Drug discovery is usually focused on a single protein target; in this process, existing compounds that bind to related proteins are often ignored. We describe ProBiS plugin, extension of our earlier ProBiSi-ligands approach, which for a given protein structure allows prediction of its binding:sites and, for each binding site, the ligands from similar binding sites in the Protein Data Bank. We developed a new database of precalculated binding site comparisons of about 290000 proteins to allow fast prediction of binding sites in existing proteins. The plugin enables advanced viewing of predicted binding sites, ligands' poses, and their interactions in three-dimensional graphics. Using the InhA query protein, an enoyl reductase enzyme in the Mycobacterium tuberculosis fatty acid biosynthesis pathway, we predicted its possible ligands and assessed their inhibitory activity experimentally. This resulted in three previously unrecognized inhibitors with novel scaffolds, demonstrating the plugin's utility in the early drug discovery process.