Two-Dimensional (2D) In Silico Models for Absorption, Distribution, Metabolism, Excretion and Toxicity (ADME/T) in Drug Discovery

Abstract

With the dawn of new century, major technological advances in the drug discovery field have revolutionized absorption, distribution, metabolism, excretion and toxicity (ADME/T) profiling of new chemical entities (NCEs) among others. The progress made in the in vitro experimental determination of the ADME/T properties fueled the growth in the so-called predictive ADME/T. The process of in silico model development improved significantly with the availability of high quality data as well newer, more accurate statistical methods of analysis. Even several such models appear in the literature regularly, the prediction accuracy is limited to 'local' rather than 'global' applicability domain in majority of the cases. Majority of the efforts are still needed to address several issues such as data quality, accuracy of the results, etc., to increase the usefulness of these models. The ultimate aim is to develop in silico ADME/T models which will largely replace their in vitro experimental counterparts. The current review article discusses the two-dimensional (2D) approaches used in the predictive ADME/T model development and their limitations and usefulness in the discovery process.

Quantitative structure–cytotoxicity relationships (QSCR) for semi-synthetic Taxoteres against cancer cell lines

“…Permeability through Caco-2 cell lines was predicted with the help of physico-chemical properties such as molecular PSA, the number of H-bond donors and acceptors and the number of flexible bonds towards the permeability. The log P and PSA seen to play a major role in affecting the permeability of chemical entities through the cell membranes [36]. Atype_C_17 denotes a ¼ CR 2 carbon, where R denotes any group attached to this carbon atom [29].…”

Reassessing the two-year rodent carcinogenicity bioassay: A review of the applicability to human risk and current perspectives

“…Qualitative and quantitative structure activity relationship (QSARs) prediction is based on the assumption that information can be extracted from known similar chemical structure and have largely relied on high throughput screening in drug development (Bredel and Jacoby, 2004;Macarron, 2006). Linear multivariate methods (2D) in predictive absorption, distribution, metabolism and excretion toxicity profiling have been applied with the goal of advancing the chemical discovery process and possibly replacing reliance on in vitro screening (Kharkar, 2010). Further, a combination of 3D-QSAR docking, local binding energy and energetically favorable binding sites (GRID) for cytochrome P450 enzymes to predict mechanisms of action in rodent carcinogenicity have also been attempted (Fratev and Benfanati, 2008).…”

Prediction of Pharmacokinetic Parameters

“…Permeability: Human intestinal permeability (important for the absorption of oral drugs) and BBB permeability (important for the distribution of CNS active agents and toxicity of non-CNS drugs) constitute important pharmacokinetic parameters (93). The hydrogen-bonding capacity of a drug solute is generally recognized as an important determinant of permeability.…”

“…Drugs reveal equilibrium between their protein-bound and -free forms. Since only unbound free drug exhibits the intended therapeutic effect, therefore, the PPB affinity of drugs becomes a crucial property (93). For these reasons, development of the in silico models for the prediction of PPB is an active area of predictive ADME/Tox.…”

“…It is extremely difficult to develop models for prediction of metabolic fate of drugs due to the complex nature of the biochemical processes involved. Of the two sets of metabolic transformations, oxidation(s) by CYP enzymes is/are critical (93). The rate and extent of metabolism influence clearance, whereas the involvement of particular enzyme(s) may lead to issues relating to the polymorphic nature of some of these enzymes as well as to drug-drug interactions (10).…”