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Dengue is an arboviral disease caused by the dengue flavivirus. The NS5 protein of flaviviruses is a potential therapeutic target, and comprises an RNA-dependent RNA polymerase (RDRP) domain that catalyses viral replication. The aim of this study was to repurpose FDA-approved drugs against the RDRP domain of dengue virus serotype 3 (DENV3) using structure-based virtual screening and molecular dynamics (MD) simulations. The FDA-approved drugs were screened against the RDRP domain of DENV3 using a two-step docking-based screening approach with Glide SP and Glide XP. For comparison, four reported DENV3 RDRP inhibitors were docked as standards. The hitlist was screened based on the docking score of the inhibitor with the lowest docking score (PubChem ID: 118797902; reported IC50 value: 0.34 µM). Five hits with docking scores and Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) energy lower than those of 118797902 were selected. The stability of the hit-receptor complexes was investigated using 100 ns MD simulations in an explicit solvent. The results of MD simulations demonstrated that polydatin and betiatide remained stably bound to the receptor, and formed stable interactions with the RDRP domain of DENV3. The hit-receptor interactions were comparable to those of 118797902. The average Prime MM-GBSA energy of polydatin and betiatide was lower than that of 118797902 during simulation, indicating that their binding affinity to DENV3 RDRP was higher than that of the standard. The results of this study may aid in the development of serotype-selective drugs against dengue in the future. Communicated by Ramaswamy H. Sarma

Epidermal growth factor receptor (EGFR), being one of the most crucial receptor in cancer therapy, has been selected as a potential target for the present study. Ligand-based pharmacophore model (

Defense personnel utilize capsaicin-based ocular sprays as non-lethal agents for law implementation during instances of mob violence. This study involves the capsaicin antagonist Capsazepine and th...

We have developed a robust quantitative structure-activity relationship (QSAR) model employing a dataset of 98 heterocycle compounds to identify structural features responsible for BACE1 (beta-secretase 1) enzyme inhibition. We have used only 2D descriptors for model development purpose thus avoiding the conformational complications arising due to 3D geometry considerations. Following the strict Organization for Economic Co-operation and Development (OECD) guidelines, we have developed models using stepwise regression analysis followed by the best subset selection, while the final model was developed by partial least squares regression technique. The model was validated using various internationally accepted stringent validation parameters. From the insights obtained from the developed model, we have concluded that heteroatoms (nitrogen, oxygen, etc.) present within to an aromatic nucleus and the structural features such as hydrophobic, ring aromatic and hydrogen bond acceptor/donor are responsible for the enhancement of the BACE1 enzyme inhibitory activity. Moreover, we have performed the pharmacophore modelling to unveil the structural requirements for the inhibitory activity against the BACE1 enzyme. Furthermore, molecular docking studies were carried out to understand the molecular interactions involved in binding, and the results are then correlated with the requisite structural features obtained from the QSAR and pharmacophore models.

Matrix metalloproteinase-2 (MMP-2) is a potential target in anticancer drug discovery due to its association with angiogenesis, metastasis and tumour progression. In this study, 67 glutamic acid derivatives, synthesized and evaluated as MMP-2 inhibitors, were taken into account for multi-QSAR modelling study (regression-based 2D-QSAR, classification-based LDA-QSAR, Bayesian classification QSAR, HQSAR, 3D-QSAR CoMFA and CoMSIA as well as Open3DQSAR). All these QSAR studies were statistically validated individually. Regarding the 3D-QSAR analysis, the Open3DQSAR results were better than CoMFA and CoMSIA, although all these 3D-QSAR models supported each other. The importance of biphenylsulphonyl moiety over phenylacetyl/naphthylacetyl moieties was established due to its association with favourable steric and hydrophobic characters. HQSAR, LDA-QSAR and Bayesian classification QSAR studies also suggested that the biphenylsulphonamido group was better than the phenylacetylcarboxamido function. Additionally, glutamines were proven to be far better inhibitors than isoglutamines. Observations obtained from the current study were revalidated and supported by the earlier reported molecular modelling studies. Depending on these observations, newer glutamic acid-based compounds may be designed further in future for potent MMP-2 inhibitory activity.

Dual inhibition of A2A and MAO-B is an emerging strategy in neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD). In this study, atom-based three-dimensional quantitative structure–activity relationship (3D-QSAR) and hologram quantitative structure–activity relationship (HQSAR) models were generated with benzothiazine and deazaxanthine derivatives. Based on activity against A2A and MAO-B, two statistically significant 3D-QSAR models (r2 = 0.96, q2 = 0.76 and r2 = 0.91, q2 = 0.63) and HQSAR models (r2 = 0.93, q2 = 0.68 and r2 = 0.97, q2 = 0.58) were developed. In an activity cliff analysis, structural outliers were identified by calculating the Mahalanobis distance for a pair of compounds with A2A and MAO-B inhibitory activities. The generated 3D-QSAR and HQSAR models, activity cliff analysis, molecular docking and dynamic studies for dual target protein inhibitors provide key structural scaffolds that serve as building blocks in designing drug-like molecules for...

Peroxysome proliferator-activated receptors (PPARs) have grown greatly in importance due to their role in the metabolic profile. Among three subtypes (α, γ and δ), we here consider the least investigated δ subtype to explore the molecular fingerprints of selective PPARδ agonists. Validated QSAR models (regression based 2D-QSAR, HQSAR and KPLS) and molecular docking with dynamics analyses support the inference of classification-based Bayesian and recursive models. Chemometric studies indicate that the presence of ether linkages and heterocyclic rings has optimum influence in imparting selective bioactivity. Pharmacophore models and docking with molecular dynamics analyses postulate the occurrence of aromatic rings, HB acceptor and a hydrophobic region as crucial molecular fragments for development of PPARδ modulators. Multi-chemometric studies suggest the essential structural requirements of a molecule for imparting potent and selective PPARδ modulation.

A convenient protocol for the efficient synthesis of aryloxycoumarins and (aryloxyimino)ethylcoumarins is described. The synthetic route developed involves the Cu-promoted C-O and N-O coupling reactions from readily available hydroxycoumarin and (hydroxyimino)ethylcoumarin derivatives in the presence of the catalytic system Cu(OAc)2/Et3N. By applying this condition, a series of arylboronic acids have been successfully reacted to afford the coupled products in fair to good yields.

Accelerated systemic free radical production poses a serious problem to healthy living. Since long, phenolic antioxidants have been studied for their ability to react with these toxic radicals. The present work deals with a series of substituted phenolic derivatives with a wide range of antioxidant property data. Quantitative structure–property relationship models have been developed correlating the antioxidant properties of these molecules with quantum chemical descriptors such as Mulliken charges of the common atoms and quantum topological molecular similarity indices of the common bonds. Models were developed based on the training set compounds, and were subsequently validated externally using the test set molecules. The results infer that substituents having a positive mesomeric effect increase the electron density over the phenolic oxygen and reduce the aromatic delocalisation of the lone pair of electron on the phenolic oxygen, thereby enabling effective interaction of the phenolic proton with the f...

In the present work, quantitative structure–activity relationship (QSAR) models have been built for a wide variety of antioxidant phenolic compounds obtained from traditional Chinese medicinal plants, with their Trolox equivalent antioxidant capacity measured using 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical and 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulphonic acid) radical (ABTS√+) assay methods. Non-linear models obtained using genetic partial least-squares technique were acceptable both in terms of internal and external predictivity. Validation of developed models using metrics and randomisation technique yielded results indicating the predictivity and robustness, respectively, of the developed models. The models signify that the presence of ketonic oxygen within the molecular structure favours their antioxidant activity. In addition, the number of hydroxyl groups, extent of branching, degree of methoxylation and the number of methyl and methylene substituents also dictate the antioxidant activity of...