title: Cluster-based molecular docking study for in silico identification of novel 6-fluoroquinolones as potential inhibitors against Mycobacterium tuberculosis.
abstract: A classical protein sequence alignment and homology modeling strategy were used for building three Mycobacterium tuberculosis-DNA gyrase protein models using the available topoII-DNA-6FQ crystal structure complexes originating from different organisms. The recently determined M. tuberculosis-DNA gyrase apoprotein structures and topoII-DNA-6FQ complexes were used for defining the 6-fluoroquinolones (6-FQs) binding pockets. The quality of the generated models was initially validated by docking of the cocrystallized ligands into their binding site, and subsequently by quantitative evaluation of their discriminatory performances (identification of active/inactive 6-FQs) for a set of 145 6-FQs with known biological activity values. The M. tuberculosis-DNA gyrase model with the highest estimated discriminatory power was selected and used afterwards in an additional molecular docking experiment on a mixed combinatorial set of 427 drug-like 6-FQ analogs for which the biological activity values were predicted using a prebuilt counter-propagation artificial neural network model. A novel three-level Boolean-based [T/F (true/false)] clustering algorithm was used to assess the generated binding poses: Level 1 (geometry properties assessment), Level 2 (score-based clustering and selection of the (T)-signed highly scored Level 1 poses), and Level 3 (activity-based clustering and selection of the most "active" (T)-signed Level 2 hits). The frequency analysis of occurrence of the fragments attached at R(1) and R(7) position of the (T)-signed 6-FQs selected in Level 3 revealed several novel attractive fragments and confirmed some previous findings. We believe that this methodology could be successfully used in establishing novel possible structure-activity relationship recommendations in the 6-FQs optimization, which could be of great importance in the current antimycobacterial hit-to-lead processes.
authors.affiliation: National Institute of Chemistry, Hajdrihova 19, 1001 Ljubljana, Slovenia. nikola.minovski@ki.si
authors.forename: Nikola
authors.initials: N
authors.lastname: Minovski
authors.forename: Andrej
authors.initials: A
authors.lastname: Perdih
authors.forename: Marjana
authors.initials: M
authors.lastname: Novic
authors.forename: Tom
authors.initials: T
authors.lastname: Solmajer
mesh_terms: D000465:Algorithms; D000995:Antitubercular Agents / Q000737:chemistry*; D001426:Bacterial Proteins / Q000037:antagonists & inhibitors / Q000737:chemistry*; D001665:Binding Sites; D016000:Cluster Analysis; D027081:DNA Gyrase / Q000737:chemistry*; D015195:Drug Design; D004791:Enzyme Inhibitors / Q000737:chemistry*; D024841:Fluoroquinolones / Q000737:chemistry*; D008024:Ligands; D008968:Molecular Conformation; D062105:Molecular Docking Simulation; D009169:Mycobacterium tuberculosis / Q000737:chemistry* / Q000201:enzymology; D016571:Neural Networks, Computer; D011485:Protein Binding; D013329:Structure-Activity Relationship; D059005:Topoisomerase II Inhibitors
chemical_list: D000995:Antitubercular Agents; D001426:Bacterial Proteins; D004791:Enzyme Inhibitors; D024841:Fluoroquinolones; D008024:Ligands; D059005:Topoisomerase II Inhibitors; D027081:DNA Gyrase