Descriptor-Based Approaches

Despite of successes of the supermolecular approach in the H-bond strength prediction, it has the following limitations. The approach is quite expensive and for realistic pharmaceutical systems it would require sampling of different binding conformations of the supermolecular complex. Therefore, simplified cheaper approaches, which are based on a correlation of certain molecular descriptor or descriptors combination with the experimental (or supermolecular derived) H-bonding strength, are attractive. 

Historically, multiple theoretical descriptor-based approaches to H-bond strength ranking were proposed. That includes approaches based on group contribution method [46], electrostatic potentials [47], electrophilic superdelocalizability and self-atom polarizability [48], Quantum Theory of Atoms In Molecules (QTAIM) descriptors [49-51], the two-center shared electron number a and the product of ionization potential [45, 52], and local quantum mechanical molecular parameters, which quantify electrostatic, polarizability, and charge transfer contributions to H-bonding [53, 54], 

An alternative approach [24, 55, 56] of H-bonding ranking is based on COSMO-RS fluid thermodynamics theory [57], Abramov [24, 58] performed a study of the correlation of two independent schemes of atomic charge calculations (polarization a H-bonding charges and electrostatic potential (ESP) fitted charges, with Abraham s experimental H-bonding scales and available 

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Assessing the diversity of various compound classes has been challenging. A number of descriptor-based approaches have been applied to assess the diversity of various libraries and compared with existing drugs. 

We now introduce a new informatics tool called Shape Signatures that shows promise for drug discovery and computational toxicology. In contrast to QSAR and other descriptor-based approaches that compute hundreds of discrete descriptors for each molecule, the Shape Signature can be viewed as a very compact descriptor that encodes molecular shape and electrostatics in a single entity [76-78]. 

In general, both supermolecular and descriptor-based approaches, discussed earlier, could be applied to the study of H-bonding strength in a crystalline solid state. An advantage of the latter approaches is that they typically do not require actual crystal structure information to rank propensities of the H-bonding interactions in the solid state. This consideration makes descriptor-based approaches the most appropriate for... 

A major potential drawback with cluster analysis and dissimilarity-based methods f selecting diverse compounds is that there is no easy way to quantify how completel one has filled the available chemical space or to identify whether there are any hole This is a key advantage of the partition-based approaches (also known, as cell-bas( methods). A number of axes are defined, each corresponding to a descriptor or son combination of descriptors. Each axis is divided into a number of bins. If there are axes and each is divided into b bins then the number of cells in the multidimension space so created is ... 

The importance of methods to predict log P from chemical structure was described in Chapter 14, which is focused on fragment- and atom-based approaches. In this chapter property-based approaches are reviewed, which comprise two main categories (i) methods that use three-dimensional (3D) structure representation and (ii) methods that are based on topological descriptors. 

Apart from pharmacophore-based approaches, a variety of methods were applied to decipher important ligand features of PXR activation. VolSurf descriptor-based partial least squares (PLS) regression-based models pointed toward amide responsive regions that implicated good acceptor abilities as key variables [33]. 

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 fourth approach is to seek reported experimental data for substances similar in chemical class or structure to the substance of interest exploiting the data base listed earlier and develop a simple structure property relationship for this specific class, using molecular weight volume as a descriptor. This approach is likely to be fairly accurate, provided the original data are accurate. 

Spatial autocorrelation is a quantitative measure of the probability of finding objects of defined properties within a distance of interest [9, 10]. The concept of autocorrelation is mainly applied in fields such as geography, economics, ecology or meteorology to describe the spatial distribution of features. The idea of a molecular descriptor based on the autocorrelation concept was first introduced into the field of cheminformatics by Moreau and Broto in 1980 [11] with the ATS (autocorrelation of a topological structure) descriptor. For this approach, the atoms of a molecule were represented by properties such as atomic mass or partial charge. The distance between atoms was measured as the number of bonds between the respective atoms (topological distance). 

In addition to cell-based partitioning, statistical partitioning methods are widely used for compound classification. One of the most popular approaches is recursive partitioning (Rusinko et al. 1999), a decision tree method, as illustrated in Figure 1.8. Recursive partitioning divides data sets along decision trees formed by sequences of molecular descriptors. At each node of the tree, a descriptor-based decision is made and the molecular data set is subdivided. For example, a chosen descriptor could simply detect the presence or absence of a structural fragment in a molecule. Alternatively, the... 

Recently, an entropy-based approach has been introduced to compare the intrinsic and extrinsic variability of different descriptors, independent of their units and value ranges. The method was originally introduced in communication theory and is based on Shannon entropy, which calculates descriptor-entropy values using histogram representations. Shannon entropy is defined as ... 

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