Computational Systems Pharmacology and Toxicology
CHAPTER 6: Chemical Similarity, Shape Matching and QSAR
Published:01 Mar 2017
E. V. Radchenko, G. F. Makhaeva, V. A. Palyulin, and N. S. Zefirov, in Computational Systems Pharmacology and Toxicology, ed. R. J. Richardson and D. E. Johnson, The Royal Society of Chemistry, 2017, pp. 120-173.
Download citation file:
The similarity property principle, implying that similar structures (should) possess similar properties, lays the basis for the detection, analysis and interpretation of patterns in the known data on the properties (including biological activities) of chemical compounds, as well as for using these patterns to predict the properties for novel structures or to design the structures with desired properties. This chapter begins with the discussion of the molecular similarity analysis and activity landscapes. Then the applications of the quantitative structure–activity/property relationships (QSAR/QSPR) analysis are considered, including the prediction of the biological activities, pharmacokinetic properties and toxicities as well as the relevant physico-chemical properties of drugs, drug-like compounds and organic chemicals in general. A number of the convenient open web-based QSAR/QSPR services are presented. The authors focus on basic ideas and representative examples, on more recent results, and on the techniques and services that are immediately available for solving some of the practical problems of computational pharmacology and toxicology.