17β-Hydroxysteroid dehydrogenase type 1 (17β-HSD1) catalyzes the reduction of estrone to estradiol, which is the most potent estrogen in humans. Inhibition of 17β-HSD1 and thereby reducing the intracellular estradiol concentration is thus a promising approach for the treatment of estrogen dependent diseases. In the past, several steroidal and non-steroidal inhibitors of 17β-HSD1 have been described but so far there is no cocrystal structure of the latter in complex with 17β-HSD1. However, a distinct knowledge of active site topologies and protein-ligand interactions is a prerequisite for structure-based drug design and optimization. An elegant strategy to enhance this knowledge is to compare inhibition values obtained for one compound toward ortholog proteins from various species, which are highly conserved in sequence and differ only in few residues. In this study the inhibitory potencies of selected members of different non-steroidal inhibitor classes toward marmoset 17β-HSD1 were determined and the data were compared with the values obtained for the human enzyme. A species specific inhibition profile was observed in the class of the (hydroxyphenyl)naphthols. Using a combination of computational methods, including homology modelling, molecular docking, MD simulation, and binding energy calculation, a reasonable model of the three-dimensional structure of marmoset 17β-HSD1 was developed and inhibition data were rationalized on the structural basis. In marmoset 17β-HSD1, residues 190 to 196 form a small α-helix, which induces conformational changes compared to the human enzyme. The docking poses suggest these conformational changes as determinants for species specificity and energy decomposition analysis highlighted the outstanding role of Asn152 as interaction partner for inhibitor binding. In summary, this strategy of comparing the biological activities of inhibitors toward highly conserved ortholog proteins might be an alternative to laborious x-ray or site-directed mutagenesis experiments in certain cases. Additionally, it facilitates inhibitor design and optimization by offering new information on protein-ligand interactions.