Abstract

Substructural molecular fragments (SMF) method [Solov'ev, V. P.; Varnek, A.; Wipff, G. J. Chem. Inf. Comput. Sci. 2000, 40, 847-858] was applied to assess anti-HIV activity for large data sets for three families of compounds: 1-[2-hydroxyethoxy)methyl]-6-(phenylthio)thymine (HEPT) derivatives, tetrahydroimidazobenzodiazepinone (TIBO) derivatives, and cyclic urea (CU) derivatives. The SMF method uses 49 types of topological descriptors (atom/bond sequences and augmented atoms) which, being coupled with 3 linear and nonlinear fitting equations, allows the user to generate up to 147 structure-property models. For each family of compounds, the modeling was performed on several training sets followed by the validation calculations where three best fit models were applied. Calculated activities well reproduce available experimental data. On the basis of the optimal molecular fragments, the focused combinatorial library containing 252 virtual HEPT derivatives has been generated. Its filtering led to several hits potentially possessing anti-HIV activity.

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