Tuberculosis (TB) is one of the top 10 causes of death worldwide. This scenario is further complicated by the insurgence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB. The identification of appropriate drugs with multi-target affinity profiles is considered to be a widely accepted strategy to overcome the rapid development of resistance. The aim of this study was to discover Food and Drug Administration (FDA)-approved drugs possessing antimycobacterial activity, potentially coupled to an effective multi-target profile. An integrated screening platform was implemented based on computational procedures (high-throughput docking techniques on the target enzymes peptide deformylase and Zmp1) and in vitro phenotypic screening assays using two models to evaluate the activity of the selected drugs against Mycobacterium tuberculosis (Mtb), namely, growth of Mtb H37Rv and of two clinical isolates in axenic media, and infection of peripheral blood mononuclear cells with Mtb. Starting from over 3000 FDA-approved drugs, we selected 29 marketed drugs for submission to biological evaluation. Out of 29 drugs selected, 20 showed antimycobacterial activity. Further characterization suggested that five drugs possessed promising profiles for further studies. Following a repurposing strategy, by combining computational and biological efforts, we identified marketed drugs with relevant antimycobacterial profiles.