A Level-Set Variational Implicit-Solvent Approach to Hydrophobic Interactions
Dr. Zhongming Wang
Biochemistry and Mathemaics,
UC San Diego
Abstract
Hydrophobic interactions drive relatively apolar molecules to stick together
in an aqueous solution. Such interactions are crucial to the structure,
dynamics, and function of biological systems. The implicit (or continuum) solvent approach is an efficient
way to model such interactions. In this talk, I will first describe a class of variational
implicit-solvent models for solvation. Central in these models is a
free-energy functional of all possible solute-solvent interfaces, coupling both
non-polar and polar contributions. Minimization of this free-energy functional
determines equilibrium solute-solvent interfaces which conceptually replace
solvent accessible surfaces (SAS) or solvent excluded surfaces (SES). I will then
describe a level-set method for capturing equilibrium solute-solvent interfaces.
In our level-set method, a possible solute-solvent interface is represented by the zero
level set (i.e., the zero level surface) of a function and
is evolved to reduce the free energy of the system, eventually into an equilibrium solute-solvent interface.
This method is applied to the study of a large concave wall in water, together with a
small solute molecule. Our level-set calculations determine the solute-solvent interface locations and free energies very accurately
compared with molecular dynamics simulations that have been previously reported.
We also capture the bimodal behavior of the potential of mean force of the underlying hydrophobic interactions.
In addition, we find the curvature correction to the surface tension has a significant influence on the solute-solvent
interface profile in the concave region. All these demonstrate that our mean-field approach and numerical techniques
are capable of efficiently and accurately describing hydrophobic interactions with significant geometric influences.
This is joint work with Li-Tien Cheng, Piotr Setny, Joachim Dzubiella, Bo Li, and J. Andrew McCammon.