A 2D-QSAR, Homology Modeling, Docking, ADMET, and Molecular Dynamics Simulations Studies for Assessment of a Novel SARS-Cov-2 and Pseudomonas Aeruginosa Inhibitors

Abstract

Pseudomonas aeruginosa and SARS-CoV-2 are two of the world's most hazardous diseases. Treatments that target the enzyme or protein could be more successful and efficient. In this study, iminoguanidine derivatives were treated to a combination of five [5] computational assessments in the: 2D-QSAR, homology modeling, docking simulation, ADMET evaluation, and molecular dynamics simulations [MDs simulations]. A dataset of 25 iminoguanidine compounds was used in the QSAR analysis, giving a statistically robust and highly predictive model. The created model has been thoroughly validated and meets various statistical parameter thresholds. The interactions between Chloroquine and Azithromycin, a potentially and commonly used antimalarial and antibacterial medication, and the postulated iminoguanidine derivatives with the SARS-CoV-2 main nucleocapsid phosphoprotein were investigated using the docking simulation. The docking data demonstrate that the novel compound 18 has a high level of stability in the SARS-CoV-2 active site as well as a high binding affinity for the heme oxygenase receptor. The rules of five, rule of two, toxicity, and metabolism were used to screen these compounds for suitable fragments and pharmacological properties. Predictions of pharmacological properties suggested that compound 18 could be a promising therapeutic candidate for Pseudomonas aeruginosa and SARS-CoV-2.