We introduce here for the first time the RNAMute package, a pattern-recognition-based utility to perform mutational analysis and detect vulnerable spots within an RNA sequence that affect structure. Mutations in these spots may lead to a structural change that directly relates to a change in functionality. Previously, the concept was tried on RNA genetic control elements called “riboswitches” and other known RNA switches, without an organized utility that analyzes all single-point mutations and can be further expanded. The RNAMute package allows a comprehensive categorization, given an RNA sequence that has functional relevance, by exploring the patterns of all single-point mutants. For illustration, we apply the RNAMute package on an RNA transcript for which individual point mutations were shown experimentally to inactivate spectinomycin resistance in Escherichia coli. Functional analysis of mutations on this case study was performed experimentally by creating a library of point mutations using PCR and screening to locate those mutations. With the availability of RNAMute, preanalysis can be performed computationally before conducting an experiment.