Background: Tuberculosis (Mycobacterium tuberculosis) is an infectious bacterial disease with
the highest levels of mortality worldwide, presenting numerous cases of resistance. In silico studies, which
elaborate chemical and biological models in computational tools and make it possible to interpret
molecular characteristics, are among the methods used in the search for new drugs.
Objective: In this perspective, our aim was to use QSAR and molecular modeling to propose possible
pharmacophores from benzothiazinone derivatives.
Methods: In this study, a set of 69 benzothiazinone derivatives, together with computational tools such as
molecular descriptor analysis in chemometrics, metabolic prediction, and molecular coupling to 4
proteins: DprE1, InhA, PS, and DHFR important for the bacillus were investigated.
Results: The chemometric model computed in the Volsurf+ program presented good predictive values for
both amphiphilicity and molecular volume. These are essential for biological activity. Metabolites from
the cytochrome isoforms CYP3A4 and 2D6 interactions revealed coupling divergences which, noting that
the metabolites did not present changes to the QSAR proposed pharmacophore structures, may be due to
the reaction medium and existing differences in the benzothiazinone structures. Similarly, molecular
docking with the four TB enzymes presented good interactions for the more active compounds. The
fragments found using QSAR (being essential for biological activity) also presented as being essential for
ligand-protein site interactions.
Conclusion: From the benzothiazinone derivative series evaluated, compound 11026134 presented the
best profile in all study analyses, noting that the trifluoromethyl, nitro group, and piperazine fragment with
aliphatic hydrocarbon groups are likely pharmacophores for the benzothiazinones studied.