325
Chapter 11
Computational Toxicology in Drug Discovery:
Opportunities and Limitations
Alexey Zakharov and Alexey Lagunin
© Springer Science+Business Media Dordrecht 2014
L. Gorb et al. (eds.), Application of Computational Techniques in Pharmacy and Medicine,
Challenges and Advances in Computational Chemistry and Physics 17,
DOI 10.1007/978-94-017-9257-8_11
A. Zakharov ()
National Institutes of Health, National Cancer Institute, Chemical Biology Laboratory,
376 Boyles St., Frederick, MD 21702, USA
e-mail: alexey.zakharov@nih.gov
A. Lagunin
Orechovich Institute of Biomedical Chemistry of Russian Academy of Medical Sciences,
Laboratory of Structure-Function Based Drug Design,
Pogodinskaya St. 10/7, Moscow 119121, Russia
e-mail: alexey.lagunin@ibmc.msk.ru
Abstract Different methods of computational toxicology are used in drug discovery to reveal toxic and dangerous side effects of drug candidates on early stages of
drug development. Information about chemoinformatic, toxicogenomic and system
biological approaches, commercial and freely available software and resources with
data about toxicity of chemicals used in computational toxicology are represented.
General rules and key components of QSAR modeling in respect to opportunities
and limitations of computational toxicology in drug discovery are considered. The
questions of computer evaluation of drug interaction with antitargets, drug-metabolizing enzymes, drug-transporters and related with such interaction toxic and side
effects are discussed in the chapter. Along with an overview of existing approaches
we give examples of the practical application of computer programs GUSAR, PASS
and PharmaExpert to assess the general toxicity and toxic properties of individual
drug-like compounds and drug combinations.
11.1 Introduction
The practical use of computer technology to predict the effects of chemicals on the
environment and human health, preclinical evaluation of toxicity, side effects and
metabolism of drug candidates is of great interest to the scientific community and
human society [1]. Currently, the benefits of using computational methods to predict the toxicity of compounds are properly recognized by members of the business
Chapter 11
Computational Toxicology in Drug Discovery:
Opportunities and Limitations
Alexey Zakharov and Alexey Lagunin
© Springer Science+Business Media Dordrecht 2014
L. Gorb et al. (eds.), Application of Computational Techniques in Pharmacy and Medicine,
Challenges and Advances in Computational Chemistry and Physics 17,
DOI 10.1007/978-94-017-9257-8_11
A. Zakharov ()
National Institutes of Health, National Cancer Institute, Chemical Biology Laboratory,
376 Boyles St., Frederick, MD 21702, USA
e-mail: alexey.zakharov@nih.gov
A. Lagunin
Orechovich Institute of Biomedical Chemistry of Russian Academy of Medical Sciences,
Laboratory of Structure-Function Based Drug Design,
Pogodinskaya St. 10/7, Moscow 119121, Russia
e-mail: alexey.lagunin@ibmc.msk.ru
Abstract Different methods of computational toxicology are used in drug discovery to reveal toxic and dangerous side effects of drug candidates on early stages of
drug development. Information about chemoinformatic, toxicogenomic and system
biological approaches, commercial and freely available software and resources with
data about toxicity of chemicals used in computational toxicology are represented.
General rules and key components of QSAR modeling in respect to opportunities
and limitations of computational toxicology in drug discovery are considered. The
questions of computer evaluation of drug interaction with antitargets, drug-metabolizing enzymes, drug-transporters and related with such interaction toxic and side
effects are discussed in the chapter. Along with an overview of existing approaches
we give examples of the practical application of computer programs GUSAR, PASS
and PharmaExpert to assess the general toxicity and toxic properties of individual
drug-like compounds and drug combinations.
11.1 Introduction
The practical use of computer technology to predict the effects of chemicals on the
environment and human health, preclinical evaluation of toxicity, side effects and
metabolism of drug candidates is of great interest to the scientific community and
human society [1]. Currently, the benefits of using computational methods to predict the toxicity of compounds are properly recognized by members of the business