2D topological descriptors

Rum and Herndon, in 1991, used n x n similarity index matrices (n = number of compounds in the data set), derived from 2D topological descriptors, and stepwise regression analysis to correlate several columns of these matrices with biological activities. Good and Richards, in a more systematic investigation, superimposed molecules, as in CoMFA analyses, and compared their 3D electronic similarity. Also from this approach n x n similarity index matrices result which are correlated with biological activities, using either neural networks or PLS analysis. 

Several research groups have built models using theoretical desaiptors calculated only from the molecular structure. This approach has been proven to be particularly successful for the prediction of solubility without the need for descriptors of experimental data. Thus, it is also suitable for virtual data screening and library design. The descriptors include 2D (two-dimensional, or topological) descriptors, and 3D (three-dimensional, or geometric) descriptors, as well as electronic descriptors. 

Norinder and Haeberlein (unpublished results) have developed a model based on the Palm dataset [2] using rapidly computable 2D-based descriptors, among them a number of topological indices, using an in-house AstraZeneca software package called SaSA [35], and with the good quality (Table 16.7). 

Another set of particularly useful 2D-based topological descriptors are the so-called electrotopological state index (E-state) descriptors developed by Kier and Hall [36],... 

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

Figure 6.14 Bar graph comparing the analysis All calculations were performed on a 2.5 GHz capacity, in number of ligands bite angles and desktop computer (analysis capacity will flexibility ranges calculated per hour, using improve with better computers and software, topological descriptors (2D), and 3D descriptors but the 2D/3D cost-effectiveness ratio will based on MM force fields, semi-empirical remain constant).

Descriptors based on the 2D structure or simply on the connectivity matrix of a structure have long been used for chemical similarity and for property correlations. Because they often lack any relationship to mechanism, these descriptors are best used within a congeneric series or at least a set of similar structures. They may be empirically useful for cluster analysis and chemical library design, because they are effective at representing structure differences and similarities. A few programs and providers of topological descriptors include the following ... 

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