The Prediction of Physicochemical Properties

VII. Appendix 1. Commonly Available Methods for the Prediction of Physicochemical Properties SRC EPIWIN Software... 

VII. APPENDIX 1. COMMONLY AVAILABLE METHODS FOR THE PREDICTION OF PHYSICOCHEMICAL PROPERTIES SRC EPIWIN SOFTWARE... 

Structure-activity relationships (SARs) and quantitative structure-activity relationships (QSARs), referred to collectively as QSARs, can be used for the prediction of physicochemical properties, environmental fate parameters (e.g., accumulation and biodegradation), human health effects, and ecotoxicological effects. A SAR is a (qualitative) association between a chemical substructure and the potential of a chemical containing the substructure to exhibit a certain physical or biological effect. A QS AR is a mathematical model that relates a quantitative measure of chemical structure (e.g., a physicochemical property) to a physical property or to a biological effect (e.g., a toxicological endpoint). 

Furthermore, in-silico models need to be challenged with new data, since models derived from small training datasets may become unstable upon the addition of new compounds. Finally, the prediction of physicochemical properties should be checked against experimental data for representative members of a lead series. 

Quantum-mechanical studies on the tautomerism of heterocyclic compounds involve, in general, two aspects. The first deals with the prediction of physicochemical properties of defined tautomeric forms (e.g., ultraviolet spectra, dipole moments, ionization potentials, etc.). This seems to be easy to handle. Using any semiempirical or nonempirical quantum-mechanical computational method, depending on approximations involved in the method, we are able to calculate properties that, more or less, agree with experimental values. Calculations of this type do not contribute to a direct estimation of the relative stability of the tautomers, however they are particularly important for cases in which a tautomeric form of a compound is so rare that it is not possible to measure it directly. 

Russo, N. Abaskin, Y. Calaminici, P. Mineva, T. Sicilia, E. Toscano, M. Gausian Density Functional Method An Alternative Tool for the Prediction of Physicochemical Properties. In Recent Advances in Density Functional Methods, Chong, D. P., Ed. World Scientific Publishing Singapore, 1995 Vol. 1, Chapter 9, pp 335-368. 

O. Ivanciuc, T. Ivancinc, and D. J. Klein, Flow network QSAR for the prediction of physicochemical properties by mapping an electrical resistance network onto a chemical reaction poset, Curr. Comput. Aided Drug Design 9 (2013) 233-240. 

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