Molecular descriptors types

Commonly used molecular descriptor types are listed. For each category, one or two representative examples are given. Dimensionality refers to the molecular representation (molecular formula, 2D drawing, or 3D conformation) from which the descriptors are calculated (adapted from ref. 4). 

Table 8-1. Classification of molecular descriptors by descriptor s data type.

Calculated molecular descriptors including H-bond parameters were used for QSAR studies on different types of permeabiUty. For example, the new H-bond descriptor characterizing the total H-bond ability of a compound, was successfully appUed to model Caco-2 cell permeability of 17 drugs [30]. A similar study on human jejunal in vivo permeabiUty of 22 structurally diverse compounds is described in Ref. [62]. An exceUent one-parameter correlation of human red ceU basal permeabiUty (BP) was obtained using the H-bond donor strength [63] ... 

Linear representations are by far the most frequently used descriptor type. Apart from the already mentioned structural keys and hashed fingerprints, other types of information are stored. For example, the topological distance between pharmacophoric points can be stored [179, 180], auto- and cross-correlation vectors over 2-D or 3-D information can be created [185, 186], or so-called BCUT [187] values can be extracted from an eigenvalue analysis of the molecular adjacency matrix. 

Since the definition of chemical reference spaces very much depends on the choice of molecular descriptors, we begin the description with a brief overview of some commonly used types of descriptors, as summarized in Table 1. 

The table shows a number of representative descriptor types (there are many more) that can be used to define chemical spaces. Each descriptor adds a dimension (with discrete or continuous value ranges) to the chemical space representation (e.g., selection of 18 descriptors defines an 18-dimensional space). Axes of chemical space are orthogonal only if the applied molecular descriptors are uncorrelated (which is, in practice, hardly ever the case). 

A brief overview of different types of molecular descriptors is given in Chapter 9 about cell-based partitioning by Xue et al. this chapter also includes a description of genetic algorithm calculations. 

There are literally thousands of molecular descriptors available for various applications. We have only mentioned a few of them in previous paragraphs. Interested readers can find a more complete coverage of molecular descriptors in reference (15), which gives definitions for 3,300 molecular descriptors. Many software, or subroutines as an integral part of other programs, are available to generate various types of molecular descriptors. Table 2.2 lists a few of these software. 

Molecular descriptors derived solely from D, E, B, and R discriminate between different basic graphs. They do not, however, differentiate between molecules such as I, II, and III with the same basic graph but with differences in their types of atoms, bonds, or stereo- and quantum-chemical features. In the remaining part of this section, a few approaches that extend basic graph descriptors to chemically informed descriptors are introduced. 

The o scale was developed to incorporate the effect of through-resonance. Both types of correlations included ortho- as well as meta- and para-substituted phenoxides, and the only outliers are compounds that exhibit strong intramolecular hydrogen bonding because this effect is not incorporated in most molecular descriptors. The rate constants for oxidation of phenoxide anions give good Hammett correlations to cr constants, as shown in the following equation ... 

Table 2.5 defines the 40 molecular descriptors and provides their values. Figure 2.1 provides further definition of the different types of molecular fragments used while Figure 2.2 provides further definition of the hydrogen bonding and biphenyl ring corrections. Simamora and Yalkowsky (1994) consider the values in parentheses in Table 2.5 insignificant, based on the statistical analysis used to derive the molecular descriptor values. 

Quantitative structure/activity relationships (QSARs) for hydrolysis are based on the application of linear free energy relationships (LFERs) (Well, 1968). An LFER is an empirical correlation between the standard free energy of reaction (AG0), or activation energy (Ea) for a series of compounds undergoing the same type of reaction by the same mechanism, and the reaction rate constant. The rate constants vary in a way that molecular descriptors can correlate. 

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