Review of QSAR Models and Software Tools for predicting Biokinetic Properties

Abstract

In the assessment of industrial chemicals, cosmetic ingredients, and active substances in pesticides and biocides, metabolites and degradates are rarely tested for their toxicologcal effects in mammals. In the interests of animal welfare and cost-effectiveness, alternatives to animal testing are needed in the evaluation of these types of chemicals. In this report we review the current status of various types of in silico estimation methods for Absorption, Distribution, Metabolism and Excretion (ADME) properties, which are often important in discriminating between the toxicological profiles of parent compounds and their metabolites/degradation products. The review was performed in a broad sense, with emphasis on QSARs and rule-based approaches and their applicability to estimation of oral bioavailability, human intestinal absorption, blood-brain barrier penetration, plasma protein binding, metabolism and. This revealed a vast and rapidly growing literature and a range of software tools. While it is difficult to give firm conclusions on the applicability of such tools, it is clear that many have been developed with pharmaceutical applications in mind, and as such may not be applicable to other types of chemicals (this would require further research investigation). On the other hand, a range of predictive methodologies have been explored and found promising, so there is merit in pursuing their applicability in the assessment of other types of chemicals and products. Many of the software tools are not transparent in terms of their predictive algorithms or underlying datasets. However, the literature identifies a set of commonly used descriptors that have been found useful in ADME prediction, so further research and model development activities could be based on such studies. LIST OF ABBREVIATIONS ADME Absorption, distribution, metabolism and excretion ADMET Absorption, distribution, metabolism, excretion and toxicity ANN Artificial neural networks ASNN Associative Neural Networks BB Blood/brain partitioning BBB Blond/brain barrier BM Bayesian modelling BNN Bayesian neural networks BRANN Bayesian regularized artificial neural network CART Classification and regression trees CG Conjugate gradient CLtot Non-metabolic clearance (bile and urinary elimination) CNS Central nervous system CoMFA Comparative molecular field analysis CoMSIA Comparative molecular similarity index analysis CV Cross-validation DB Database DIDB Metabolism & Transport Drug Interaction Database (University of Washington) F Oral bioavailability FA Fractional absorption FALS Fuzzy adaptive least squares FIRM Formal inference-based recursive modelling GA Genetic algorithm GI Gastrointestinal GRNN General regression neural networks GST Glutathione S-transferase HIA Human intestinal absorption HM Homology modelling HQSAR Hologram quantitative structure-property relationship HSA Human serum albumin ILP Inductive logic programming KL Kohonen learning kNN k-Nearest neighbours k-PLS Kernel-partial least squares LDA Linear discriminant analysis LIE Linear interaction energy LOO-CV Leave-one-out cross validation LR Logistic regression MD Molecular docking MLP-NN Multilayer perceptron neural networks MLR Multiple linear regression ML Machine learning MM Molecular modelling MO Molecular orbital calculations MT Methyltransferase NAT N-acetyltransferase NN Neural networks P Pharmacophore PBPK Physiologically-based pharmacokinetic model/modelling PLS Partial least squares PLS-DA Partial least squares-discriminant analysis PPB Plasma protein binding QM Semi-empirical quantum-mechanical calculations QMSA Quantitative molecular similarity analysis QSAR Quantitative structure-activity relationship QSMR Quantitative structure-metabolism relationship QSPkR Quantitative structure-pharmacokinetic relationship QSPR Quantitative structure-property relationship RBF-NN Radial basis function neural networks RF Random forest technique RMSE Root mean squared error RRM Ridge regression modelling SDEC Standard deviation of error of calculations SDEP Standard deviation of error of predictions SOM Self-organising map SOMFA Self-organising molecular field analysis SULT Sulfotransferase SVM Support vector machine SVR Support vector regression TPSA Topological polar surface area TVM Trend vector model UFS Unsupervised forward selection UGT UDP-glucuronosyltransferase VSA Van der Waals surface area