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Predicting solvation free energies and describing the complex water behavior that plays an important role in essentially all biological processes is a major challenge from the computational standpoint. While an atomistic, explicit description of the solvent can turn out to be too expensive in large biomolecular systems, most implicit solvent methods fail to capture "dewetting" effects and heterogeneous hydration by relying on a pre-established (i.e., guessed) solvation interface. Here we focus on the Variational Implicit Solvent Method, an implicit solvent method that adds water "plasticity" back to the picture by formulating the solvation free energy as a functional of all possible solvation interfaces. We survey VISM's applications to the problem of molecular recognition and report some of the most recent efforts to tailor VISM for more challenging scenarios, with the ultimate goal of including thermal fluctuations into the framework. The advances reported herein pave the way to make VISM a uniquely successful approach to characterize complex solvation properties in the recognition and binding of large-scale biomolecular complexes.

Predicting solvation free energies and describing the complex water behavior that plays an important role in essentially all biological processes is a major challenge from the computational standpoint. While an atomistic, explicit description of the solvent can turn out to be too expensive in large biomolecular systems, most implicit solvent methods fail to capture "dewetting" effects and heterogeneous hydration by relying on a pre-established (i.e., guessed) solvation interface. Here we focus on the Variational Implicit Solvent Method, an implicit solvent method that adds water "plasticity" back to the picture by formulating the solvation free energy as a functional of all possible solvation interfaces. We survey VISM's applications to the problem of molecular recognition and report some of the most recent efforts to tailor VISM for more challenging scenarios, with the ultimate goal of including thermal fluctuations into the framework. The advances reported herein pave the way to make VISM a uniquely successful approach to characterize complex solvation properties in the recognition and binding of large-scale biomolecular complexes.

We develop and implement geometric methods to study three-dimensional structures of proteins, the knowledge of which is critical to the understanding of the molecules and their interactions. Delaunay and Laguerre methods, which concern sets of overlapping spheres and their interrelationships, are well suited to the study of molecules. We discuss and implement algorithms for the calculation of molecular volume, atomic solvent accessible surface areas, their gradients and discontinuities. This is used for a detailed analysis of parameters obtained by the implicit solvation method, Semi-Explicit Assembly (SEA). We introduce the concept of Laguerre-Intersection cells which consist of the intersection of the Laguerre tessellation and space-filling diagram. This method eliminates the need for explicit water molecules to cap infinite Laguerre cells of certain solvent accessible solute atoms. We discuss and implement a quick weighted Delaunay tetrahedrization algorithm which is tailored specifically to the aforementioned algorithms. Finally, we use concepts from continuum mechanics to study the motion of the HIV protease dimer.

One of the essential requirements of biomolecular modeling is an accurate description of water as a solvent. The challenge is to make this description computationally facile -- reasonably fast, simple, robust and easy to incorporate into existing software packages, yet accurate. The most rigorous procedure to model the effect of aqueous solvent is to explicitly model every water molecule in the system. For many practical applications, this approach is computationally too intense, as the number of required water atoms is on an average at least one order of magnitude larger than the number of atoms of the molecule of interest. Implicit solvent models, in which solvent molecules are replaced by a continuous dielectric, have become a popular alternative to explicit solvent methods. However, implicit solvation models often lack various microscopic details which are crucial for accuracy. One such missing effect that is currently missing from popular implicit models is the so called effect of charge hydration asymmetry (CHA). The missing effect of charge hydration asymmetry -- the asymmetric response of water upon the sign of solute charge -- manifests a characteristic, strong dependence of solvation free energies on the sign of solute charge. Here, we incorporate this missing effect into the continuum solvation framework via the conceptually simplest Born equation and also in the generalized Born model. We identify the key electric multipole moments of model water molecules critical for the various degrees of CHA effect observed in studies based on molecular dynamics simulations using different rigid water models. We then use this gained insight to incorporate CHA first into the Born model, and then into the generalized Born model. The proposed framework significantly improves accuracy of the hydration free energy estimates tested on a comprehensive set of varied molecular solutes -- monovalent and divalent ions, small drug-like molecules, charged and uncharged amino acid

We develop and implement geometric methods to study three-dimensional structures of proteins, the knowledge of which is critical to the understanding of the molecules and their interactions. Delaunay and Laguerre methods, which concern sets of overlapping spheres and their interrelationships, are well suited to the study of molecules. We discuss and implement algorithms for the calculation of molecular volume, atomic solvent accessible surface areas, their gradients and discontinuities. This is used for a detailed analysis of parameters obtained by the implicit solvation method, Semi-Explicit Assembly (SEA). We introduce the concept of Laguerre-Intersection cells which consist of the intersection of the Laguerre tessellation and space-filling diagram. This method eliminates the need for explicit water molecules to cap infinite Laguerre cells of certain solvent accessible solute atoms. We discuss and implement a quick weighted Delaunay tetrahedrization algorithm which is tailored specifically to the aforementioned algorithms. Finally, we use concepts from continuum mechanics to study the motion of the HIV protease dimer.

The treatment of hydration effects in protein dynamics simulations varies in model complexity and spans the range from the computationally intensive microscopic evaluation to simple dielectric screening of charge-charge interactions. This paper compares different solvent models applied to the problem of estimating the free-energy difference between two loop conformations in acetylcholinesterase. Molecular dynamics (MD) simulations were used to sample potential energy surfaces of the two basins with solvent treated by means of explicit and implicit methods. Implicit solvent methods studied include the generalized Born (GB) model, atomic solvation potential (ASP), and the distance-dependent dieletric constant. By using the linear response approximation (LRA), the explicit solvent calculations determined a free-energy difference that is in excellent agreement with the experimental estimate, while rescoring the protein conformations with GB or the Poisson equation showed inconsistent and inferior results. While the approach of rescoring conformations from explicit water simulations with implicit solvent models is popular among many applications, it perturbs the energy landscape by changing the solvent contribution to microstates without conformational relaxation, thus leading to non-optimal solvation free energies. Calculations applying MD with a GB solvent model produced results of comparable accuracy as observed with LRA, yet the electrostatic free-energy terms were significantly different due to optimization on a potential energy surface favored by an implicit solvent reaction field. The simpler methods of ASP and the distance-dependent scaling of the dielectric constant both produced considerable distortions in the protein internal free-energy terms and are consequently unreliable., The original document contains color images. USAMRMC project no. RIID-02-4-1R-069. Published in PROTEINS: Structure, Function, and Bioinformatics, v57 p645-650, 2004.