SciELO - Scientific Electronic Library Online

 
vol.94 número1-3A preliminary theoretical study of antiepileptic drugsComplexation of Zn(II) by catechol in hydroxylic solvents índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

  • Não possue artigos citadosCitado por SciELO

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Anales de la Asociación Química Argentina

versão impressa ISSN 0365-0375

Resumo

TALEVI, A.; CASTRO, E. A.  e  BRUNO-BLANCH, L.E.. New solubility models based on descriptors derived from the Detour Matrix. An. Asoc. Quím. Argent. [online]. 2006, vol.94, n.1-3, pp.129-141. ISSN 0365-0375.

New molecular descriptors were derived from already-known descriptors obtained from the Detour Matrix (also known as Maximal Topological Distance Matrix or Maximum Path Matrix) and applied to the prediction of aqueous solubility of 46 structurally heterogeneous compounds, constructing one-variable models through linear regression. The correlation coefficients between these descriptors and the experimental values of solubility were compared to those obtained with more than 1,600 widely-used descriptors included in commercial software Dragon, confirming the very good performance of the proposed descriptors. The best-performance descriptors were then applied, in combination with Dragon's descriptors, to generate two five-variable models for the estimation of solubility. The F-Statistical and the p-value for this models confirmed high statistical significance. We also present the distribution of molecular weights, solubility values, number of H donors, number of H acceptors and number of heteroatoms for the 46 compounds employed, which show molecular diversity. The results indicate that the proposed descriptors can be applied in QSAR and QSPR studies.

        · resumo em Espanhol     · texto em Inglês

 

Creative Commons License Todo o conteúdo deste periódico, exceto onde está identificado, está licenciado sob uma Licença Creative Commons