In Silico Prediction of Drug Solubility: 4. Will Simple Potentials Suffice?
Artikel i vetenskaplig tidskrift, 2009

In view of the extreme importance of reliable computational prediction of aqueous drug solubility, we have established a Monte Carlo simulation procedure which appears, in principle, to yield reliable solubilities even for complex drug molecules. A theory based on judicious application of linear response and mean field approximations has been found to reproduce the computationally demanding free energy determinations by simulation while at the same time offering mechanistic insight. The focus here is on the suitability of the model of both drug and solvent, i.e., the force fields. The optimized potentials for liquid simulations all atom (OPLS-AA) force field, either intact or combined with partial charges determined either by semiempirical AM1/CM1A calculations or taken from the condensed- phase optimized molecular potentials for atomistic simulation studies (COMPASS) force field has been used. The results illustrate the crucial role of the force field in determining drug solubilities. The errors in interaction energies obtained by the simple force fields tested here are still found to be too large for our purpose but if a component of this error is systematic and readily removed by empirical adjustment the results are significantly improved. In fact, consistent use of the OPLS-AA Lennard-Jones force field parameters with partial charges from the COMPASS force field will in this way produce good predictions of amorphous drug solubility within 1 day on a standard desktop PC. This is shown here by the results of extensive new simulations for a total of 47 drug molecules which were also improved by increasing the water box in the hydration simulations from 500 to 2000 water molecules.

crystal energy calculation

free energy


Monte-Carlo simulation

drug molecule



Kai Lüder

Göteborgs universitet

Lennart Lindfors

Göteborgs universitet

Jan Westergren

Sture Nordholm

Göteborgs universitet

Rasmus Persson

Göteborgs universitet

Mikaela Pedersen

Chalmers, Kemi- och bioteknik

Journal of Computational Chemistry

0192-8651 (ISSN) 1096-987X (eISSN)

Vol. 30 12 1859-





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