To　investigate　the　mechanism　of　aquatic　pathogens　in　quorum　sensing　(QS)　and　decode　the　signal　transmission　of　aquatic　Gram-negative　pathogens,　this　paper　proposes　a　novel　method　for　the　intelligent　matching　identification　of　eight　quorum　signaling　molecules　(N-acyl-homoserine　lactones,　AHLs)　with　similar　molecular　structures,　using　terahertz　(THz)　spectroscopy　combined　with　molecular　dynamics　simulation　and　spectral　similarity　calculation.　The　THz　fingerprint　absorption　spectral　peaks　of　the　eight　AHLs　were　identified,　attributed,　and　resolved　using　the　density　functional　theory　(DFT)　for　molecular　dynamics　simulation.　To　reduce　the　computational　complexity　of　matching　recognition,　spectra　with　high　peak　matching　values　with　the　target　were　preliminarily　selected,　based　on　the　peak　position　features　of　AHL　samples.　A　comprehensive　similarity　calculation　(CSC)　method　using　a　weighted　improved　Jaccard　similarity　algorithm　(IJS)　and　discrete　Frechet　distance　algorithm　(DFD)　is　proposed　to　calculate　the　similarity　between　the　selected　spectra　and　the　targets,　as　well　as　to　return　the　matching　result　with　the　highest　accuracy.　The　results　show　that　all　AHL　molecular　types　can　be　correctly　identified,　and　the　average　quantization　accuracy　of　CSC　is　98.48%.　This　study　provides　a　theoretical　and　data-supported　foundation　for　the　identification　of　AHLs,　based　on　THz　spectroscopy,　and　offers　a　new　method　for　the　high-throughput　and　automatic　identification　of　AHLs.