A novel, distance-cum-adjacency topological descriptor, termed as eccentric connectiVity index, has been conceptualized, and its discriminating power has been investigated with regard to physical/biological properties of molecules. Correlation coefficients ranging from 95% to 99% were obtained using eccentric connectivity index in various datasets with regard to physical properties of diverse nature. These correlations were far superior to those correspondingly derived from the Wiener index. For structure-activity studies, a dataset, comprised of 94 substituted piperidinyl methyl ester and methylene methyl ester analogs as analgesic agents, was selected. Values of the eccentric connectivity index, the Wiener index, and Randic ´'s molecular connectivity index were calculated, and active ranges were identified. Good correlations between topological descriptors and analgesic activity of these analogs were obtained. Eccentric connectivity index exhibited highest predictibility of the order of 86%. High discriminating power as revealed by excellent correlations obtained from structure-property and structure-activity studies offers an eccentric connectivity index of vast potential in QSPR/QSAR.
Eccentric Connectivity Index: A Novel Highly Discriminating Topological Descriptor for Structure-Property and Structure-Activity Studies -(comparison with Wiener index and Randic's molecular connectivity index). -(SHARMA, V.; GOSWAMI, R.; MADAN, A. K.; J. Chem.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.