Structure-activity relationship analysis of 4 '-bromo-[1,1 '-biphenyl]-4-yl 4-X-phenyl methanone derivatives and activity against Mycobacterium tuberculosis

Principal Component Analysis (PCA) and Artificial Neural Network (ANN) were used to analyze the relationship between the structure and the activities of a series of nine biphenylphenyl methanone derivatives against Mycobacter ium tuberculosis in vitro. Both PCA and ANN were able to classify these der ivatives in two categories: low active and highly active compounds. Empiric al and theoretical descriptors were used in the classification process. The descriptors selected by PCA indicated that the reactivity plays an importa nt role in the determination of antimycobacterial activity of biphenylpheny l methanone derivatives (BPM). The BPM showed a moderate activity against t he M. tuberculosis strain tested with the exception of chloride-, bromide- and nitroderivatives (when X = Cl, Br, NO2) which were the most actives aga inst M. tuberculosis in vitro among all the methanones studied.