Fmoc-phenylalanine displays antibacterial activity against Gram-positive bacteria in gel and solution phases.

In the quest for new antimicrobial materials, hydrogels of Fmoc-protected peptides and amino acids have gained momentum due to their ease of synthesis and cost effectiveness; however, their repertoire is currently limited, and the mechanistic details of their function are not well understood. Herein, we report the antibacterial activity of the hydrogel and solution phases of Fmoc-phenylalanine (Fmoc-F) against a variety of Gram-positive bacteria including methicillin-resistant Staphylococcus aureus (MRSA). Fmoc-F, a small molecule hydrogelator, reduces the bacterial load both in vitro and in the skin wound infections of mice. The antibacterial activity of Fmoc-F is predominantly due to its release from the hydrogel. Fmoc-F shows surfactant-like properties with critical micelle concentration nearly equivalent to its minimum bactericidal concentration. Similar to Fmoc-F, some Fmoc-conjugated amino acids (Fmoc-AA) have also shown antibacterial effects that are linearly correlated with their surfactant properties. At low concentrations, where Fmoc-F does not form micelles, it inhibits bacterial growth by entering the cell and reducing the glutathione levels. However, at higher concentrations, Fmoc-F triggers oxidative and osmotic stress and, alters the membrane permeabilization and integrity, which kills Gram-positive bacteria. Herein, we proposed the use of the Fmoc-F hydrogel and its solution for several biomedical applications. This study will open up new avenues to enhance the repertoire of Fmoc-AA to act as antimicrobial agents and improve their structure-activity relationship.

Literature-based drug-drug similarity for drug repurposing: impact of Medical Subject Headings term refinement and hierarchical clustering.

Background: We describe herein, an improved procedure for drug repurposing based on refined Medical Subject Headings (MeSH) terms and hierarchical clustering method. Materials & methods: In the present study, we have employed MeSH data from MEDLINE (2019), 1669 US FDA approved drugs from Open FDA and a refined set of MeSH terms. Refinement of MeSH terms was performed to include terms related to mechanistic information of drugs and diseases. Results and Conclusions: In-depth analysis of the results obtained, demonstrated greater efficiency of the proposed approach, based on refined MeSH terms and hierarchical clustering, in terms of number of selected drug candidates for repurposing. Further, analysis of misclustering and size of noise clusters suggest that the proposed approach is reliable and can be employed in drug repurposing.