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Use of Linear Retention Indices in GC-MS Libraries for Essential Oil Analysis
Published in K. Hüsnü Can Başer, Gerhard Buchbauer, Handbook of Essential Oils, 2020
Emanuela Trovato, Giuseppe Micalizzi, Paola Dugo, Margita Utczás, Luigi Mondello
A further index system, the molecular topological index, proposed by Balaban (1982), has been shown to be a very important structural parameter for describing the chromatographic behavior of a compound. Heinzen and Yunes investigated the determination of molecular topological indices and their correlation with retention indices of linear alkylbenzene isomers with C10 to C14 linear alkyl chains (Heinzen and Yunes, 1996).
The application of molecular topology for ulcerative colitis drug discovery
Published in Expert Opinion on Drug Discovery, 2018
Carolina L. Bellera, Mauricio E. Di Ianni, Alan Talevi
At the core of the chemical graph theory lies the adjacency matrix. From a hydrogen-suppressed molecular representation, a N × N symmetric matrix can be obtained whose elements Aij equal 1 if vertices i and j are directly connected through a covalent chemical bond, and 0 otherwise. The sum of all entries in the ith row or the jth column provides the degree or topological valence δ of vertex i or j, respectively. Professor Milan Randić defined the first connectivity index (now known as Randić index) back in 1975 [49]. It was defined as the sum of the degrees of the two vertices adjacent to each edge, extended to all edges of the graph. Another very relevant topological matrix is the distance matrix, whose elements Dij equal the number of edges joining two vertices i and j by the shortest path, provided that i and j are different, or 0 otherwise. The first topological index ever defined, the Wiener index, equals one half of the sum of all entries in the distance matrix [50]. These two examples (the simpler at hand, illustrated in Figure 3) depict the general procedure to obtain topological descriptors. It is interesting to note that the numbering of the vertices of the graph does not influence the value of the graph-derived descriptors: they are graph invariants. In principle, the molecular graph is not influenced by any deformation introduced to the molecule: topological indices are conformation-independent unless deliberately pursued otherwise. Reproducibility and ease of calculation are thus two of the important (and interrelated) virtues of topological descriptors. No conformational analysis, no geometry optimization, no orientation, or conformation-related decisions are required to compute topological descriptor. The modeler is released from the burden of answering the difficult question ‘What conformation should be used to compute a molecular descriptor?’, and from the noise that defining a conformer could introduce to the QSAR model [51,52]. Note that the former question is particularly difficult to answer if, in the frame of a VS campaign, one pretends to apply a QSAR model to a large chemical database. At the other side of the coin, the values of the topological descriptors are usually insensitive to space or even geometry isomers, with some very specific exceptions (see, for instance, [53]).