Leprosy is an ancient disease and the focus of the researchers' scrutiny for more than a century. However, many of the molecular aspects related to transmission, virulence, antigens and immune responses are far from known. Initially, the implementation of recombinant DNA library screens raised interesting antigen candidates. Finally, the availability of Mycobacterium leprae genomic information showed an intriguing genome reduction which is now largely used in comparative genomics. While predictive in silico tools are commonly used to identify possible antigens, proteomic approaches have not yet been explored fully to study M. leprae biology. Quantitative information obtained at the protein level, and its analysis as part of a complex system, would be a key feature to be used to help researchers to validate and understand many of such in silico predictions. Through a re-analysis of data from a previous publication of our group, we could easily tackle many questions regarding antigen prediction and pseudogene expression. Several well known antigens are among the quantitatively dominant proteins, while several major proteins have not been explored as antigens. We argue that combining proteomic approaches together with bioinformatic workflows is a required step in the characterization of important pathogens.