Connectivity descriptor

Molecular Connectivity. A class of molecular descriptors derived from the connection table of a structure. For increasing path lengths (1-, 2-, 3-bonds, etc.), the molecular connectivity values are computed as the sum of functions of the connectivity values (number of attachments) of the atoms in the path. Molecular connectivity descriptors can be used to distinguish structures. As such, they can be correlated with physicochemical properties that are functions of structure size, linearity, and degree of branching. 

The widespread use of connectivity descriptors in modeling many molecular properties has been noticeable in the literature since 1975. Some examples of QSAR/ QSPR studies by connectivity descriptors are reported below. 

Diudea, M.V, Minailiuc, O.M. and Katona, G. (19%b). Molecular Topology. 22. Novel Connectivity Descriptors Based on Walk Degrees. Croat.Chem.Acta, 69,857-871. 

Pogliani, L. (1994a). Molecular Connectivity Descriptors of the Physicochemical P roperties of the a-Amino Acids. J.Phys.Chem., 98,1494-1499. 

Pogliani, L. (1999a). Modeling Properties with Higher-Level Molecular Connectivity Descriptors. J.Chem.lnf.Comput.ScL, 39,104-111. 

Randic, M. and Dobrowolski, J.Cz. (1998b). Optimal Molecular Connectivity Descriptors for Nitrogen-Containing Molecules. Int.J.Quant.Chem., 70,1209-1215. 

X values for some substituents are reported in —> connectivity descriptors (Table C6). 

Estrada, E., Delgado, E.J., Alderete, J.B. and Jana, G.A. (2006) Quantum-connectivity descriptors in modeling solubility of environmentally important organic compounds. /. Comput. Chem., 25, 1787-1796. 

Pogliani, L. (1999a) Modeling properties with higher-level molecular connectivity descriptors. /. Chem. Inf. Comput. Sci., 39, 104-111. 

The methods applied in recent years by various groups to construct QSAR models for ART and analogues include docking calculations to heme [104, 105], CoMFA [106-109] and hologram QSAR [108] as well as the hypothetical active-site lattice (HASL) approach [107], self-organizing maps of the molecular electrostatic potential [110], quantum-similarity measures [111] and topological molecular connectivity descriptors [112]. 

The structures were quite diverse, ranging from those with simple alkyl ether attachments, to complex cyclized derivatives. The entire set could not be modeled and analyzed, so to obtain a representative sampling of the compounds, several molecular connectivity descriptors (12) were computed using the ADAPT program... 

Topological parameters were the first molecular descriptors that could be calculated for any chemical structure (other than obvious parameters such as molecular weight, atom counts, etc.) all that was required for their computation was a standard two-dimensional (2-D) representation of a chemical structure. The best known topological parameters are the molecular connectivity indices first described by Randic and investigated extensively by Hall and Kier et al. Molecular connectivity descriptors have since been used by chemists in the construction of QSAR models for many types of biological properties, especially applications in the environmental area. The reason for such heavy application in environmental studies is because these data sets often contain diverse sets of compounds, and as just mentioned, topological descriptors can be computed for any structure. 

Thus, for the first time, it became possible to generate even more descriptors than molecules in a dataset, which gives rise to several problems, as discussed in the next section, but in fact, many simple molecular connectivity descriptors are not so problematic because they contain much colinearity (colinearity between a pair of descriptors means that they are highly correlated) and multicolinearity. These two properties are discussed in more detail later. Fligh correlation between a pair of descriptors implies that they carry the same information. Although much debate has occurred about the physicochemical meaning of molecular connectivity descriptors,little doubt seems to exist that molecular connectivity descriptors contain information related primarily to molecular shape.A principal component (PC) analysis of 108 molecular connectivity descriptors for a set of -alkanes and polychlorinated biphenyls showed " that three principal components account for 98% of the variance in the dataset. These three PCs were associated with ... 

Molecular graph-based descriptors can also be calculated using the cxcalc command. Here, let us compute Randic index [40] and Wiener index [41] which are important molecular connectivity descriptors. Randic index, also called bond index, is the snm of bond contribntions in a molecnle and Wiener path is a topo-logic index describing the shortest path between all pairs of vertices. The syntax of the commands is cxcalc randicindex test ameslOO.smi and cxcalc wienerindex test ameslOO.smi (Fig. 2.6). 

One of the drawbacks with molecular connectivity descriptors is the difficulty in moving back from connectivity values to chemical structure. That is to say, it is difficult to predict a chemical structure which will give a particular value of a coimectivity index. 

A better test for the potential of the variable connectivity descriptors in QSAR is to choose a more difficult case. So we will report on a regression of a set of imid-azolidines with respect to their hypotensive activity. Let us examine the hypotensive activities of 18 methyl and chloro derivatives of 2-(arylimino)imidazolidine. The compounds are illustrated schematically in Figure 6.6. 

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