Tuberculosis (TB) remains one of the leading infectious disease killers in the world. The ongoing development of novel anti-TB medications has yielded potent compounds that often target single sites with well-defined mechanisms of action. However, despite the identification of resistance-associated mutations through target deconvolution studies, comparing these findings with the diverse Mycobacterium tuberculosis populations observed in clinical settings is often challenging. To address this gap, we constructed an open-access database encompassing genetic variations from > 50,000 clinical isolates, spanning the entirety of the M. tuberculosis protein-encoding genome. This resource offers a valuable tool for investigating the prevalence of target-based resistance mutations in any drug target within clinical contexts. To demonstrate the practical application of this dataset in drug discovery, we focused on drug targets currently undergoing phase II clinical trials. By juxtaposing genetic variations of these targets with resistance mutations derived from laboratory-adapted strains, we identified multiple positions across three targets harbouring resistance-associated mutations already present in clinical isolates. Furthermore, our analysis revealed a discernible correlation between genetic diversity within each protein and their predicted essentiality. This meta-analysis, openly accessible via a dedicated dashboard, enables comprehensive exploration of genetic diversity pertaining to any drug target or resistance determinant in M. tuberculosis.