Natural products remain a popular alternative treatment for many ailments in various countries. This study aimed to screen for potential mammalian target of rapamycin (mTOR) inhibitors from Malaysian natural substance, using the Natural Product Discovery database, and to determine the IC50 of the selected mTOR inhibitors against UMB1949 cell line. The crystallographic structure of the molecular target (mTOR) was obtained from Protein Data Bank, with Protein Data Bank (PDB) ID: 4DRI. Everolimus, an mTOR inhibitor, was used as a standard compound for the comparative analysis. Computational docking approach was performed, using AutoDock Vina (screening) and AutoDock 4.2.6 (analysis). Based on our analysis, asiaticoside and its derivative, asiatic acid, both from Centella asiatica, revealed optimum-binding affinities with mTOR that were comparable to our standard compound. The effect of asiaticoside and asiatic acid on mTOR inhibition was validated with UMB1949 cell line, and their IC50 values were 300 and 60 µM, respectively, compared to everolimus (29.5 µM). Interestingly, this is the first study of asiaticoside and asiatic acid against tuberous sclerosis complex (TSC) disease model by targeting mTOR. These results, coupled with our in silico findings, should prompt further studies, to clarify the mode of action, safety, and efficacy of these compounds as mTOR inhibitors.

In our study, molecular docking and molecular dynamics (MD) simulations were performed in order to explore the interactions between human insulin and β-cyclodextrin (β-CD). Molecular docking study was performed using the Autodock v4.2 program to determine the number of β-CD molecules that adhere to the binding sites of insulin. A random structure docking approach using an initial ratio of 1:1 insulin-β-CD was conducted and from these, additional β-CDs were added. Molecular docking results revealed that a maximum of four β-CDs are able to bind to the insulin structure with the 1:3 insulin-β-CD ratio producing the lowest binding free energy. The docked conformations showed that hydrophobic interactions played a crucial role in insulin-β-CD conformational stability in addition to the formation of hydrogen bonds. A 50 ns MD simulation was further conducted using an NPT ensemble to verify the results obtained by molecular docking. The analysis of the MD simulation results of the 1:3 insulin-β-CD formation system conclude that a good interaction exists between insulin and β-CDs and the RMSD value obtained was 4.00 ± 0.50 Å. The RMSF profiles of insulin in the 1:3 insulin-β-CD formation also show reduced amino acid residues flexibility as compared to the free insulin system. The theoretical results indicated the presence of significant interactions between insulin and β-CD which could provide interesting insights into an insulin formulation.

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Acetylcholinesterase (AChE) inhibitors are the most effective drugs for Alzheimer's disease treatment. However, considering the potential and failure rates of AChE inhibitors, chemical scaffolds targeting cholinesterase specifically are still very limited. Herein, we report a new class of AChE inhibitors identified by employing a virtual screening approach that combines shape similarity with molecular docking calculations. Virtual screening followed by the evaluation of AChE inhibitory activity allowed us to identify 1,2,4-triazolylthioethanones as a novel class of AChE inhibitors. Thirteen compounds with 1,2,4-triazolylthiothanone core and IC 50 values in the range of 0.15 � 0.07 to 3.32 � 0.92 μM have been reported here. Our findings shed light into a class of AChE inhibitors that could be useful starting point for the development of novel therapeutics to tackle Alzheimer's disease.