Fast and Accurate Predictions of Physical-Chemical Properties of Drug-Like Molecules
Figure 1. Selection of new drug-candidates.
Accurate computational methods to predict physical-chemical properties (e.g. solvation free energy, solubility, etc) of organic molecules in water and other liquids are highly sought after in many fields of environmental and biomolecular sciences. For example, predictions of solubility are used in the agrochemical and pharmaceutical industries to assess the environmental fate of potential pollutants and the bioavailability of de novo designed drugs, respectively. While a number of statistical Quantitative Structure-Property Relationship (QSPR) solubility models have been built by many groups, including ourselves , development of a method based on chemical theory and molecular simulation has proved challenging. The main aim of the project is to construct ‘bottom up’ theoretical/computational methods to predict physico-chemical properties. The new methods will be systematically improvable and will provide greater insight into the underlying physical phenomena.
As a pilot result of the project we have recently shown reasonably accurate values for the intrinsic aqueous solubility of druglike organic molecules are obtainable from theory . We combine sublimation free energies calculated using the crystal lattice minimisation program DMACRYS with hydration free energies calculated using the 3D Reference Interaction Site Model (3DRISM) [3,4,5] of the Integral Equation Theory of Molecular Liquids (IET). Intrinsic solubilities of 25 diverse crystalline druglike molecules are computed by our method, obtaining R=0.85 and RMSE =1.45 log10 S units. This is considerably better than results from implicit continuum solvent models such as the polarizable continuum model (PCM). We can fully computationally describe the thermodynamics of the transfer of a druglike molecule from the crystalline solid phase via the gas phase to dilute aqueous solution. Although the 3D RISM free energy functional that we use contains some parameters, our approach is not parameterized against experimentally measured solubilities.
Figure 2. Optimizing physical-chemical properties of pharmaceuticals.
The computational methods developed as part of this project will provide means to select new drug-candidates with good physical-chemical properties (Fig.1) and to optimize physical-chemical properties of existing pharmaceuticals (Fig. 2).