Property-based descriptor

The results suggested that the property-based descriptors are the most efficient, as they predicted new molecules as well or better than the other two families, and involve fewer descriptors than the topological descriptor family. 

Property-based descriptors, lipophilicity, molecular flexibility, PSA, and number of hydrogen-bond donors are the main parameters influencing the BBB permeability of compounds. 

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. 

A particularly good selection of physical properties may be spectra, because they are known to depend strongly on the chemical structure. In fact, different types of spectra carry different kinds of structural information, NMR spectra characterize individual carbon atoms in their molecular environment. They therefore correspond quite closely to fragment-based descriptors, as underlined by the success of approaches to predict NMR spectra by fragment codes (see Section 10.2.3). 

Raevsky, 0. A. Physicochemical descriptors in property-based drug design. Minirev. Med. Chem. 2004, 4, 1041-1052. 

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. 

BB. Most molecule-based descriptors, such as logP, PSA, and molecular electronic properties, were used to construct models with a variety of statistical tools. The best performing models can approach the limit of experimental error, which was estimated to be 0.3 log units. 

A polar surface area approximation can be calculated by summing the V, contribution of each polar atom in a molecule. A hydrophobic surface area approximation can be calculated by V) contribution of each hydrophobic atom in a molecule. More generally, for a given binary property Bt (such as is polar or is aromatic or is acceptor ) for each atom i in a molecule, an approximate surface-area based descriptor can be calculated with... 

ADMET Predictor Constitutional, functional group counts, topological, E-state, Moriguchi descriptors, Meylan flags, molecular patterns, electronic properties, 3D descriptors, hydrogen bonding, acid-base ionization, empirical estimates of quantum descriptors 297... 

Constitutional, property-based, 2D topologi- 1,084 cal, and 3D conformational descriptors... 

Modified QCMs GCM schemes often consider extra contributions. These contributions can be physicochemical properties, molecular descriptors, and various correction factors. For example, to estimate the critical temperature, Tc, the input of the normal boiling point, Tb, is required by certain GCMs [33]. In this case a typical approach is based on the modification of eq. 1.6.3 as follows ... 

Many different structural descriptors have been developed for similarity searching in chemical databases [4] including 2D fragment based descriptors, 3D descriptors, and descriptors that are based on the physical properties of molecules. More recently, attention has focused on diversity studies and many of the descriptors applied in similarity searching are now being applied in diversity studies. Structural descriptors are basically numerical representations of structures that allow pairwise (dis)similarities between structures to be measured through the use of similarity coefficients. Many diversity metrics have been devised that are based on calculating structural (dis)similarities, some of these are described below. 

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