Aliyu Abdulmalik2024-04-172024-04-172022-10https://uilspace.unilorin.edu.ng/handle/123456789/11981Carbapenem-resistant and carbapenemase-producing Pseudomonas aeruginosa (CRPA) and methicillin-resistant Staphylococcus aureus (MRSA) are two pathogens that are resistant to currently available antimicrobials. As an alternative to effective medication molecules, antimicrobial peptides (AMPs) have the potential to cure superbug-caused infections effectively. Two new AMPs (ama1 and ama2) were designed utilizing a knowledge-based technique with optimal parameters. First, the PEP-FOLD 3.5 server made a de novo prediction of the AMPs' three-dimensional (3D) structure, which was validated using PROCHECK of SAVES v6.0 by checking the amino acid locations in the Ramachandra plot. Then, protein-peptide docking simulations of the predicted AMPs and reference AMP (Aurein 1.2) for positive control were performed using the HPEPDOCK docking web server, followed by the computation of the AMPs' physicochemical parameters and toxicity profile using the ProtParam and vNN-ADMET web servers, respectively. The sequences for ama1 and ama2 were AWGKIKALR and IKWLRLAKP, respectively. Docking analysis revealed that the antibacterial activity of ama1 and ama2 was superior to that of Aurein 1.2 against CRPA-resistant enzyme (6ew3), respectively. However, ama1, ama2, and Aurein 1.2 inhibited the activity of MRSA-resistant protein (4c12). Both the physicochemical qualities and the toxicity profiles were advantageous. Therefore, the in-silico-derived AMPs could serve as a pharmaceutical candidate for developing multidrug-resistant bacteria-effective antimicrobials.Antimicrobial peptidesMolecular docking Pseudomonas aeruginosa Pharmacokinetic parameters Resistant pathogens Staphylococcus aureus