Quantitative Structure-Activity Relationships QSAR

Classical QSAR methods focus on correlating experimental activities with experimental descriptors. This allows an identification of important structural features, such as having a pA a value close to 5 or having an electron-withdrawing group in a para-position of a phenyl ring, thereby limiting the field of possible new compounds to 

When the molecular structure of the compounds in the training set has few or no common elements, the alignment may instead be done based on for example the electric moments (dipole, quadrupole, etc.) or on the electrostatic potential on a suitable molecular surface. 

Molecular descriptors are any parameter used in the development of either a SAR or QSAR to model any type of property under investigation e.g., molecular structure, logPwith some type of biological attribute or response e.g., toxicity, LC50, carcinogenicity, etc.). A plethora of potential property response combinations exist and many have been developed with a high degree of repeatability. Some of the more common properties are listed in Table 9.1. 

The partition eoefficient between water and n-octanol occupies a central role for predicting the behaviour of non-polar organic molecules and is the most 

Physicochemical Lipophilicity (as logP) Water solubility Henry s law constant Rates of reaction 

When the organic phase is /r-octanol, the partition coefficient is represented by the or the octanol-water partition coefficient. The relationship is parabolic when the log of the inverse of the concentration is plotted against the log of the partition coefficient and reflects the influence that the degree of lipophilicity has on the movement of compounds across biological membranes. At low lipid solubilities, compounds do not pass as readily through membranes as do compounds that are more lipid soluble. 

The partition coefficient values can span five or six orders of magnitude, therefore the log base 10 values are often used. Most xenobiotics that have a logAo, between 2 and 6 will cross membranes easily and effectively. Above values of logAo,y = 6, the compounds are said to be super-lipophilic and their passage across membranes diminishes because the compounds tend to dissolve in the membrane lipids very strongly and never move or the time to equilibrium is too great to be measured on biologically important time frames. 

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A challenging task in material science as well as in pharmaceutical research is to custom tailor a compound s properties. George S. Hammond stated that the most fundamental and lasting objective of synthesis is not production of new compounds, but production of properties (Norris Award Lecture, 1968). The molecular structure of an organic or inorganic compound determines its properties. Nevertheless, methods for the direct prediction of a compound s properties based on its molecular structure are usually not available (Figure 8-1). Therefore, the establishment of Quantitative Structure-Property Relationships (QSPRs) and Quantitative Structure-Activity Relationships (QSARs) uses an indirect approach in order to tackle this problem. In the first step, numerical descriptors encoding information about the molecular structure are calculated for a set of compounds. Secondly, statistical and artificial neural network models are used to predict the property or activity of interest based on these descriptors or a suitable subset. 

Furthermore, QSPR models for the prediction of free-energy based properties that are based on multilinear regression analysis are often referred to as LFER models, especially, in the wide field of quantitative structure-activity relationships (QSAR). 

When the property being described is a physical property, such as the boiling point, this is referred to as a quantitative structure-property relationship (QSPR). When the property being described is a type of biological activity, such as drug activity, this is referred to as a quantitative structure-activity relationship (QSAR). Our discussion will first address QSPR. All the points covered in the QSPR section are also applicable to QSAR, which is discussed next. 

Practical Applications of Quantitative Structure-Activity Relationships (QSAR) in Environmental Chemistry and Toxicology W. Karcher, J. Devillers, Eds., Kluwer, Dordrecht (1990). 

Quantitative Structure—Activity Relationships (QSAR). Quantitative Stmcture—Activity Relationships (QSAR) is the name given to a broad spectmm of modeling methods which attempt to relate the biological activities of molecules to specific stmctural features, and do so in a quantitative manner (see Enzyme INHIBITORS). The method has been extensively appHed. The concepts involved in QSAR studies and a brief overview of the methodology and appHcations are given here. 

Gao H, Williams C, Labute P, Bajorath J. Binary quantitative structure-activity relationship (QSAR) analysis of estrogen receptor ligands. / Chem Inf Comput Sci 1999 39 164-8. 

In 1868 two Scottish scientists, Crum Brown and Fraser [4] recognized that a relation exists between the physiological action of a substance and its chemical composition and constitution. That recognition was in effect the birth of the science that has come to be known as quantitative structure-activity relationship (QSAR) studies a QSAR is a mathematical equation that relates a biological or other property to structural and/or physicochemical properties of a series of (usually) related compounds. Shortly afterwards, Richardson [5] showed that the narcotic effect of primary aliphatic alcohols varied with their molecular weight, and in 1893 Richet [6] observed that the toxicities of a variety of simple polar chemicals such as alcohols, ethers, and ketones were inversely correlated with their aqueous solubilities. Probably the best known of the very early work in the field was that of Overton [7] and Meyer [8], who found that the narcotic effect of simple chemicals increased with their oil-water partition coefficient and postulated that this reflected the partitioning of a chemical between the aqueous exobiophase and a lipophilic receptor. This, as it turned out, was most prescient, for about 70% of published QSARs contain a term relating to partition coefficient [9]. 

Benigni R, Giuliani A. Quantitative structure-activity relationship (QSAR) studies of mutagens and carcinogens. Med Res Rev 1996 16 267-84. 

Debnath, A.K. (2001) Quantitative Structure-Activity Relationship (QSAR) Paradigm - Hansch Era to New Millennium. Mini Reviews in Medicinal Chemistry, 1, 187-195. 

More recently (2006) we performed and reported quantitative structure-activity relationship (QSAR) modeling of the same compounds based on their atomic linear indices, for finding fimctions that discriminate between the tyrosinase inhibitor compounds and inactive ones [50]. Discriminant models have been applied and globally good classifications of 93.51 and 92.46% were observed for nonstochastic and stochastic hnear indices best models, respectively, in the training set. The external prediction sets had accuracies of 91.67 and 89.44% [50]. In addition to this, these fitted models have also been employed in the screening of new cycloartane compounds isolated from herbal plants. Good behavior was observed between the theoretical and experimental results. These results provide a tool that can be used in the identification of new tyrosinase inhibitor compounds [50]. 

A httle number of works performing Bfx and Fx quantitative structure-activity relationship (QSAR) studies have been described. On the other hand, to gain insight into the biological behavior of Bfxs and Fxs some studies... 

Hansch and Verma contribute to the quantitative structure-activity relationship (QSAR) analysis of heterocyclic topoisomerase I and II inhibitors. These inhibitors, known to inhibit either enzyme, act as antitumor agents and are currently used in chemotherapy and in clinical trials. 

Dudek, A. Z., Arodz, T., Galvez, J. Gomputational methods in developing quantitative structure-activity relationships (QSAR) a review. Comb. Chem. High-Throughput Screen. 2006, 9, 213-228. 

C. N., Boutina, D., Beck, G., Sherbom, B., Cooper, J., Platts, J. A. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. J. Pharm. Sci. 2001, 90, 749-784. 

The increased interest in 3D aspects of organic chemistry and quantitative structure-activity relationship (QSAR) studies has caused an increasing need for a much broader access to 3D molecular structures from experiment or calculation. 

Certain computational methodologies such as some approaches to quantitative structure-activity relationship (QSAR) studies use 3D ligand structures [37, 38]. These methods generally assume that a bioactive conformation has been estab-Hshed for a set of molecules and that these conformers can be ahgned in a maimer that reflects the relative orientation they would adopt in a binding site. It is thus... 

The CHI index is reportedly a relevant parameter in quantitative structure-activity relationship (QSAR) studies [41]. With this approach, log P could be determined in the range -0.45more than 25000 compounds with excellent reproducibility (within 2 index units) and reported in a GlaxoSmithKline database [11]. Two main drawbacks were identified using this approach (i) the assumptions used in Ref [7], i.e. that S is constant for all compounds and that the system dwell volume is excluded in calculations, yield some discrepancies in the resulting log P, and (ii) the set of gradient calibration... 

Lipophilicity is the measure of the partitioning of a compound between a lipidic and an aqueous phase [1]. The terms lipophilicity and hydrophobicity are often used inconsistently in the literature. Lipophilicity encodes most of the intramolecular forces that can take place between a solute and a solvent. Hydrophobicity is a consequence of attractive forces between nonpolar groups and thereby is a component of lipophilicity [2]. Lipophilicity is one of the most informative physicochemical properties in medicinal chemistry and since long successfully used in quantitative structure-activity relationship (QSAR) studies. Its... 

Lewis, D. F., Lake, B. G., Ito, Y., Anzenbacher, P. Quantitative structure-activity relationships (QSARs) within cytochromes P450 2B (CYP2B) subfamily enzymes the importance of lipophilicity for binding and metabolism. Drug Metab. Drug Interact. 

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