interactions. The majority of biomolecular simulations are performed using the TIP3P [81] and SPC/E [82] water models. 

A statistical mechanical fonnulation of implicit solvent representations provides a robust theoretical framework for understanding the influence of solvation biomolecular systems. A decomposition of the free energy in tenns of nonpolar and electrostatic contributions, AVF = AVF " + AVF ° , is central to many approximate treatments. An attractive and widely used treatment consists in representing the nonpolar contribution AVF " by a SASA surface tension term with Eq. (15) and the electrostatic contribution by using the... 

In recent years, there has been an increased need for a proper treatment of the effects of a surrounding medium on the electronic properties of a probe atomic, molecular or biomolecular system. Great progress has been obtained with continuum models [1-5], wherein the solvent is described in some average way and represented by its macroscopic constants. Although successful in some cases, the statistical nature of the liquid environment is not considered in such models. 

The problems being addressed in recent work carried out in various laboratories include the fundamental nature of the solute-water intermolecular forces, the aqueous hydration of biological molecules, the effect of solvent on biomolecular conformational equilibria, the effect of biomolecule - water interactions on the dynamics of the waters of hydration, and the effect of desolvation on biomolecular association 17]. The advent of present generation computers have allowed the study of the structure and statistical thermodynamics of the solute in these systems at new levels of rigor. Two methods of computer simulation have been used to achieve this fundamental level of inquiry, the Monte Carlo and the molecular dynamics methods. 

Application to Polar Biopolymers.—On the basis of the above general relationships, the classical dielectric polarization of any biomolecular system can be evaluated. In the particularly interesting case of a dilute solution of polar biopolymers with a uniform rotational diffusion coeffident a comparatively simple relation can be derived because of the fact that orientational polarization of the solute occurs far below the relaxation range of the solvent. The complex permittivity (without the contribution of background conductivity) turns out to be... 

The simplest solution to increase the sampling of biomolecular systems is to perform longer simulations. Ten years ago, the time scale accessible for peptide simulation in explicit solvent was on the order of 100 ps [37, 38]. Today simulations of this length are routinely used in structural refinement and modelling studies. At present, about 1 s of CPU time on a fast processor is required to compute 1 fs of an MD trajectory of a small biomolecular system in aqueous solution with a total of 5000 atoms. This means that about one day on one processor is required to compute a 100 ps MD trajectory for such a system. However, about one year on 300 processors is required to compute a 1 is MD trajectory for such a system. Thus, the maximum accessible time scale is usually on the order of 100 ns for solvated biomolecules [39, 40]. 

In biological systems the interaction of aqueous solvents with amino acids and pol)q)eptide chains has been examined and even exploited for decades. Two brilliant papers were written by John Edsall and Hugh McKenzie, regarding how proteins might fold and thereby interact with water. " These papers were written at a time when eloquent scientific discussions were conducted through published manuscripts. They are a unique joy to read in today s application oriented environment and are recommended for anyone interested in the thought processes that evolved into modern protein folding theory and biomolecular spectroscopy. 

The appeal of fluorescence spectroscopy in the study of biomolecular systems lies in the characteristic time scale of the emission process, the sensitivity of the technique, and its ability to accommodate rapid and facile changes in the solvent milieu under conditions corresponding to thermodynamic equilibrium. The time scale of the emission process invites exploitation in two related manners. First, information on hydrodynamic aspects of the system is available from steady-state or time-resolved measurements. Second, detailed information on local dynamic processes within the biomolecular matrix may be derived. Information on hydrodynamic aspects of a macromolecular system may be used to study binding processes, that is, the association of small ligands with macromolecules or macromolecule-macromolecule interactions. In this chapter we focus on the latter applications of polarization or anisotropy data. We shall also try to clarify aspects of this area that our experience has shown to be occasionally misunderstood by initiates. 

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