Bulk descriptors

By fitting a non-linear model equation with identical regression coefficients in the three subequations with identical regression coefficients for each of the bulk descriptors ui, a j j, and 0C(+), three new subequations were obtained. Finally, with identical regression coeffidents in the three subequations for the descriptors a and Xq+, with the exception of SCaujand XCal+j, Eqs. 4.7a-c were derived. 

The importance of hydrogen bonds for dmg-membrane interaction and transport has been stressed recently [20]. The authors analyzed the data of Vaes et al. [21] regarding the partitioning of polar and non-polar chemicals into SUVs of L-a-dimyris-toylphosphatidylcholine and into octanol. Descriptors used were a bulk descriptor, a, and the H-bond acceptor and donor strength, LC EQ. Regression analysis led to Eq. 4.8 ... 

From the literature there is evidence that in GC on polar phases and in normal-phase (adsorption) liquid chromatography (HPLC and TLC) the chemically specific, molecular size-independent intermolecular interactions play the main retention-determining role. For example, the HPLC retention parameters determined for substituted benzenes on porous graphite are described by QSRR equations comprising polarity descriptors but containing no bulk descriptors [93-95]. Because, in general, it is difficult to quantify the polarity properties precisely, the QSRR for GC on polar phases and for normal-phase HPLC are usually of lower quality than in the case of GC on non-polar phases and in the case of reversed-phase liquid chromatography. 

The term bulk descriptors can be used to denote steric descriptors of the whole molecule, referring to the measure of the hindrance of the molecule when it is considered as a part of a system and dense assembly, each molecule being constrained by its neighbours to a limited region in space. 

Bulk descriptors Mol. Wt., van der Waals volume, dead space volume, collision diameter, approach diameter, surface area, molar refraction... 

The most widely used descriptor for the hydrophobicity term in toxicology is the distribution coefficient between octanol and water, log Pq< - (the environmental scientists would rather call it log The bulk solvent octanol is of course a... 

The Jamieson paper reports the results of a number of studies, some successful, others not. Failures can be ascribed to the difficulties encountered in log P control. The first evident trouble concerns the choice of the lipophilicity descriptor many prefer log P, but this choice is questionable as has been outlined by Lombardo (see Chapter 16). Secondly, variations in lipophilicity profile influence not only hERG activity, but also target selectivity and also ADMET properties. Lipophilicity is a bulk property and its modification can involve different moieties of the molecules. Once the chemical modulation has been designed, but before moving to the bench, the research group should predict the consequences of this change on each step of the drug s action, but unfortunately this is not always done. 

The octanol-water partition coefficient, Kow, is the most widely used descriptor of hydrophobicity in quantitative structure activity relationships (QSAR), which are used to describe sorption to organic matter, soil, and sediments [15], bioaccumulation [104], and toxicity [105 107J. Octanol is an amphiphilic bulk solvent with a molar volume of 0.12 dm3 mol when saturated with water. In the octanol-water system, octanol contains 2.3 mol dm 3 of water (one molecule of water per four molecules of octanol) and water is saturated with 4.5 x 10-3 mol dm 3 octanol. Octanol is more suitable than any other solvent system (for) mimicking biological membranes and organic matter properties, because it contains an aliphatic alkyl chain for pure van der Waals interactions plus the alcohol group, which can act as a hydrogen donor and acceptor. 

MolES E-state descriptor representing the molecular bulk... 

Russell et al. (1992) conducted a similar study using the same data set from Hine and Mookeijee (1975). They developed a computer-assisted model based on five molecular descriptors which was related to the compound s bulk, lipophilicity, and polarity. They found that 63 molecular stmctures were highly correlative with the log of Henry s law constants (r = 0.96). 

Geometry-based approach from a geometrical point of view, a cavity is a concave empty space that can be described using 2D (surface) or 3D shape descriptors (19-21). We consider three regions in the protein environment the protein bulk, the bulk solvent and the cavity space. The protein bulk is the space filled by the protein atoms. The bulk solvent is the space outside the protein which differentiates from the space inside the protein which defines the cavity where the drug-like molecule is supposed to bind. The identification of protein pockets by numerical methods suppose the capacity to discriminate first the protein bulk from the rest... 

A preliminary and essential step in a QSAR study is to evaluate the database to identify any outliers and hidden patterns, trends, and major groupings. Outliers refer to certain members of the database exhibiting mechanistic behaviors so different that the outlier cannot belong to the bulk of the data. Selecting suitable molecular descriptors, whether they are theoretical or empirical or are derived from readily available experimental characteristics of the structures, is an important step in the development of sound QSAR models. Many descriptors reflect simple molecular properties and thus can provide insight into the physicochemical nature of the activity or property under consideration. 

Descriptors derived via quantum chemistry are fundamentally different from experimentally measured quantities although there is some natural overlap. Unlike experimental measurements, quantum-chemical calculations have no statistical error. An inherent error is associated with the assumptions required to facilitate the calculations, but the computational error is considered to be approximately constant throughout the series when using quan-tum-chemistry-based descriptors with a series of related compounds. In most studies, the direction but not the magnitude of the error is known. The major weakness of quantum-chemical descriptors is the failure to directly address bulk effects of a molecule. 

Hur, J. I. N., and Schlautman, M. A. (2003). Using selected operational descriptors to examine the heterogeneity within a bulk humic substance. Environ. Sci. Technol. 37,880-887. 

The descriptor was a product of the correlation weights, CW(Ik), calculated by the Monte Carlo method for each kth element of a special SMILES-like notation introduced by the authors. The notation codes the following characteristics the atom composition, the type of substance (bulk or not, ceramic or not), and the temperature of synthesis. The QSAR model constructed in this way was validated with the use of many different splits into training (n 21) and validation (n=8) sets. Individual sub-models are characterized by high goodness-of-fit (0.972 applicability domain of the model, it is not known if all the compounds (metal oxides, nitrides, mullite, and silicon carbide) can be truly modeled together. 

Equation [1] relates a (macroscopic) bulk, empirical property, Y, with some set, X, of (microscopic) molecular structural parameters (descriptors). The equation as shown is linear in that each term involves a first power for its descriptor. Fligher order descriptors may also be used. The coefficients, Uj, are obtained with the aid of statistical methods, particularly, regression... 

A bulk property, Y, is measured for a set of n compounds leading to a set of values, Y,, 1 < i < . For each of the n compounds, a set of m molecular descriptors, Xj, lcomputational methods. The (m+ 1) arises because of the possibility of a nonzero intercept appearing in a relationship. A minimum of m measurements are required, one for each parameter. The regression coefficients have greater statistical validity if there exist more measurements than coefficients a common rule of thumb is n> 5m (i.e., at least five... 

Because authors present correlation equations in different ways, a uniform pattern of presentation is employed. For each example given, the following information is provided the author(s), the bulk property with its units, the number and types of compounds in the data set, the types of descriptors used, and QM methods employed. Computer programs used in molecular model visualization, QM calculation, descriptor calculation, and statistical calculation will be mentioned. More information on some of the computer programs available for these purposes may be found in two chapters in... 

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