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A. Zakharov and A. Lagunin
community and the public authorities responsible for safety of the environment and
human health. Pharmaceutical companies use computer predictions of toxicity at
the design stage to identify lead compounds with low toxic properties, as well as in
selection of candidates at the optimization stage of potential drugs [2]. An important
priority of pharmaceutical companies during the drug design programs and safety
assessment is an early detection of dangerous toxic effects before significant time
and financial resources will be spent for new drugs at the latest stages of clinical
trials.
Computational prediction of toxicity is a significant part of a more general field
of science—Computational Toxicology. Definition of Computational Toxicology
was given by U.S. Environmental Protection Agency (EPA): an integration of modern computational and information technology with molecular biology, which is
aimed to improve the prioritization and risk assessment of chemicals [3]. Thus, we
have the following definition of toxicology: Toxicology (from the Greek τοξικος—
poison and λογος—science, that is τοξικολογία—the science of poisons) means the
science that studies poisonous, toxic and harmful substances, a potential risk of
their effects on organisms and ecosystems, mechanisms of toxicity, and methods
of diagnosis, prevention and treatment of emerging diseases as the result of such
exposure. Therefore, computational prediction of toxicity can be characterized as
prediction of the effects provided by chemical compounds on biological organisms
and ecosystems which is based on the analysis of structure-activity relationships
using the modern computational and informational technology.
The National Research Council of the United States (NRC) has recently published a basic report entitled “Toxicity Testing in the twenty-first Century: A Vision
and Strategy” [4]. The report is devoted to a well-established methodology in the
toxicity study and discussion on the use of alternative methods, strategies to increase effectiveness and appropriateness of toxicity tests for the risk assessment of
chemicals. According to NRC, the application of system biology, high-throughput
screening and computational technology will be increased significantly in future,
together with other toxicological tests that generate a huge amount of the biological
data (toxicogenomics, proteomics, metabolomics, etc.). The progress in a bioinformatics field, system biology, omics and computational toxicology can transform
and change the animal toxicity testing to the alternative testing methods.
As a practical development and promotion of the computational toxicity prediction for the risk assessment of chemicals in industry, the European Community
has adopted a special law—Registration, Evaluation, Authorization and Restriction
of Chemicals (REACH). REACH provides the basis for a regular use of quantitative/ qualitative analysis of structure—activity (Quantitative Structure-Activity
Relationships—(Q)SAR analysis) in the European Community. The aim of REACH
is to improve the protection of humans and the environment through the better and
earlier identification of the toxic properties of compounds [5]. The effect of 60,000
compounds on humans and the environment, which are produced in the EU in
amounts of more than 1 ton per year, will be evaluated by REACH. Examples of
QSAR practice in REACH are given in the following review [6, 7].
A. Zakharov and A. Lagunin
community and the public authorities responsible for safety of the environment and
human health. Pharmaceutical companies use computer predictions of toxicity at
the design stage to identify lead compounds with low toxic properties, as well as in
selection of candidates at the optimization stage of potential drugs [2]. An important
priority of pharmaceutical companies during the drug design programs and safety
assessment is an early detection of dangerous toxic effects before significant time
and financial resources will be spent for new drugs at the latest stages of clinical
trials.
Computational prediction of toxicity is a significant part of a more general field
of science—Computational Toxicology. Definition of Computational Toxicology
was given by U.S. Environmental Protection Agency (EPA): an integration of modern computational and information technology with molecular biology, which is
aimed to improve the prioritization and risk assessment of chemicals [3]. Thus, we
have the following definition of toxicology: Toxicology (from the Greek τοξικος—
poison and λογος—science, that is τοξικολογία—the science of poisons) means the
science that studies poisonous, toxic and harmful substances, a potential risk of
their effects on organisms and ecosystems, mechanisms of toxicity, and methods
of diagnosis, prevention and treatment of emerging diseases as the result of such
exposure. Therefore, computational prediction of toxicity can be characterized as
prediction of the effects provided by chemical compounds on biological organisms
and ecosystems which is based on the analysis of structure-activity relationships
using the modern computational and informational technology.
The National Research Council of the United States (NRC) has recently published a basic report entitled “Toxicity Testing in the twenty-first Century: A Vision
and Strategy” [4]. The report is devoted to a well-established methodology in the
toxicity study and discussion on the use of alternative methods, strategies to increase effectiveness and appropriateness of toxicity tests for the risk assessment of
chemicals. According to NRC, the application of system biology, high-throughput
screening and computational technology will be increased significantly in future,
together with other toxicological tests that generate a huge amount of the biological
data (toxicogenomics, proteomics, metabolomics, etc.). The progress in a bioinformatics field, system biology, omics and computational toxicology can transform
and change the animal toxicity testing to the alternative testing methods.
As a practical development and promotion of the computational toxicity prediction for the risk assessment of chemicals in industry, the European Community
has adopted a special law—Registration, Evaluation, Authorization and Restriction
of Chemicals (REACH). REACH provides the basis for a regular use of quantitative/ qualitative analysis of structure—activity (Quantitative Structure-Activity
Relationships—(Q)SAR analysis) in the European Community. The aim of REACH
is to improve the protection of humans and the environment through the better and
earlier identification of the toxic properties of compounds [5]. The effect of 60,000
compounds on humans and the environment, which are produced in the EU in
amounts of more than 1 ton per year, will be evaluated by REACH. Examples of
QSAR practice in REACH are given in the following review [6, 7].