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The <i>Streptomyces</i> strain G222, isolated from a Vietnamese marine sediment, was confidently identified by 16<i>S</i> rRNA gene sequencing. Its AcOEt crude extract was successfully analyzed using non-targeted LC-MS/MS analysis, and molecular networking, leading to a putative annotation of its chemical diversity thanks to spectral libraries from GNPS and <i>in silico</i> metabolite structure prediction obtained from SIRIUS combined with the bioinformatics tool conCISE (Consensus Annotation Propagation of <i>in silico</i> Elucidations). This dereplication strategy allowed the identification of an interesting cluster of a series of putative cyclic and linear lipopeptides of the lichenysin and surfactin families. Lichenysins (<b>3</b>–<b>7</b>) were isolated from the sub-fraction, which showed significant anti-biofilm activity against <i>Pseudomonas aeruginosa</i> MUC-N1. Their structures were confirmed by detailed 1D and 2D NMR spectroscopy (COSY, HSQC, HMBC, TOCSY, ROESY) recorded in CD₃OH, and their absolute configurations were determined using the modified Marfey’s method. The isolated lichenysins showed anti-biofilm activity at a minimum concentration of 100 µM. When evaluated for antibacterial activity against a panel of Gram-positive and Gram-negative strains, two isolated lichenysins exhibited selective activity against the MRSA strain without affecting its growth curve and without membranotropic activity. This study highlights the power of the MS/MS spectral similarity strategy using computational methods to obtain a cross-validation of the annotated molecules from the complex metabolic profile of a marine sediment-derived <i>Streptomyces</i> extract. This work provides the first report from a <i>Streptomyces</i> strain of combined cyclic and linear lichenysins and surfactins, known to be characteristic compounds of the genus <i>Bacillus</i>.