Almost all
important biological processes in nature, including signal transduction, DNA
recognition, transcription, post-translational modification, translation,
protein folding and protein ligand binding, occur in water, which comprises
65–90% of cellular mass. The understanding of solvation is an elementary
prerequisite for the quantitative description and analysis of the
above-mentioned processes.
Solvation models can be roughly divided into two classes: explicit solvent models that treat the solvent
in molecular or atomic detail while implicit solvent models that generally
replace the explicit solvent with a dielectric continuum.While explicit solvent models offer some of
the highest levels of detail, they generally require extensive sampling to
converge thermodynamic or kinetic properties of interest. On the other hand,
implicit solvent models trade detail and some accuracy to eliminate costly
sampling of solvent degrees of freedom. Because of their fewer degrees of
freedom, implicit solvent methods have become popular for many applications in
molecular simulation with applications in the calculations of biomolecular titration states, folding energies, binding
affinities, mutational effects, surface properties, and many other problems in
chemical and biomedical research.
However, most biomolecular implicit solvent
methods currently use ad hoc
assumptions about solvent-solute interfaces to define some of the most
important components of the solvation model. Such assumptions have a
significant impact on the physical interpretation of the implicit solvent
models, the transferability of parameters, and the robustness of observables
calculated from these models.
The proposed project eliminates these assumptions by developing a framework
which builds solvent-solute interfaces from a free energy model which
incorporates fundamental physical properties of the solvent as well as
microscopic details of the solute structure which can be easily obtained from
standard molecular modeling approaches.
Construction of the solute-solvent interface proceeds by minimization of a
free energy functional which incorporates both polar and nonpolar solvent
behavior, involving a balance of surface tension, solvent pressure, attractive
dispersion interactions, and electrostatic influences. As such, the surface is
intrinsically linked to the evaluation of the solvation free energy -- the
fundamental observable of an implicit solvent model.
In the proposed model, the differential geometry of surfaces is utilized to
define the solvation free energy functional and construct the solute-solvent
boundary. The total free energy functional is minimized by coupled geometric
and potential flows constructed by simultaneous variation of the functional
with respect the hypersurface function and the
electrostatic potential. In addition to promising preliminary results
illustrating the power of this approach, extensive validation and application
have been proposed to ensure that this methodology yields accurate solvation
properties.
