Magainin 1 TFA
Magainin 1 TFA (Magainin I TFA) is an antimicrobial and amphipathic peptide isolated from the skin of Xenopus laevis. Magainin 1 TFA exhibits antibiotic activity against numerous Gram-negative and Gram-positive bacteria.
For research use only. We do not sell to patients.
- Formula: Magainin I (TFA) C112H177N29O28S·xC2HF3O2
- Molecular Weight:2409.85 (free base)
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Storage:
Please store the product under the recommended conditions in the Certificate of Analysis.
All Antibiotic Isoforms
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Biological Activity
Description
In Vitro
Magainin 1 interacts with acidic lipids through electrostatic interactions followed by hydrophobic interactions to form an amphiphilic helix, inducing the leakage. Magainin 1 induces the leakage of calcein specifically out of negatively-charged vesicles. The peptide binds to bovine brain phosphatidylserine sonicated vesicles according to the Langmuir isotherm with a binding constant of 3.8×105 M-1 and a binding-site number of 0.10 per lipid molecule[2].
MedChemExpress (MCE) has not independently confirmed the accuracy of these methods. They are for reference only. Further protocols information, click here.
Chemical Information
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Molecular Weight 2409.85 (free base)
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Formula Magainin I (TFA) C112H177N29O28S·xC2HF3O2
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Sequence
Gly-Ile-Gly-Lys-Phe-Leu-His-Ser-Ala-Gly-Lys-Phe-Gly-Lys-Ala-Phe-Val-Gly-Glu-Ile-Met-Lys-Ser
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Sequence Shortening
GIGKFLHSAGKFGKAFVGEIMKS
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Structure Classification
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Initial Source
Xenopus laevis
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Shipping
Room temperature in continental US; may vary elsewhere.
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Storage
Please store the product under the recommended conditions in the Certificate of Analysis.
Protocols
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Research Protocol for Infectious Diseases
Infectious-disease experiments test how pathogens interact with host barriers, innate immune receptors, inflammatory signaling, pathogen replication, and tissue injury; pattern-recognition receptors such as TLRs, RIG-I-like receptors, NOD-like receptors, and inflammasomes detect microbial molecules and activate NF-κB, interferon, and cytokine responses. The central hypothesis is that infection severity reflects the balance between pathogen burden and host response: protective inflammation restricts pathogen growth, whereas excessive or mislocalized inflammation contributes to tissue damage and disease phenotype. Unresolved questions include which host pathways are protective versus pathogenic, why some infection models fail to translate to human disease, and which combined readouts best predict clinically relevant infection outcomes.
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Gram Staining of Tissue Sections
Gram staining of tissue sections is a histochemical technique used to differentiate Gram-positive and Gram-negative bacteria within histological specimens based on differences in bacterial cell wall structure and dye retention, adapted from classical bacteriological Gram staining into tissue-compatible “histological Gram stain” variants. In tissue applications, modifications of the Brown-Hopps and Brown-Brenn methods are commonly used to improve differentiation of microorganisms embedded within host connective tissue and to reduce overstaining or loss of Gram-negative signal, which are known limitations of earlier approaches. The principle relies on crystal violet-iodine complex retention in Gram-positive organisms and subsequent decolorization and counterstaining steps that allow contrast visualization of Gram-negative organisms against tissue background.
Purity & Documentation
References
[1]. Duclohier H, et al. Antimicrobial peptide magainin I from Xenopus skin forms anion-permeable channels in planar lipid bilayers. Biophys J. 1989 Nov;56(5):1017-21. [Content Brief]
[2]. Matsuzaki K, et al. Magainin 1-induced leakage of entrapped calcein out of negatively-charged lipid vesicles. Biochim Biophys Acta. 1989 May 19;981(1):130-4. [Content Brief]
[3]. Zasloff M, et al. Magainins, a class of antimicrobial peptides from Xenopus skin: isolation, characterization of two active forms, and partial cDNA sequence of a precursor. Proc Natl Acad Sci U S A. 1987 Aug;84(15):5449-53. [Content Brief]
Calculators
Concentration (start) × Volume (start) = Concentration (final) × Volume (final)