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Abstract Background Growing concern about the emergence of antibiotic resistance is compelling the pharmaceutical industry to search for new antimicrobial agents. The availability of genome sequences has enabled the development of computational mining as an important tool in the discovery of natural products with antibiotic effect. Results NRPPUR (Non-Ribosomal Peptide and Polyketide Urmite) is a new bioinformatic tool that was created to detect polyketides and non-ribosomal peptide gene clusters (PKS and NRPS) in bacterial genomes using the rpsBlast program. The NRPPUR database was constructed locally by assembling all 3505 available sequences of NRPS-PKS that have been identified by in silico approaches to date, with 164 Biosynthetic Gene Clusters (BGCs) derived from the published literature that have demonstrated antimicrobial activity in vitro. The in silico analysis of 49 intestinal human bacterial genomes using the NRPPUR made it possible to identify 91 BGCs including 89 clusters that had never previously been described. On average, intestinal human bacterial genomes devote nearly 0.8% (±1.4% s.d.) of their genome to NRPS/PKS biosynthesis, with Bacillus vallismortis, Streptomyces massiliensis and Bacillus subtilis genomes apportioning 8.4, 3.6 and 3.15% of their genomes, respectively. When using the cross-streak method, S. massiliensis displayed antibacterial activity against many Gram-positive and negative bacteria including methicillin-resistant Staphylococcus aureus (MRSA). Conclusions NRPPUR has proven to be a very useful tool for the primary in silico selection of species with potential antimicrobial activity and human microbiota could be the future source of new antimicrobial discoveries. Further exploration of this and other ecological niches, coupled with high-throughput antibacterial activity screening should be envisaged.