Structure-based design of a novel series of azetidine inhibitors of the hepatitis C virus NS3/4A serine protease

Investigating the binding affinity, molecular dynamics, and ADMET properties of 2,3-dihydrobenzofuran derivatives as an inhibitor of fungi, bacteria, and virus protein

Background

2,3-Dihydrobenzofurans (DHB) have proposed as advantages structures, and used as chemical entresol to design small compound libraries. The present study illustrates to explore 2,3-dihydrobenzofurans(DHB) in comparison to selected some derivatives drugs by using molecular docking and molecular dynamics, as well as ADMET studies. The online database “Molinspiration online server” was used to detect the physicochemical pharmacokinetics and drug likeness score of DHB drugs. For estimation of molecular docking, six pathogens, such as Aspergillus niger (PDB id: 1kum), Candida albicans (3dra), Escherichia coli (6og7), Salmonella typhi (4k6l), Influenza (1ru7), and Hepatitis C (4tyd), were chosen due to close biological studies.

Results

From Molinspiration online server has showed that DHB did not violate the “Lipinski five rule” as drugs, leading compound for molecular docking exhibited the potential interaction to the active residue. The binding affinity of DHB2 (−7.00 kcal/mol) against 3dra was higher than DHB8 (−6.40 kcal/mol) and DHB (5.70 kcal/mol) for compounds. The results of molecular docking show that the compounds mentioned in this study are not equally effective against pathogens, such as fungi, viruses, and bacteria. However, DHB2, DHB3, and DHB 8 compounds can work against almost given pathogens which results are derived from auto dock vina in terms of binding affinity around 6.00 kcal/mol, and Fire Dock has values from about 38.0 to 42.0 kcal/mol. To explore the dynamic nature of the interaction, 50 ns molecular dynamics (MD) simulation was performed on the selected protein-DHB complexes. Thus, DHB 8 has greater potential to interact for further for fungi.

Conclusion

Finding from this study can play an effective role as a drug in any biological system. This study as well recommends to researchers to synthesize these DHBs for evaluation of its biological activity.

Graphical abstract

Polyhydroxylated azetidine iminosugars: Synthesis, glycosidase inhibitory activity and molecular docking studies

An efficient and practical strategy for the synthesis of unknown azetidine iminosugars (2S,3R,4S)-2-((R)-1,2-dihydroxyethyl)-3-hydroxy-4-(hydroxymethyl)azetidine 2, (2S,3r,4R)-3-hydroxy-2,4-bis(hydroxymethyl)azetidine 3 and (2S,3R,4S)-3-hydroxy-4-(hydroxymethyl)-N-methylazetidine-2-carboxylic acid 4, starting from the d-glucose has been reported. The methodology involves preparation of the 3-amino-N-benzyloxycarbonyl-3-deoxy-6-O-tert-butyldimethylsillyl-1,2-O-isopropylidene-α-d-glucofuranose 9, which was converted to the C-5-OMs derivative 11. Intramolecular nucleophilic displacement of the C-5-OMs group with in situ generated 3-amino functionality provided the required key azetidine ring skeletons 10 with additional hydroxymethyl group. Removal of 1,2-acetonide protection, followed by reduction and hydrogenolysis afforded azetidine iminosugar 2. Alternatively, removal of 1,2-acetonide group and chopping of C1-anomeric carbon gave C2-aldehyde that on reduction or oxidation followed by hydrogenolysis gave 2,4-bis(hydroxymethyl) azetidine iminosugars 3 and N-methylazetidine-2-carboxylic acid 4 respectively. The glycosidase inhibitory activity of 2-4 iminosugars was screened against various glycosidase enzymes and compared with a standard miglitol. Amongst synthesized targets, the compound 2 was found to be more potent amyloglucosidase inhibitor than miglitol. These results were supported by molecular docking studies.

QSAR studies of the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by multiple linear regression (MLR) and support vector machine (SVM)

In this study, quantitative structure-activity relationship (QSAR) models using various descriptor sets and training/test set selection methods were explored to predict the bioactivity of hepatitis C virus (HCV) NS3/4A protease inhibitors by using a multiple linear regression (MLR) and a support vector machine (SVM) method. 512 HCV NS3/4A protease inhibitors and their IC₅₀ values which were determined by the same FRET assay were collected from the reported literature to build a dataset. All the inhibitors were represented with selected nine global and 12 2D property-weighted autocorrelation descriptors calculated from the program CORINA Symphony. The dataset was divided into a training set and a test set by a random and a Kohonen's self-organizing map (SOM) method. The correlation coefficients (r²) of training sets and test sets were 0.75 and 0.72 for the best MLR model, 0.87 and 0.85 for the best SVM model, respectively. In addition, a series of sub-dataset models were also developed. The performances of all the best sub-dataset models were better than those of the whole dataset models. We believe that the combination of the best sub- and whole dataset SVM models can be used as reliable lead designing tools for new NS3/4A protease inhibitors scaffolds in a drug discovery pipeline.

Synthesis of potent and broad genotypically active NS5B HCV non-nucleoside inhibitors binding to the thumb domain allosteric site 2 of the viral polymerase

The hepatitis C virus (HCV) NS5B RNA-dependent RNA polymerase (RdRp) plays a central role in virus replication. NS5B has no functional equivalent in mammalian cells and, as a consequence, is an attractive target for selective inhibition. This Letter describes the discovery of a new family of HCV NS5B non-nucleoside inhibitors, based on the bioisosterism between amide and phosphonamidate functions. As part of this program, SAR in this new series led to the identification of IDX17119, a potent non-nucleoside inhibitor, active on the genotypes 1b, 2a, 3a and 4a. The structure and binding domain of IDX17119 were confirmed by X-ray co-crystallization study.