Evaluation of chalcones as new glycogen phosphorylase inhibitors - an in-vitro and in-silico approach.

Diabetes mellitus (DM) remains one of the pivotal diseases that have drawn the attention of researchers recently and during the last few decades. Due to its devastating symptoms, attempts to develop new drugs with mild side effects have resulted in a number of drugs that are functioning through various mechanisms. Among these, Glycogen phosphorylase (GP) inhibitors emerged as a new strategy for combating DM. GP is an enzyme that regulates blood glucose levels; it catalyses the breakdown of glycogen to glucose-1-phosphate in the liver and tissues with high and fluctuating energy demands. In the present research, we evaluate the possibility of type 2 diabetes therapy with the help of chalcones which are known to have antidiabetic activities. For this purpose, 29 chalcones were modelled, synthesised and investigated for their inhibitory activity against GP using in-vitro methods. Compounds 1, 2, and 3 were found to be the most potent compounds with IC50 values 26.6, 57.1 and 75.6 µM respectively. The observed results were further validated using in-silico methods. Molecular docking simulation revealed interaction patterns that explain the structure-activity relationships of the compounds with GP. Molecular dynamic (MD) simulation demonstrated a stable complex formation between compound 1 and GP through lower value and uniformity in root mean square deviation (RMSD) of the complex and root mean square fluctuation (RMSF) of the protein Cα.

Chalcone Scaffolds Exhibiting Acetylcholinesterase Enzyme Inhibition: Mechanistic and Computational Investigations.

This study was aimed to perform the mechanistic investigations of chalcone scaffold as inhibitors of acetylcholinesterase (AChE) enzyme using molecular docking and molecular dynamics simulation tools. Basic chalcones (C1-C5) were synthesized and their in vitro AChE inhibition was tested. Binding interactions were studied using AutoDock and Surflex-Dock programs, whereas the molecular dynamics simulation studies were performed to check the stability of the ligand-protein complex. Good AChE inhibition (IC50 = 22 ± 2.8 to 37.6 ± 0.75 µM) in correlation with the in silico results (binding energies = -8.55 to -8.14 Kcal/mol) were obtained. The mechanistic studies showed that all of the functionalities present in the chalcone scaffold were involved in binding with the amino acid residues at the binding site through hydrogen bonding, π-π, π-cation, π-sigma, and hydrophobic interactions. Molecular dynamics simulation studies showed the formation of stable complex between the AChE enzyme and C4 ligand.

Evaluation of certain medicinal plants compounds as new potential inhibitors of novel corona virus (COVID-19) using molecular docking analysis.

SARS-CoV-2 is a new strain of coronavirus that appeared in China in December 2019, in recent years, great progress has been made in developing new antiviral drugs, and natural products, are important sources of potential and new antiviral drugs. The present study aimed to assess some biologically active compounds present in medicinal plants as potential COVID-19 inhibitors, using molecular docking methods. The Docking study was performed by Molecular Operating Environment software (MOE). About 20 Compounds were screened in this study; these compounds were selected based on classification of their chemical origin and their antiviral activity from literature. These compounds might be used to inhibit COVID-19 infection. The results demonstrate the effectiveness of this screening strategy, which can lead to rapid drug discovery in response to new infectious diseases. The results showed that many compounds isolated from medicinal plants such as; Gallic acid (- 17.45), Quercetin (- 15.81), Naringin (- 14.50), Capsaicin (- 13.90), and Psychotrine (- 13.5) are important sources for novel antiviral drugs targeting COVID-19.

Valproic acid as a potential inhibitor of Plasmodium falciparum histone deacetylase 1 (PfHDAC1): an in silico approach.

A new Plasmodium falciparum histone deacetylase1 (PfHDAC1) homology model was built based on the highest sequence identity available template human histone deacetylase 2 structure. The generated model was carefully evaluated for stereochemical accuracy, folding correctness and overall structure quality. All evaluations were acceptable and consistent. Docking a group of hydroxamic acid histone deacetylase inhibitors and valproic acid has shown binding poses that agree well with inhibitor-bound histone deacetylase-solved structural interactions. Docking affinity dG scores were in agreement with available experimental binding affinities. Further, enzyme-ligand complex stability and reliability were investigated by running 5-nanosecond molecular dynamics simulations. Thorough analysis of the simulation trajectories has shown that enzyme-ligand complexes were stable during the simulation period. Interestingly, the calculated theoretical binding energies of the docked hydroxamic acid inhibitors have shown that the model can discriminate between strong and weaker inhibitors and agrees well with the experimental affinities reported in the literature. The model and the docking methodology can be used in screening virtual libraries for PfHDAC1 inhibitors, since the docking scores have ranked ligands in accordance with experimental binding affinities. Valproic acid calculated theoretical binding energy suggests that it may inhibit PfHDAC1.