Target class profiling (TCP) is a chemical biology approach to investigate understudied biological target classes. TCP is achieved by developing a generalizable assay platform and screening curated compound libraries to interrogate the chemical biological space of members of an enzyme family. In this work, we took a TCP approach to investigate inhibitory activity across a set of small-molecule methyltransferases (SMMTases), a subclass of methyltransferase enzymes, with the goal of creating a launchpad to explore this largely understudied target class. Using the representative enzymes nicotinamide N-methyltransferase (NNMT), phenylethanolamine N-methyltransferase (PNMT), histamine N-methyltransferase (HNMT), glycine N-methyltransferase (GNMT), catechol O-methyltransferase (COMT), and guanidinoacetate N-methyltransferase (GAMT), we optimized high-throughput screening (HTS)-amenable assays to screen 27,574 unique small molecules against all targets. From this data set, we identified a novel inhibitor which selectively inhibits the SMMTase HNMT and demonstrated how this platform approach can be leveraged for a targeted drug discovery campaign using the example of HNMT.