Designing peptide drug with archaeal antimicrobial peptides against multidrug resistant bacterial biofilms and human diseases: an in silico approach
BANERJEE, S.; CHAKRABORTY, S.; MAJUMDER, K.
Show abstract
Novel peptide therapeutics have been the cardinal part of modern-day research. Such therapies are being incorporated to prevent the adverse effects of globally emerging multi-drug resistant bacteria and various chronic human diseases which pose a great risk to the present world. In this study, we have designed a novel peptide therapy involving archaeal antimicrobial peptides. In silico predictions assign the peptide construct to be antigenic, non-allergenic, non-toxic and having stable physicochemical properties. The secondary and tertiary structures of the construct were predicted. The tertiary structure was refined for improving the quality of the predicted model. Computational tools predicted intracellular receptors in Escherichia coli, Klebsiella pneumoniae and the human body to be possible binding targets of the construct. In silico docking of modelled peptide with predicted targets, showed prominent results against targets for complex human diseases and that of bacterial infections. The stability of those docked complexes was confirmed with computational studies of conformational dynamics. Certainly, the designed peptide could be a potent therapeutic against multi-drug resistant bacteria as well as several human diseases.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Molecular and functional characterization of buffalo nasal epithelial odorant binding proteins and their structural insights by in-silico and biochemical approach 96%
- Pharmacophore modeling, 2D-QSAR, Molecular Docking and ADME studies for the discovery of inhibitors of PBP2a in MRSA 96%
- De novo drug designing coupled with brute force screening and structure guided lead optimization gives highly specific inhibitor of METTL3: a potential cure for Acute Myeloid Leukaemia 96%
Similar papers in this journal
- Design of D-amino acids SARS-CoV-2 Main protease inhibitors using the cationic peptide from rattlesnake venom as a scaffold 94%
- Rational design by structural biology of industrializable, long-acting antihyperglycemic GLP-1 receptor agonists 94%
- Peptide-based drug predictions for cancer therapy using deep learning 93%
Similar papers in this journal
Similar papers in this journal
- Putative staphylococcal enterotoxin possesses two common structural motifs for MHC-II binding 95%
- Employing Steered MD Simulations for Effective Virtual Screening: Active Pharmacophore Search by Dynamic Corrections to target MKK3-MYC Interactions 95%
- Computational insights into mechanism of AIM4-mediated inhibition of aggregation of TDP-43 protein implicated in ALS and evidence for in vitro inhibition of liquid-liquid phase separation (LLPS) of TDP-432C-A315T by AIM4. 95%
Similar papers in this journal
- Interfacial residues in protein-protein complexes are in the eyes of the beholder 94%
- Evolutionary Models of Amino Acid Substitutions Based on the Tertiary Structure of their Neighborhoods 93%
- The TCR/peptide/MHC complex with a superagonist peptide shows similar interface and reduced flexibility compared to the complex with a self-peptide 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.