title: Structure-activity relationship analysis of 4'-bromo-[1,1'-biphenyl]-4-yl 4-X-phenyl methanone derivatives and activity against Mycobacterium tuberculosis.
abstract: 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 biphenyl-phenyl methanone derivatives against Mycobacterium tuberculosis in vitro. Both PCA and ANN were able to classify these derivatives in two categories: low active and highly active compounds. Empirical and theoretical descriptors were used in the classification process. The descriptors selected by PCA indicated that the reactivity plays an important role in the determination of antimycobacterial activity of biphenylphenyl methanone derivatives (BPM). The BPM showed a moderate activity against the M. tuberculosis strain tested with the exception of chloride-, bromide- and nitroderivatives (when X = Cl, Br, NO2) which were the most actives against M. tuberculosis in vitro among all the methanones studied.
authors.affiliation: Instituto de Química, Universidade Estadual de Campinas, S. P., Brazil.
authors.forename: A O
authors.initials: AO
authors.lastname: de Souza
authors.forename: J B
authors.initials: JB
authors.lastname: Alderete
authors.forename: F
authors.initials: F
authors.lastname: Schimidt
authors.forename: D N
authors.initials: DN
authors.lastname: Sato
authors.forename: N
authors.initials: N
authors.lastname: Durán
mesh_terms: D000995:Antitubercular Agents / Q000138:chemical synthesis* / Q000494:pharmacology; D001713:Biphenyl Compounds / Q000138:chemical synthesis* / Q000494:pharmacology; D008826:Microbial Sensitivity Tests; D008968:Molecular Conformation; D009169:Mycobacterium tuberculosis / Q000187:drug effects*; D016571:Neural Networks, Computer; D013329:Structure-Activity Relationship
chemical_list: D000995:Antitubercular Agents; D001713:Biphenyl Compounds