Discovery of New Amphipathic Helix Antibacterial Peptides with Proteomic Analysis using LC-HRMS and Virtual Screening
Keywords:
Antibacterial, Discovery, Peptide, Proteomic, Virtual Screening
Abstract
Antimicrobial peptide is an alternative to combat antibiotic resistance with typical characteristics such as amphipathic and helical structure. Several approaches such as virtual and conventional screening have been employed to discover new antibacterial peptides. In the current study we aim to discover new antibacterial peptides with virtual screening by filtering proteomic data bank of Chondrus crispus using machine learning. The proteomic data bank of Chondrus crispus were generated by LC-HRMS after tryptic digestion. The candidate peptides selection was carried out using machine learning and AMP’s characteristics. The proteomic study resulted 3645 candidate peptides. The first filtering using a positive charge characteristic, avoid amino acid and 12 – 50 residual lengths resulted 175 candidate peptides. Twelve candidate peptides were resulted second filtering by scoring using CAMPR4 and dbAMP. The last filtering performed by physicochemical analysis resulted three selected peptides CC1 (FSTSSRALRFFR), CC2 (RDLQQAISMVKK), and CC3 (IAAKIQLLRSYR). All selected peptides have promising physicochemical with amphipathic structures. The secondary structure analysis by CD showed that all peptides have a random coil structure in water and helix structure in 50% TFE. CC1 and CC3 showed inhibitions up to 100% at 250 μg/mL concentration against E. coli. However, both peptides exhibited lower activity against S. aureus with inhibitions around 50-60% at 250 μg/mL.
References
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Caprani, M. C., Healy, J., Slattery, O., & O’Keeffe, J. (2021). Using an Ensemble to Identify and Classify Macroalgae Antimicrobial Peptides. Interdisciplinary Sciences: Computational Life Sciences, 13(2), 321–333. https://doi.org/10.1007/s12539-021-00435-6
Capriotti, A. L., Cavaliere, C., Piovesana, S., Samperi, R., & Laganà, A. (2016). Recent trends in the analysis of bioactive peptides in milk and dairy products. Analytical and Bioanalytical Chemistry, 408(11), 2677–2685. https://doi.org/10.1007/S00216-016-9303-8/FIGURES/1
Chen, Y., Guarnieri, M. T., Vasil, A. I., Vasil, M. L., Mant, C. T., & Hodges, R. S. (2007). Role of peptide hydrophobicity in the mechanism of action of α-helical antimicrobial peptides. Antimicrobial Agents and Chemotherapy, 51(4), 1398–1406. https://doi.org/10.1128/AAC.00925-06/ASSET/64D167C5-5052-4B28-BB57-AABF7714F559/ASSETS/GRAPHIC/ZAC0040763980006.JPEG
Edwards, I. A., Elliott, A. G., Kavanagh, A. M., Zuegg, J., Blaskovich, M. A. T., & Cooper, M. A. (2016). Contribution of amphipathicity and hydrophobicity to the antimicrobial activity and cytotoxicity of β-hairpin peptides. ACS Infectious Diseases, 2(6), 442–450. https://doi.org/10.1021/ACSINFECDIS.6B00045/ASSET/IMAGES/LARGE/ID-2016-000456_0007.JPEG
Founou, R. C., Founou, L. L., & Essack, S. Y. (2017). Clinical and economic impact of antibiotic resistance in developing countries: A systematic review and meta-analysis. PLOS ONE, 12(12), 1–18. https://doi.org/10.1371/JOURNAL.PONE.0189621
Gawde, U., Chakraborty, S., Waghu, F. H., Barai, R. S., Khanderkar, A., Indraguru, R., Shirsat, T., & Idicula-Thomas, S. (2022). CAMPR4: a Database of Natural and Synthetic Antimicrobial Peptides. Nucleic Acids Research, 51(D1), D377–D383. https://doi.org/10.1093/nar/gkac933
Habibie, A., Raharjo, T. J., Swasono, R. T., & Retnaningrum, E. (2023). Antibacterial activity of active peptide from marine macroalgae Chondrus crispus protein hydrolysate against Staphylococcus aureus. Pharmacia, 70(4), 983–992. https://doi.org/10.3897/pharmacia.70.e112215
Hancock, R. E. W., & Patrzykat, A. (2002). Clinical development of cationic antimicrobial peptides: from natural to novel antibiotics. Current Drug Targets. Infectious Disorders, 2(1), 79–83. https://doi.org/10.2174/1568005024605855
Hollmann, A., Martínez, M., Noguera, M. E., Augusto, M. T., Disalvo, A., Santos, N. C., Semorile, L., & Maffía, P. C. (2016). Role of amphipathicity and hydrophobicity in the balance between hemolysis and peptide–membrane interactions of three related antimicrobial peptides. Colloids and Surfaces B: Biointerfaces, 141, 528–536. https://doi.org/10.1016/J.COLSURFB.2016.02.003
Huan, Y., Kong, Q., Mou, H., & Yi, H. (2020). Antimicrobial Peptides: Classification, Design, Application and Research Progress in Multiple Fields. Frontiers in Microbiology, 11(582779), 1–21. https://doi.org/10.3389/fmicb.2020.582779
Huang, Y., He, L., Li, G., Zhai, N., Jiang, H., & Chen, Y. (2014). Role of helicity of α-helical antimicrobial peptides to improve specificity. Protein Cell, 5(8), 631–642. https://doi.org/10.1007/s13238-014-0061-0
Hutchings, M., Truman, A., & Wilkinson, B. (2019). Antibiotics: past, present and future. Current Opinion in Microbiology, 2019(51), 72–80. https://doi.org/10.1016/J.MIB.2019.10.008
Huynh, L., Velásquez, J., Rabara, R., Basu, S., Nguyen, H. B., & Gupta, G. (2021). Rational Design of Antimicrobial Peptides Targeting Gram-negative Bacteria. Computational Biology and Chemistry, 92(107475), 1–7. https://doi.org/10.1016/j.compbiolchem.2021.107475
Jiao, K., Gao, J., Zhou, T., Yu, J., Song, H., Wei, Y., & Gao, X. (2019). Isolation and purification of a novel antimicrobial peptide from Porphyra yezoensis. Journal of Food Biochemistry, 43(7), 1–9. https://doi.org/10.1111/jfbc.12864
Le Huy, B., Phuong, H. B. T., Thanh, B. N. T., Van, Q. T., Dinh, H. V., & Xuan, H. L. (2024). Influence of hydrophobicity on the antimicrobial activity of helical antimicrobial peptides: a study focusing on three mastoparans. Molecular Diversity. https://doi.org/10.1007/S11030-024-11046-W
Li, Y., Xiang, Q., Zhang, Q., Huang, Y., & Su, Z. (2012). Overview On the Recent Study of Antimicrobial Peptides: Origins, Functions, Relative Mechanisms and Application. Peptides, 37(2), 207–215. https://doi.org/10.1016/j.peptides.2012.07.001
Lunkad, R., Murmiliuk, A., Tošner, Z., Štěpánek, M., & Košovan, P. (2021). Role of p KA in Charge Regulation and Conformation of Various Peptide Sequences. Polymers, 13(2), 2–21. https://doi.org/10.3390/POLYM13020214
Malanovic, N., Leber, R., Schmuck, M., Kriechbaum, M., Cordfunke, R. A., Drijfhout, J. W., De Breij, A., Nibbering, P. H., Kolb, D., & Lohner, K. (2015). Phospholipid-driven differences determine the action of the synthetic antimicrobial peptide OP-145 on Gram-positive bacterial and mammalian membrane model systems. Biochimica et Biophysica Acta (BBA) - Biomembranes, 1848(10), 2437–2447. https://doi.org/10.1016/J.BBAMEM.2015.07.010
Malanovic, N., & Lohner, K. (2016). Gram-positive bacterial cell envelopes: The impact on the activity of antimicrobial peptides. Biochimica et Biophysica Acta - Biomembranes, 1858(5), 936–946. https://doi.org/10.1016/j.bbamem.2015.11.004
Micsonai, A., Moussong, É., Wien, F., Boros, E., Vadászi, H., Murvai, N., Lee, Y. H., Molnár, T., Réfrégiers, M., Goto, Y., Tantos, Á., & Kardos, J. (2022). BeStSel: webserver for secondary structure and fold prediction for protein CD spectroscopy. Nucleic Acids Research, 50(W1), W90–W98. https://doi.org/10.1093/NAR/GKAC345
Miles, A. J., Janes, R. W., & Wallace, B. A. (2021). Tools and methods for circular dichroism spectroscopy of proteins: a tutorial review. Chemical Society Reviews, 50(15), 8400–8413. https://doi.org/10.1039/D0CS00558D
Myers, J. K., Pace, C. N., & Scholtz, J. M. (1998). Trifluoroethanol effects on helix propensity and electrostatic interactions in the helical peptide from ribonuclease T1. Protein Science : A Publication of the Protein Society, 7(2), 383. https://doi.org/10.1002/PRO.5560070219
Narayana, J. L., Mishra, B., Lushnikova, T., Wu, Q., Chhonker, Y. S., Zhang, Y., Zarena, D., Salnikov, E. S., Dang, X., Wang, F., Murphy, C., Foster, K. W., Gorantla, S., Bechinger, B., Murry, D. J., & Wang, G. (2020). Two distinct amphipathic peptide antibiotics with systemic efficacy. Proceedings of the National Academy of Sciences of the United States of America, 117(32), 19446–19454. https://doi.org/10.1073/PNAS.2005540117/SUPPL_FILE/PNAS.2005540117.SAPP.PDF
Rahman, M., Browne, J. J., Van Crugten, J., Hasan, M. F., Liu, L., & Barkla, B. J. (2020). In Silico, Molecular Docking and In Vitro Antimicrobial Activity of the Major Rapeseed Seed Storage Proteins. Frontiers in Pharmacology, 11(1340), 1–23. https://doi.org/10.3389/fphar.2020.01340
Roversi, D., Luca, V., Aureli, S., Park, Y., Mangoni, M. L., & Stella, L. (2014). How many antimicrobial peptide molecules kill a bacterium? The case of PMAP-23. ACS Chemical Biology, 9(9), 2003–2007. https://doi.org/10.1021/CB500426R/SUPPL_FILE/CB500426R_SI_001.PDF
Saubenova, M., Rapoport, A., Yermekbay, Z., & Oleinikova, Y. (2025). Antimicrobial Peptides, Their Production, and Potential in the Fight Against Antibiotic-Resistant Pathogens. Fermentation 2025, Vol. 11, Page 36, 11(1), 36. https://doi.org/10.3390/FERMENTATION11010036
Schrader, M., Schulz-Knappe, P., & Fricker, L. D. (2014). ScienceDirect Historical perspective of peptidomics. EuPA OPEM PROTEOMICS, 3, 171–182. https://doi.org/10.1016/j.euprot.2014.02.014
Song, J., Liu, K., Jin, X., Huang, K., Fu, S., Yi, W., Cai, Y., Yu, Z., Mao, F., & Zhang, Y. (2024). Machine Learning-Driven Discovery and Evaluation of Antimicrobial Peptides from Crassostrea gigas Mucus Proteome. Marine Drugs, 22(9), 385. https://doi.org/10.3390/MD22090385
Spohn, R., Daruka, L., Lázár, V., Martins, A., Vidovics, F., Grézal, G., Méhi, O., Kintses, B., Számel, M., Jangir, P. K., Csörgő, B., Györkei, Á., Bódi, Z., Faragó, A., Bodai, L., Földesi, I., Kata, D., Maróti, G., Pap, B., … Pál, C. (2019). Integrated evolutionary analysis reveals antimicrobial peptides with limited resistance. Nature Communications, 10(4538), 1–13. https://doi.org/10.1038/s41467-019-12364-6
Wang, L., Wang, N., Zhang, W., Cheng, X., Yan, Z., Shao, G., Wang, X., Wang, R., & Fu, C. (2022). Therapeutic peptides: current applications and future directions. In Signal Transduction and Targeted Therapy (Vol. 7, Issue 1). Springer Nature. https://doi.org/10.1038/s41392-022-00904-4
Xu, J., Li, F., Li, C., Guo, X., Landersdorfer, C., Shen, H. H., Peleg, A. Y., Li, J., Imoto, S., Yao, J., Akutsu, T., & Song, J. (2023). iAMPCN: a deep-learning approach for identifying antimicrobial peptides and their functional activities. Briefings in Bioinformatics, 24(4). https://doi.org/10.1093/BIB/BBAD240
Yao, L., Guan, J., Xie, P., Chung, C. R., Zhao, Z., Dong, D., Guo, Y., Zhang, W., Deng, J., Pang, Y., Liu, Y., Peng, Y., Horng, J. T., Chiang, Y. C., & Lee, T. Y. (2025). dbAMP 3.0: updated resource of antimicrobial activity and structural annotation of peptides in the post-pandemic era. Nucleic Acids Research, 53(D1), D364–D376. https://doi.org/10.1093/NAR/GKAE1019
Zhang, Y., He, S., Bonneil, É., & Simpson, B. K. (2020). Generation Of Antioxidative Peptides from Atlantic Sea Cucumber Using Alcalase Versus Trypsin: In Vitro Activity, De Novo Sequencing, and In Silico Docking For In Vivo Function Prediction. Food Chemistry, 306(125581), 1–10. https://doi.org/10.1016/j.foodchem.2019.125581
Zhou, Q. J., Wang, J., Liu, M., Qiao, Y., Hong, W. S., Su, Y. Q., Han, K. H., Ke, Q. Z., & Zheng, W. Q. (2016). Identification, expression and antibacterial activities of an antimicrobial peptide NK-lysin from a marine fish Larimichthys crocea. Fish & Shellfish Immunology, 55, 195–202. https://doi.org/10.1016/J.FSI.2016.05.035
Published
2025-08-28
How to Cite
Habibie, A., Putri, R. A., Husna, I., CHANDRA, K. K. B., Swasono, R. T., Retnaningrum, E., Raharjo, T., & Siahaan, T. (2025). Discovery of New Amphipathic Helix Antibacterial Peptides with Proteomic Analysis using LC-HRMS and Virtual Screening. Indonesian Journal of Pharmacy. https://doi.org/10.22146/ijp.23682
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Research Article
