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  • Quantitative structure-activity relationship study of antitubercular fluoroquinolones
    Minovski, Nikola ; Vračko, Marjan ; Šolmajer, Tomaž
    Quantitative structure-activity relationship study on three diverse sets of structurally similar fluoroquinolones was performed using a comprehensive set of molecular descriptors. Multiple linear ... regression technique was applied as a preprocessing tool to find the set of relevant descriptors (10) which are subsequently used in the artificial neural networks approach (non-linear procedure). The biological activity in the series (minimal inhibitory concentration ([mu]g/mL) was treated as negative decade logarithm, [rho]MIC). Using the non-linear technique counter propagation artificial neural networks, we obtained good predictive models. All models were validated using cross validation leave-one-out procedure. The results (the best models: Assay1, R = 0.8108; Assay2, R = 0.8454, and Assay3, R = 0.9212) obtained on external, previously excluded test datasets show the ability of these models in providing structure-activity relationship of fluoroquinolones. Thus, we demonstrated the advantage of non-linear approach in prediction of biological activity in these series. Furthermore, these validated models could be proficiently used for the design of novel structurally similar fluoroquinoloneanalogues with potentially higher activity.
    Vir: Molecular diversity. - ISSN 1381-1991 (Vol. 15, no. 2, 2011, str. 417-426)
    Vrsta gradiva - članek, sestavni del
    Leto - 2011
    Jezik - angleški
    COBISS.SI-ID - 4355354
    DOI

vir: Molecular diversity. - ISSN 1381-1991 (Vol. 15, no. 2, 2011, str. 417-426)
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