Molecular Simulation Methods to Compute Intrinsic Aqueous Solubility of Crystalline Drug-Like Molecules

MOLECULAR SIMULATION METHODS TO COMPUTE INTRINSIC AQUEOUS SOLUBILITY OF CRYSTALLINE DRUG-LIKE MOLECULES 

Accurate computational methods to predict the solubihty of crystalline organic molecules in aqueous solutions are highly sought after in many fields of the biomo-lecular sciences and industry. For example, predictions of solubility are required in the pharmaceutical and agrochemical industries to assess the bioavailability of de novo designed drugs and the environmental fate of potential pollutants, respectively [1 ]. Due in part to the requirements of industry, interest in the prediction of solubility has risen dramatically in recent years, with hundreds of articles published in the last decade alone. 

The most widely used methods to predict aqueous solubility from molecular structure are quantitative structure-property relationships (QSPRs) [4-6], which are empirical models that use experimental data to learn a statistical relationship between the physical property of interest (i.e., solubility) and molecular descriptors calculable from a simple computational representation of the molecule (e.g., counts of atoms or functional groups, polar surface area, and molecular dipole moment) [1], The current 

Computational Pharmaceutical Solid State Chemistry, First Edition. Edited by Yuriy A. Abramov. 2016 John Wiley Sons, Inc. Published 2016 by John Wiley Sons, Inc. 

MOLECULAR SIMULATION METHODS TO COMPUTE INTRINSIC AQUEOUS 

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