Predictions physicochemical properties

This chapter is a review of practical and easily accessible techniques in physicochemical property prediction. It is not intended to be comprehensive, or be a guide to every kind of approach that can be adopted. The scientific basis of the various methods has been reviewed frequently and recently (Boethling and Mackay, 2000 Fisk 1995). The intention is to set out approaches that can be readily applied, and to give guidance on good practice. The very fact of the ready availability of computerized methods of well-established reliability can give a false sense of security. The examples show that the off-the-peg methods are remarkably effective, which, somewhat ironically, increases the risk of bad practice creeping in. 

Physicochemical property prediction is only one example of this most familiar of approaches to structure-property relationships. 

The calculation of the confidence of predictions will be definitely one of the most important features of physicochemical property prediction in the future, and this field is quickly developing now. 

The benchmarking of methods for physicochemical property predictions is a topic of considerable interest, particularly for the comparison of commercial programs. There were a number of studies and reviews that addressed this problem for prediction of lipophilicity [82-84] aqueous solubility [19,44] as well as other physicochemical property prediction methods [115]. Indeed, since the final purpose of any model development is to predict new data, the benchmarking of different models allows one to compare the advantages of different methodologies. 

A number of methods to predict physicochemical properties of compounds are available as public or commercial products. Table 9.1 lists some of the programs and their providers. Many programs have been developed for prediction of lipophilicity and aqueous solubility of chemicals. A more detailed overview of Internet-based tools that can be used for physicochemical property prediction can be also found elsewhere [142],... 

The availability of data will dramatically transform the field and boost development of new, reliable methods for physicochemical property predictions. The development of methods to estimate the accuracy of a prediction and the applicability domain of models will make it possible to obtain more confident results on their wider use in environmental and pharmaceutical studies. 

Fisk PR, McLaughlin L, Wildey RJ. Good practice in physicochemical property prediction. In Cronin MTD, Livingstone DJ, editors, Predicting chemical toxicity and fate. Boca Raton, FL CRC Press, 2004. p. 41-59. 

These few examples are of course a small and arbitrarily chosen set of methods for the calculation of log P values. Nevertheless, it is hoped that they demonstrate some basic principles in the prediction of a physicochemical property. 

An extensive series of studies for the prediction of aqueous solubility has been reported in the literature, as summarized by Lipinski et al. [15] and jorgensen and Duffy [16]. These methods can be categorized into three types 1 correlation of solubility with experimentally determined physicochemical properties such as melting point and molecular volume 2) estimation of solubility by group contribution methods and 3) correlation of solubility with descriptors derived from the molecular structure by computational methods. The third approach has been proven to be particularly successful for the prediction of solubility because it does not need experimental descriptors and can therefore be applied to collections of virtual compounds also. 

Prediction of various physicochemical properties such as solubihty, lipophhicity log P, pfQ, number of H-donor and acceptor atoms, number of rotatable bonds, polar surface area), drug-likeness, lead-likeness, and pharmacokinetic properties (ADMET profile). These properties can be applied as a filter in the prescreening step in virtual screening. 

It is also important to develop an understanding of the movement of chemicals through the environment by investigating their fate and behaviour. Based on a chemical s inherent physicochemical properties, it is possible to predict with some degree of certainty which environmental compartment it is likely to reside in and to what extent it is likely to be bioavailable and accumulate through the food chain. 

While chemists differed on the relative importance of prediction and accommodation, it seems fair to approximate the consensus as follows. The reasons for accepting the periodic law are, in order of importance, [1] it accurately describes the correlation between physicochemical properties and atomic weights of nearly all known elements ... 

The physicochemical properties of carbonaceous materials can be altered in a predictable manner by different types of treatments. For example, heat treatment of soft carbons, depending on the temperature, leads to an increase in the crystallite parameters, La and Lc and a decrease in the d(0 0 2) spacing. Besides these physical changes in the carbon material, other properties such as the electrical conductivity and chemical reactivity are changed. A review of the electronic properties of graphite and other types of carbonaceous materials is presented by Spain [3],... 

Malkia A, Murtomaki L, Urtti A and Kontturi K. Drug permeation in biomembranes in vitro and in silico prediction and influence of physicochemical properties. Eur J Pharm Sci 2004 23 13-47. 

The distribution of a drug in the body is largely driven by its physicochemical properties and in part for some compounds by the contribution of transporter proteins [17]. By using the Oie-Tozer equation and estimates for ionization (pfCj). plasma protein binding (PPB) and lipophilicity (log quite robust predictions for the volume of distribution at steady state (Vdss), often within 2-fold of the observed value, can be made [18]. 

Blake, J. F. Chemoinformatics -predicting the physicochemical properties of drug-like molecules. Curr. Opin. Biotechnol. 2000, 11, 104-107. 

Schtiurmann, G., Ebert, R. U Ktihne, R. Prediction of physicochemical properties of organic compounds from 2D molecular structure - fragment methods vs. LEER models. Chimia 2006, 60, 691-698. 

Morris, J. J., Bruneau, P. Prediction of physicochemical properties. In Virtual Screening for Bioactive Molecules, Bohm,... 

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