Highly discriminating distance-based topological index

A new topological indexJ (based on distance sumss_i as graph invariants) is proposed. For unsaturated or aromatic compounds, fractional bond orders are used in calculatings_i. The degeneracy ofJ is lowest among all single topological indices described so far. The asymptotic behaviour ofJ is discussed, e.g. whenn → ∞ in C_nH_{2n = 2},Jar π for linear alkanes, andJ → ∞ for highly branched ones.     

Augmented Zagreb index

Inspired by recent work on the atom-bond connectivity (ABC) index we propose here a new topological index, augmented Zagreb index (AZI). The tight upper and lower bounds for chemical trees are obtained. Moreover, it has been shown that among all trees the star has the minimum AZI value. Characterizing trees with maximal augmented Zagreb index remains an open problem for future research.     

Synthesis,antimicrobial, anticancer,antiviral evaluation and QSAR studies of 4-(1-aryl-2-oxo-1,2-dihydro-indol-3-ylideneamino)-N-substituted benzene sulfonamides

A series of 4-(1-aryl-2-oxo-1,2-dihydro-indol-3-ylideneamino)-N-substituted benzenesulfonamide derivatives (1–32) was synthesized and evaluated for its in vitro antimicrobial, antiviral and cytotoxic activities. Antimicrobial results indicated that compounds (11) and (18) were found to be the most effective ones. In general, the synthesized compounds were bacteriostatic and fungistatic in their action. The cytotoxic screening results indicated that the compounds were less active than the standard drug 5-fluorouracil (5-FU). None of the compounds inhibited viral replication at subtoxic concentrations. In general, the presence of a pyrimidine ring with electron releasing groups and an ortho- and para-substituted benzoyl moiety favored antimicrobial activities. The results of QSAR studies demonstrated the importance of topological parameters, valence zero order molecular connectivity index (⁰χ^v) and valence first order molecular connectivity index (¹χ^v) in describing the antimicrobial activity of synthesized compounds.     

The study of the relationship between the new topological index A(m) and the gas chromatographic retention indices of hydrocarbons by artificial neural networks

The newly developed topological indices A_m1-A_m3 and the molecular connectivity indices ^mX were applied to multivariate analysis in structure-property correlation studies. The topological indices calculated from the chemical structures of some hydrocarbons were used to represent the molecular structures. The prediction of the retention indices of the hydrocarbons on three different kinds of stationary phase in gas chromatography can be achieved applying artificial neural networks and multiple linear regression models. The results from the artificial neural networks approach were compared with those of multiple linear regression models. It is shown that the predictive ability of artificial neural networks is superior to that of multiple linear regression method under the experimental conditions in this paper. Both the topological indices ²X and A_m1 can improve the predicted results of the retention indices of the hydrocarbons on the stationary phase studied.