Histidine-Containing Amphiphilic Peptide-Based Non-Cytotoxic Hydrogelator with Antibacterial Activity and Sustainable Drug Release.
Biswanath HansdaJhilam MajumderBiplab MondalAkash ChatterjeeSubhadeep DasSourav KumarRatan GachhuiValeria CastellettoIan William HamleyProsenjit SenArindam BanerjeePublished in: Langmuir : the ACS journal of surfaces and colloids (2023)
A histidine-based amphiphilic peptide ( P ) has been found to form an injectable transparent hydrogel in phosphate buffer solution over a pH range from 7.0 to 8.5 with an inherent antibacterial property. It also formed a hydrogel in water at pH = 6.7. The peptide self-assembles into a nanofibrillar network structure which is characterized by high-resolution transmission electron microscopy, field-emission scanning electron microscopy, atomic force microscopy, small-angle X-ray scattering, Fourier-transform infrared spectroscopy, and wide-angle powder X-ray diffraction. The hydrogel exhibits efficient antibacterial activity against both Gram-positive bacteria Staphylococcus aureus ( S. aureus ) and Gram-negative bacteria Escherichia coli ( E. coli ). The minimum inhibitory concentration of the hydrogel ranges from 20 to 100 μg/mL. The hydrogel is capable of encapsulation of the drugs naproxen (a non-steroidal anti-inflammatory drug), amoxicillin (an antibiotic), and doxorubicin, (an anticancer drug), but, selectively and sustainably, the gel releases naproxen, 84% being released in 84 h and amoxicillin was released more or less in same manner with that of the naproxen. The hydrogel is biocompatible with HEK 293T cells as well as NIH (mouse fibroblast cell line) cells and thus has potential as a potent antibacterial and drug releasing agent. Another remarkable feature of this hydrogel is its magnification property like a convex lens.
Keyphrases
- electron microscopy
- drug delivery
- high resolution
- hyaluronic acid
- wound healing
- drug release
- tissue engineering
- escherichia coli
- anti inflammatory
- atomic force microscopy
- staphylococcus aureus
- cancer therapy
- high speed
- induced apoptosis
- machine learning
- emergency department
- magnetic resonance imaging
- magnetic resonance
- climate change
- cell death
- multidrug resistant
- pseudomonas aeruginosa
- deep learning
- essential oil
- computed tomography
- gram negative