In Silico Identification of Potential Insect Peptides against Biofilm‐Producing Staphylococcus aureus

Abstract

Biofilm-producing Staphylococcus aureus (SA) strains are frequently found in medical environments, from surgical/ wound sites, medical devices. These biofilms reduce the efficacy of applied antibiotics during the treatment of several infections, such as cystic fibrosis, endocarditis, or urinary tract infections. Thus, the development of potential therapeutic agents to destroy the extra protective biofilm layers or to inhibit the biofilm-producing enzymes is urgently needed. Advanced and cost-effective bioinformatics tools are advantageous in locating and speeding up the selection of antibiofilm candidates. Based on the potential drug characteristics, we have selected one-hundred thirty-three antibacterial peptides derived from insects to assess for their antibiofilm potency via molecular docking against five putative biofilm formation and regulated target enzymes: the staphylococcal accessory regulator A or SarA (PDB ID: 2FRH), 4,4'-diapophytoene synthase or CrtM (PDB ID: 2ZCQ), clumping factor A or ClfA (PDB ID: 1N67) and serine-aspartate repeat protein C or SdrC (PDB ID: 6LXH) and sortase A or SrtA (PDB ID: 1T2W) of SA bacterium. In this study, molecular docking was performed using HPEPDOCK and HDOCK servers, and molecular interactions were examined using BIOVIA Discovery Studio Visualizer-2019. The docking score (kcal/mol) range of five promising antibiofilm peptides against five targets was recorded as follows: diptericin A (À 215.52 to À 303.31), defensin (À 201.11 to À 301.92), imcroporin (À 212.08 to À 287.64), mucroporin (À 228.72 to À 286.76), apidaecin II (À 203.90 to À 280.20). Among these five, imcroporin and mucroporin were 13 % each, while defensin contained only 1 % of positive net charged residues (Arg + Lys) projected through ProtParam and NetWheels tools. Similarly, imcroporin, mucroporin and apidaecin II were 50 %, while defensin carried 21.05 % of hydrophobic residues predicted by the tool PEPTIDE. 2.0. Most of the peptides exhibited potential characteristics to inhibit S. aureus-biofilm formation via disrupting the cell membrane and cytoplasmic integrity. In summary, the proposed hypothesis can be considered a cost-effective platform for selecting the most promising bioactive drug candidates within a limited timeframe with a greater chance of success in experimental and clinical studies.

Myh7 regulates SDRC protein and biofilm formation to alleviate osteomyelitis induced by Staphylococcus aureus

“…In our study, we constructed a model of Staphylococcus aureus induced Osteomyelitis by knocking out the SDRC protein sequence of Staphylococcus aureus and infecting rat, founding that compared with wild type Staphylococcus aureus infected Osteomyelitismouse , its IL-6, TNFα The inflammatory indexes such as ALP, OST and RunX2 were significantly reduced, the infection of bone tissue was significantly lighter, and the osteogenic indexes such as ALP, OST and RunX2 were also significantly increased, suggesting that SDRC protein played a huge role in the occurrence and progress of Osteomyelitis infected by Staphylococcus aureus. Previous studies [19,31] have shown that the most important biological function of SDRC protein is its ability to promote the formation of bacterial biofilms, which is particularly important in the process of bacterial infection of the host [32,33] . Therefore, understanding the molecular mechanism mediated by SDRC protein is of great significance for the treatment of Staphylococcus aureus infectious diseases.…”

Alcoholic Extracts of Eleusine indica as Alternative Diuretic Regimens: A Computational Based Investigation

“…Ltd., Mumbai, India, through local vendors. The entire computational work was analysed on a Linux-Ubuntu 16.04 LTS workstation with several cheminformatics software packages (Swain et al, 2022a;Sahoo et al, 2022b).…”

“…Based on the docking score (kcal/mol. ), the potent phytoconstituents were again docked manually in AutoDock to confirm the ligand's crystallographic binding mode and appropriate docking score through 3-D and twodimensional (2-D) molecular interactions with targets using the software BIOVIA-DSV-2019 (Swain et al, 2022a;Sahoo et al, 2022b).…”

“…So, to see if our compounds would make a good active oral drug candidate, we predicted their physicochemical or Lipinski rule of five (RO5) profiles. We recorded EI_1 to EI_9 along with standard drug profiles individually using the SwissADME tool with reference to the PubChem database (Sahoo et al, 2022b).…”

“…), and P-glycoprotein substrate interactions with cytochrome P450 enzyme interactions (CYP1A2-I, CYP2C19-I, CYP2C9-I, CYP2D6-I, and CYP3A4-I), as well as bioavailability profiles. (Sahoo et al, 2022b and.…”