An accurate description of solvation effects is of high importance in modeling biomolecular
systems. Our main interest is to find an accurate yet efficient solvation model for …

The semiempirical quantum mechanical (SQM) methods used in drug design are commonly
parametrized and tested on data sets of systems that may not be representative models for …

In this study several commonly used implicit solvent models are compared with respect to
their accuracy of estimating solvation energies of small molecules and proteins, as well as …

The prediction of protein–ligand binding affinities is of central interest in computer-aided
drug discovery, but it is still difficult to achieve a high degree of accuracy. Recent studies …

The free energy of solvation can play an important or even dominant role in the accurate
prediction of binding affinities and various other molecular-scale interaction phenomena …

We have estimated the hydration free energy for 20 neutral drug-like molecules, as well as
for three series of 6–11 inhibitors to avidin, factor Xa, and galectin-3 with four different …

In this paper, we review our efforts to use quantum mechanical (QM) methods to improve
free-energy estimates of the binding of drug candidates to their receptor proteins. First, we …

Implicit solvent methods for classical molecular modeling are frequently used to provide fast,
physics-based hydration free energies of macromolecules. Less commonly considered is …

Accurate yet efficient computational models of solvent environment are central for most
calculations that rely on atomistic modeling, such as prediction of protein–ligand binding …

We present a fast continuum method for the calculation of solvation free energies. It is based
on a continuum electrostatics model with MMFF94 atomic charges combined with a …