We have developed methods for studying the interactions between small molecules and RNA and have applied them to characterize the binding of three classes of aminoglycoside antibiotics to ribosomal RNA subdomains. High-resolution MS was used to quantitatively identify the noncovalent binding interactions between mixtures of aminoglycosides and multiple RNA targets simultaneously. Signal overlap among RNA targets was avoided by the addition of neutral mass tags that direct each RNA target to a unique region of the spectrum. In addition to determining binding affinities, the locations of the binding sites on the RNAs were identified from a protection pattern generated by fragmenting the aminoglycoside/RNA complex. Specific complexes were observed for the prokaryotic rRNA A-site subdomain with ribostamycin, paromomycin, and lividomycin, whereas apramycin preferentially formed a complex with the eukaryotic subdomain. We show that differences in binding between paromomycin and ribostamycin can be probed by using an MS-MS protection assay. We have introduced specific base substitutions in the RNA models and have measured their impact on binding affinity and selectivity. The binding of apramycin to the prokaryotic subdomain strongly depends on the identity of position 1408, as evidenced by the selective increase in affinity for an A1408G mutant. An A1409-G1491 mismatch pair in the prokaryotic subdomain enhanced the binding of tobramycin and bekanamycin. These observations demonstrate the power of MS-based methods to provide molecular insights into small molecule/RNA interactions useful in the design of selective new antimicrobial drugs.