Chemistry Reference
In-Depth Information
system approach. This program contains a family of expert systems, each
comprising one or more databases, as well as tools for prediction. These databases
are composed mostly of metabolic patterns obtained from already created
databases and frequent metabolic patterns. Biotransformations were implemented
as rules based on the presence or absence of substructures. These rules operate on
the original list of molecules (input) to produce first generation metabolites, and
the process is repeated until the generation of second generation metabolites [37].
These programs should be used in conjunction with some computer-aided toxicity
prediction based on quantitative structure-toxicity relationships or expert systems
for toxicity evaluation [38, 39]. Although several studies have been conducted to
predict the site of metabolism, there is no consensus on which method is the best.
Recent research suggests that the prediction of the metabolism site can be
accomplished by estimating the intrinsic reactivity of ligand atoms. This can be
estimated using Hartree-Fock methods such as, AM1 or quantum mechanical
calculations using DFT approaches [30].
TOXICITY
Toxicity can be defined as any harmful effect of a chemical compound on a target
organism [38]. Toxicology is a rather different matter compared with the other
ADME disciplines because many different mechanisms may be involved [40]. It
is widely accepted that the ionization constant, lipophilicity and solubility are
parameters that can affect toxicological aspects [41]. A problem associated with
predictions of toxicological effects is that similar compounds may exert their
toxicity through different mechanisms [40].
Computational toxicology is an emerging interdisciplinary field that combines
in vitro
assay data with computational approaches to model, understand, and
predict the toxicity of environmental chemicals and pharmaceuticals. The need for
computational methods is due to the innumerous environmental chemicals without
relevant associated toxicity data for estimating potential risks to humans as well as
the ethical difficulties and high costs of performing animal-based studies.
Moreover, many experimental tests often do not provide the necessary molecular
mechanism information required to understand how to extrapolate to human
toxicity risk [42].
