QSPR Studies on Aqueous Solubilities of Drug-Like Compounds

Abstract

A rapidly growing area of modern pharmaceutical research is the prediction of aqueous solubility of drug-sized compounds from their molecular structures. There exist many different reasons for considering this physico-chemical property as a key parameter: the design of novel entities with adequate aqueous solubility brings many advantages to preclinical and clinical research and development, allowing improvement of the Absorption, Distribution, Metabolization, and Elimination/Toxicity profile and “screenability” of drug candidates in High Throughput Screening techniques. This work compiles recent QSPR linear models established by our research group devoted to the quantification of aqueous solubilities and their comparison to previous research on the topic.

In silico Prediction of Aqueous Solubility: a Comparative Study of Local and Global Predictive Models

“…Furthermore, many interesting articles were published on this subject from 2007 up to the present. Some examples are the automatic QSAR modelling of aqueous solubility by Gaussian Processes,7 on‐the‐fly selection of a training set for aqueous solubility prediction,8 a novel approach to the generation of an individually tailored “local” training set for predicting solubility,9 quantitative correlation of solubility with chemical structure,10 insolubility classification with accurate prediction probabilities using a metaclassifier,11 accurate prediction of hydration free energies by combination of molecular integral equations theory with structural descriptors,12 prediction of pH‐dependent aqueous solubility of drug‐like molecules,13 uniting cheminformatics and chemical theory to predict the intrinsic aqueous solubility of crystalline drug‐like molecules,14 compilation of recent QSPR linear models devoted to the quantification of aqueous solubilities,15 and a QSAR‐based solubility model for drug‐like compounds 16. Our researches in this field, based on the application of structural and physicochemical similarities over the period 2000–2014 are published in a number of articles 17a–i…”

Recent Advances on Aqueous Solubility Prediction

“…For logS, the performance is reasonable (RMSE = 0.90, r 2 = 0.79 for external test set) [21]. Duchowicz et al recently generated QSPR models for a small molecular set (~148) of drug-like molecules using the Lipinski-based descriptors and a few descriptors selected from the Dragon descriptor set [14,47].…”

“…The models published five years ago were well reviewed by several review papers [8,1,[9][10][11][12][13][14].…”

“…How to construct more reliable models and how to increase a QSAR model's applicability is discussed later in this review. The development of in silico solubility prediction was reviewed by Lipinski et al [8], Jorgensen et al [9], Hou et al [10], Dearden [11], and recently by Wang et al [1,12], Balakin and Tetko [13], and Duchowicz et al [14].…”

BioPPSy: An Open-Source Platform for QSAR/QSPR Analysis

“…Here we show the capabilities of BioPPSy by predicting three critical ADME/Tox properties for drug discovery: aqueous solubility, Blood-Brain Barrier (BBB) permeability and Caco-2 cell permeability. The first property is arguably the most critical of any drug, as its solubility governs both the rate of dissolution of the compound and the maximum concentration reached in the gastrointestinal fluid[4]. As a result it determines whether the compound is orally available and can be ultimately delivered to its intended target [5].…”