Identification and bioinformatics study of antibacterial peptides from symbiotic bacteria associated with macroalgae sargassum sp

Abstract

This study aims to identify fragment peptides isolation from symbiotic bacteria associated with macroalgae Sargassum sp and predict antibacterial properties from peptides by bioinformatics analysis. Identification fragment peptide using LC-MS/MS with de novo sequencing method. AMP Scanner Vr.2, iAMP-2L, DBAASP used for prediction antibacterial activities. The peptides' potency as antibacterial was evaluated by looking at the peptides' physicochemical properties used APD3 and ProtParam software. The result showed ten peptides sequences, and these peptides were the first reported; five peptides have antibacterial activities according to data from the software. Physicochemical properties from five peptides show the exciting activity to be used as antibacterial agents. The F4h1k peptide sequence has a higher potential according to data physicochemical. However, it is not yet certain which peptides provide the most optimal activity. It needs to be analyzed further.