Bacicyclin is a 6-mer N-to-C cyclic peptide isolated from Bacillus sp. associated with the blue mussel (Mytilus edulis). The peptide exhibits activity against Enterococcus faecalis and Staphylococcus aureus. The iAMPpred prediction server was used to screen the linear counterpart of bacicyclin to identify six prospective antimicrobial analogs. The peptides were then synthesized via solid-phase peptide synthesis (SPPS) using Fmoc chemistry and hexafluorophosphate azabenzotriazole tetramethyl uronium (HATU)/1-hydroxy-7-azabenzotriazole (HOAt) as coupling agents, achieving yields of ∼80%, and characterized by time of flight-electrospray ionization-mass spectrometry (TOF-ESI-MS), nuclear magnetic resonance (1H-NMR, and 13C-NMR). Antimicrobial activity was evaluated against Escherichia coli, Salmonella typhimurium, Staphylococcus aureus, Staphylococcus epidermidis, and Candida albicans. The peptide, An-Bas-2 (FKIVLG), showed significant activity, particularly against Gram-positive bacteria and fungi. Molecular dynamic simulations revealed that An-Bas-2 interacts more strongly with the Gram-positive bacterial membrane compared to linear bacicyclin. While iAMPpred predictions provided valuable insights for initial peptide selection, experimental results revealed discrepancies likely influenced by factors such as peptide degradation, aggregation, and interactions with bacterial membrane components. These findings highlight the critical role of amino acid composition in antimicrobial activity and the importance of integrating experimental and dynamical factors into computational models for designing antimicrobial peptides (AMPs). This study provides valuable insights into the design of AMPs for combating Gram-positive bacterial infections by integrating prediction tools, experimental validation, and molecular dynamics to evaluate peptide interactions with membrane models.