Identification and Bioinformatics Study of Antibacterial Peptides from Symbiotic Bacteria Associated with Macroalgae Sargassum sp
Asmi, N., Ahmad, A., Natsir, H., Massi, M., Karim, H. (2021). Identification and Bioinformatics Study of Antibacterial Peptides from Symbiotic Bacteria Associated with Macroalgae Sargassum sp. EKB Journal Management System, 64(9), 4883-4888. doi: 10.21608/ejchem.2021.68242.3492
Nur Asmi; Ahyar Ahmad; Hasnah Natsir; Muhammad Nasrum Massi; Harningsih Karim. "Identification and Bioinformatics Study of Antibacterial Peptides from Symbiotic Bacteria Associated with Macroalgae Sargassum sp". EKB Journal Management System, 64, 9, 2021, 4883-4888. doi: 10.21608/ejchem.2021.68242.3492
Asmi, N., Ahmad, A., Natsir, H., Massi, M., Karim, H. (2021). 'Identification and Bioinformatics Study of Antibacterial Peptides from Symbiotic Bacteria Associated with Macroalgae Sargassum sp', EKB Journal Management System, 64(9), pp. 4883-4888. doi: 10.21608/ejchem.2021.68242.3492
Asmi, N., Ahmad, A., Natsir, H., Massi, M., Karim, H. Identification and Bioinformatics Study of Antibacterial Peptides from Symbiotic Bacteria Associated with Macroalgae Sargassum sp. EKB Journal Management System, 2021; 64(9): 4883-4888. doi: 10.21608/ejchem.2021.68242.3492

Identification and Bioinformatics Study of Antibacterial Peptides from Symbiotic Bacteria Associated with Macroalgae Sargassum sp

Egyptian Journal of Chemistry
Article 18, Volume 64, Issue 9, September 2021, Page 4883-4888  XML PDF (496.73 K)
Document Type: Original Article
DOI: 10.21608/ejchem.2021.68242.3492
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Authors
Nur Asmiorcid 1; Ahyar Ahmad email orcid 1; Hasnah Natsirorcid 1; Muhammad Nasrum Massiorcid 2; Harningsih Karim3
1Chemistry Department, Mathematics and Natural Sciences, Hasanuddin University, Makassar, Indonesia
2Department of Microbiology, Faculty of Medicine, Hasanuddin University, Makassar 90245, Indonesia
3Pharmacy College YAMASI, Makassar 90222, Indonesia
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.
Keywords
antibacterial; bioinformatic study; de novo sequencing; symbiotic bacteria; peptide
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