Topological models for prediction of adductability of substituted cyclic organic compounds in urea

Abstract

The relationship of urea adductability of substituted cyclic organic compounds with topological descriptors has been investigated. Wiener’s index—a distance-based topological descriptor, molecular connectivity index—an adjacency-based topological descriptor and eccentric connectivity index—an adjacency-cum-distance based topological descriptor were employed for the present study. A data set comprising of 45 cyclic organic compounds was utilized. The values of all the three topological indices for every compound involved in the data set were computed using in-house computer program. The resultant data was analyzed and suitable models were developed after identification of adductible ranges. Subsequently, each compound in the data set was classified using these models either as urea adductible or non-adductible, which was then compared with the reported adductability in urea. Accuracy of prediction was found to vary from a minimum of 90% for a model based upon eccentric connectivity index to a maximum of 92% for model based upon Wiener’s index. Statistical analysis revealed the selected topological indices to be weakly or appreciably intercorrelated for the said data set.