High-yield and cost-effective biosynthesis process for producing antimicrobial peptide AA139.

AA139, a variant of natural antimicrobial peptide (AMP) arenicin-3, displayed potent activity against multidrug-resistant (MDR) and extensively drug-resistant (XDR) Gram-negative bacteria. Nevertheless, there were currently few reports on the bioprocess of AA139, and the yields were less than 5 mg/L. Additionally, it was difficult and expensive to prepare AA139 through chemical synthesis due to its complex structure. These factors have impeded the further research and following clinical application of AA139. Here, we reported a bioprocess for the preparation of AA139, which was expressed in Escherichia coli (E. coli) BL21 (DE3) intracellularly in a soluble form via SUMO (small ubiquitin-related modifier) fusion technology. Then, recombinant AA139 (rAA139, refer to AA139 obtained by recombinant expression in this study) was obtained through the simplified downstream process, which was rationally designed in accordance with the physicochemical characteristics. Subsequently, the expression level of the interest protein was increased by 54% after optimization of high cell density fermentation (HCDF). Finally, we obtained a yield of 56 mg of rAA139 from 1 L culture with a purity of 98%, which represented the highest reported yield of AA139 to date. Furthermore, various characterizations were conducted to confirm the molecular mass, disulfide bonds, and antimicrobial activity of rAA139.

Building HMM and molecular docking analysis for the sensitive detection of anti-viral pneumonia antimicrobial peptides (AMPs).

Pneumonia is the main reason for mortality among children under five years, causing 1.6 million deaths every year; late research has exhibited that mortality is increasing in the elderly. A few biomarkers used for its diagnosis need specificity and precision, as they are related to different infections, for example, pulmonary tuberculosis and Human Immunodeficiency Virus. There is a quest for new biomarkers worldwide to diagnose the disease to defeat these previously mentioned constraints. Antimicrobial peptides (AMPs) are promising indicative specialists against infection. This research work used AMPs as biomarkers to detect viral pneumonia pathogens, for example, Respiratory syncytial virus, Influenza A and B viruses utilizing in silico technologies, such as Hidden Markov Model (HMMER). HMMER was used to distinguish putative anti-viral pneumonia AMPs against the recognized receptor proteins of Respiratory syncytial virus, Influenza A, and B viruses. The physicochemical parameters of these putative AMPs were analyzed, and their 3-D structures were determined utilizing I-TASSER. Molecular docking interaction of these AMPs against the recognized viral pneumonia proteins was carried out using the PATCHDOCK and HDock servers. The results demonstrated 27 anti-viral AMPs ranked based on their E values with significant physicochemical parameters in similarity with known experimentally approved AMPs. The AMPs additionally had a high anticipated binding potential to the pneumonia receptors of these microorganisms sensitively. The tendency of the putative anti-viral AMPs to bind pneumonia proteins showed that they would be promising applicant biomarkers to identify these viral microorganisms in the point-of-care (POC) pneumonia diagnostics. The high precision observed for the AMPs legitimizes HMM's utilization in the disease diagnostics' discovery process.