Such information is generally scarce, and often complicated by the existence of multiple MOAs per compound. Here, MOAs related to developmental craniofacial malformations were derived from literature, and assembled in a MOA network. A selection of gene expression markers was based on these MOAs. Next, these markers were verified by qPCR in zebrafish embryos, after exposure to reference compounds. These were: triazoles for inhibition of retinoic acid (RA) metabolism, AM580 and CD3254 for selective activation of respectively RA-receptor (RAR) and retinoid-X-receptor (RXR), dithiocarbamates for inhibition of lysyl oxidase, TCDD for activation of the aryl-hydrocarbon-receptor (AhR), VPA for inhibition of histone deacetylase (HDAC), and PFOS for activation of peroxisome proliferator-activated receptor-alpha (PPARα). Next, marker gene profiles for these reference compounds were used to map the profiles of test compounds to known MOAs. In this way, 2,4-dinitrophenol matched with the TCDD and RAR profiles, boric acid with RAR, endosulfan with PFOS, fenpropimorph with dithiocarbamates, PCB126 with AhR, and RA with triazoles and RAR profiles. Prochloraz showed no match. Activities of these compounds in ToxCast assays, and in silico analysis of binding affinity to the respective targets showed limited concordance with the marker gene expression profiles, but still confirmed the complex MOA profiles of reference and test compounds. Ultimately, this approach could be used to support modeling of mixture effects based on upfront knowledge of (dis)similarity of MOAs.