High-throughput virtual screening approach of natural compounds as target inhibitors of plasmepsin-II.

Plasmepsin II is a key enzyme in the life cycle of the Plasmodium falciparum parasite responsible for malaria, a disease that is causing deaths on a worldwide scale. Recently, plasmepsin II enzyme has gained much importance as an attractive drug target for the investigation of antimalarial drugs. In this sense, structure-based virtual screening have been utilized as tools in the process of discovering novel natural compounds based on quinoline as potential plasmepsin II inhibitors. Among the 58 quinoline derivatives isolated from different plants was screened by utilizing docking molecular, ADMET approaches, molecular dynamics simulation and MM-PBSA binding free energy. The first step in this work is building the 3 D structures of the plasmepsin II enzyme by using the SWISS-MODEL software. The optimized structures were subjected to virtual screening by Autodock Vina, an entity implicated in PyRx software. 21 were selected based on their binding affinity. The binding modes and interactions of the top-21 selected compounds were evaluated using AutoDock 4.2. Then, the pharmacokinetic proprieties and toxicity of these compounds were evaluated using ADMET analysis. Ten compounds were predicted to have ADMET characteristics with no side effects. Compounds M49 and M53 were found to be potential inhibitors. The stability of the selected two compounds was confirmed by MD simulation and MM/PBSA calculation during 200 ns. This study can be used to predict and to design new antimalarial drugs.Communicated by Ramaswamy H. Sarma.

Prediction of potential inhibitors of SARS-CoV-2 using 3D-QSAR, molecular docking modeling and ADMET properties.

Coronavirus (COVID-19), an enveloped RNA virus, primarily affects human beings. It has been deemed by the World Health Organization (WHO) as a pandemic. For this reason, COVID-19 has become one of the most lethal viruses which the modern world has ever witnessed although some established pharmaceutical companies allege that they have come up with a remedy for COVID-19. To that end, a set of carboxamides sulfonamide derivatives has been under study using 3D-QSAR approach. CoMFA and CoMSIA are one of the most cardinal techniques used in molecular modeling to mold a worthwhile 3D-QSAR model. The expected predictability has been achieved using the CoMFA model (Q2 = 0.579; R2 = 0.989; R2test = 0.791) and the CoMSIA model (Q2 = 0.542; R2 = 0.975; R2test = 0.964). In a similar vein, the contour maps extracted from both CoMFA and CoMSIA models provide much useful information to determine the structural requirements impacting the activity; subsequently, these contour maps pave the way for proposing 8 compounds with important predicted activities. The molecular surflex-docking simulation has been adopted to scrutinize the interactions existing between potentially and used antimalarial molecule on a large scale, called Chloroquine (CQ) and the proposed carboxamides sulfonamide analogs with COVID-19 main protease (PDB: 6LU7). The outcomes of the molecular docking point out that the new molecule P1 has high stability in the active site of COVID-19 and an efficient binding affinity (total scoring) in relation with the Chloroquine. Last of all, the newly designed carboxamides sulfonamide molecules have been evaluated for their oral bioavailability and toxicity, the results point out that these scaffolds have cardinal ADMET properties and can be granted as reliable inhibitors against COVID-19.

Assessment of effective imidazole derivatives against SARS-CoV-2 main protease through computational approach.

Because of the fast increase in deaths due to Corona Viral Infection in majority region in the world, the detection of drugs potent of this infection is a major need. With this idea, docking study was executed on eighteen imidazole derivatives based on 7-chloro-4-aminoquinoline against novel Coronavirus (SARS-CoV-2). In this study, we carried out a docking study of these molecules in the active site of SARS-CoV-2 main protease. The result indicate that Molecules N° 3, 7 and 14 have more binding energy with SARS-CoV-2 main protease recently crystallized (pdb code 6LU7) in comparison with the other imidazole derivatives and the two drug; Chloroquine and hydroxychloroquine. Because of the best energy of interaction, these three molecules could have the most potential antiviral treatment of COVID-19 than the other studied compounds. The structures with best affinity in the binding site of the protease have more than 3 cycles and electronegative atoms in the structure. This may increase the binding affinity of these molecules because of formation of π-bonds, halogen interactions and/or Hydrogen bond interactions between compounds and the enzyme. So, compounds with more cycles and electronegative atoms could have a potent inhibition of SARS-CoV-2 main protease.