Prafulla B. Choudhari

Contemporary development in sequential Knoevenagel, Michael addition multicomponent reaction for the synthesis of 4-Aryl-5-oxo-5H-indeno[1,2-b]pyridine-3-carbonitrile

An uncatalyzed efficient synthesis of bioactive pyridine derivatives has been investigated for the first time by a three-component sequential multicomponent reaction tackled with aromatic aldehydes, malononitrile, and 1,3-indandione via Knoevenagel condensation followed by Michael addition. The difference between the domino multicomponent and sequential multicomponent reaction is emphasized by this methodology. The reaction proceeds at ambient temperature without frequently useful N-source like ammonium salt for the construction of N-heterocycles, which makes this protocol a novel synthetic route for the preparation of the indenopyridine skeleton.Graphical Abstract

Synthesis, Characterization and Quantification of Simvastatin Metabolites and Impurities

Simvastatin is used in treatment of hypercholesterolemia because it regulates cholesterol synthesis as a result of its β-hydroxy acid acting as an inhibitor of 3-hydroxy-methylglutaryl coenzyme A (HMG-CoA). The present communication deals with synthesis, characterization and development of accurate, precise and sensitive Reverse Phase High Performance Liquid Chromatography (RP-HPLC) method for simultaneous estimation of simvastatin and its synthetic impurities. The impurities methyl ether and β-hydroxy acid of simvastatin were synthesized in the laboratory and characterized by MS, NMR and FT-IR spectroscopy. The separation of simvastatin and its impurities was carried out on an isocratic JASCO RP-HPLC system using KYA TECH HIQ SIL C18 column (150 × 4.6 mm internal diameter, particle size 5 μm) operating at ambient temperature using acetonitrile:water (80:20 v/v) with 0.1% orthophosphoric acid as mobile phase. The method developed for HPLC analysis of three impurities along with simvastatin was validated using ICH Q2B (R1) guidelines and it complied with these guidelines. The results of analysis were found to be in the range of 98.14% to 101.89% for all analytes with acceptable accuracy and precision. The method can be used for detection and quantification of synthetic impurities in bulk or formulations of simvastatin.

Application of pocket modeling and k-nearest neighbor molecular field analysis (kNN-MFA) for designing of some anticoagulants: potential factor IXa inhibitors

The present communication deals with pharmacophore modeling, pocket modeling of the target site, and 3D QSAR analysis of 23 molecules of pyrazole-5-carboxamide from reported literature as factor IX inhibitors. The 3D QSAR analysis was carried out using k-nearest neighbor molecular field analysis (kNN-MFA) combined with various selection procedures. On the basis of QSAR analysis and pocket modeling data, a series of novel factor IXA inhibitors were designed, synthesized, and screened to validate the results of pharmacophore modeling and pocket modeling.

Potentially antibreast cancer enamidines via azide–alkyne–amine coupling and their molecular docking studies

An attempt to prepare a new triazole series by Cu catalyzed multicomponent reactions of tosyl azide, propargyl bromide and secondary amines led to the synthesis of enamidines. All the synthesized enamidines were evaluated for antiproliferative activities. The four molecules 4a–c and 4h showed higher anticancer activity with GI50 values less than the standard drug doxorubicin against human breast cancer cell line MCF-7. The virtual analysis ascertains the mode of action of these compounds via inhibition of human cell division protein kinase7 (CDK7).

Pharmacophore Identification and QSAR Studies on Substituted Benzoxazinone as Antiplatelet Agents: kNN-MFA Approach.

The three-dimensional quantitative structure–activity relationship (3D-QSAR) and pharmacophore identification studies on 28 substituted benzoxazinone derivatives as antiplatelet agents have been carried out. Multiple linear regression (MLR) method was applied for QSAR model development considering training and test set approaches with various feature selection methods. Stepwise (SW), simulated annealing (SA) and genetic algorithm (GA) were applied to derive QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. The results of pharmacophore identification studies showed that hydrogen bond accepters, aromatic and hydrophobic, are the important features for antiplatelet activity. The selected best 3D kNN-MFA model A has a training set of 23 molecules and test set of 5 molecules with validation (q2) and cross validation (pred_r2) values 0.9739 and 0.8217, respectively. Additionally, the selected best 3D QSAR (MLR) model B has a training set of 23 molecules and test set of 5 molecules with validation (r2) and cross validation (pred_r2) values of 0.9435 and 0.7663, respectively, and four descriptors at the grid points S_123, E_407, E_311 and H_605. The information rendered by 3D-QSAR models may lead to a better understanding and designing of novel potent antiplatelet molecules.

An efficient synthesis of flavanones and their docking studies with aldose reductase

A series of flavanone derivatives have been synthesized from 2-hydroxy acetophenone and benzaldehyde using fused calcium chloride in good to moderate yields, and their in vitro aldose reductase inhibitory activity has been tested on aldose reductase purified enzyme from Bovine lens. Most of the synthesized compounds exhibited potent aldose reductase inhibitory activity, and the obtained results are supported by the docking studies. Among the tested derivatives, 2, 3, 4-methoxy derivative 19 (IC50 5.88 ± 0.03 µM) exhibited the highest inhibitory activity whereas 2-methoxy derivative 12 showed the lowest, and the remaining compounds exhibited moderate activity with IC50 in the range of 6.09–7.89 µM. The spatial configuration of the most active derivative 19 was compared with pharmacophore requirements of the aldose reductase inhibitor site using a molecular modeling system.

Synthesis, antimycobacterial screening and molecular docking studies of 4-aryl-4′-methyl-2′-aryl-2,5′-bisthiazole derivatives

A series of 4-aryl-4′-methyl-2′-aryl-2,5′-bisthiazole derivatives (5a–o) were synthesized and screened for inhibitory activity against Mycobacterium tuberculosis H37Ra (ATCC 25177) and Mycobacterium bovis BCG (ATCC 35743) strains. Five lead compounds (5e, 5f, 5g, 5h, and 5o) were further confirmed from their dose dependent effect against MTB and Bovine–Calmette–Guerin. The most promising compounds 5f (MIC90: 11.32 µg/mL), 5h (MIC90: 11.59 µg/mL), and 5o (MIC90: 23.64 µg/mL) showed strong antitubercular activity against dormant MTB and BCG as well as almost insignificant cytotoxicity up to 100 µg/mL against HeLa, A549, and PANC-1 human cancer cell lines. Further, the synthesized compounds were found to have potential antibacterial activity against Gram-negative bacteria, Escherichia coli, Pseudomonas flurescence and Gram-positive bacteria, Staphylococcus aureus, Bacillus subtilis. Most of the synthesized compounds showed moderate activity against fungal strain Candida albicans. Molecular docking studies of these compounds showed significant interactions with crystal structure of the cytochrome P45014α-sterol demethylase (CYP51) PDB ID: 1E9X. Hydrogen bond interactions with SER261 and VAL395 are important interactions for selective inhibition of designed inhibitors. Compounds 5f, 5h, and 5o showed significant interactions with 1E9X. All the experimental results promote us to consider this series as a starting point for the development of novel, selective and more potent antitubercular agents in the future.

K Nearest Neighbor and 3D QSAR Analysis of Thiazolidinone Derivatives as Antitubercular Agents

Purpose : The present research communication describes development of kNN and 3D QSAR models for identification of structural features which are responsible for antimycobacterial activity of Thiazolidinone. Methodology/Approach : In the present work, two predictiveof kNN and 3D QSAR models were developed via utilization of multiple linear regression analysis. MLR analysis was carried out on reported dataset of thiazolidinone as Antimycobacterial. Vlife MDS 4.4 is utilized for development of kNN and 3D QSAR models which were validated via internal test set. Findings : Two different kNN and 3D QSAR models developed for dataset of thiazolidinone molecules as antimycobacterial. The Model A and Model B describes the best selected 3D QSAR model predicting antimycobacterial activity of the thiazolidinone derivatives. 3D QSAR model A is best selected model which indicates steric interaction fields needs to be minimized while electrostatic interaction field needs to be improved for potential increase in antimycobacterial activity. The Model C and D are two selected kNN models for anti-mycobacterial activity of the thiazolidinone derivatives. Model D is better fitted kNN model describing negative contribution of the electrostatic interaction fields and positive contribution of the steric interaction field. Original Value : The review of literature revealed QSAR analysis plays vital role in the development of the novel drug like candidates. Thiazolidinone derivatives were reported for their antimycobacterial potential but their quantitative measures were not reported. These facts prompted us to for development of QSAR models which will be utilized for development of potent and selective antimycobacterial agents. Conclusion : The study revealed that 3DQSAR model A and kNN model D better describes the antimycobacterial potential of the thiazolidinone derivatives. Substitution of the smaller groups on the aromatic ring bearing thiazolidinone nucleus will increase the antimycobacterial potential of the thiazolidinone derivatives.

Target Oriented Selective Synthesis of Antibacterial Active Tyrosinase Enzyme Inhibitor Coumarin Core Derivatives

Target oriented designs and selective synthesis of bioactive molecules with broad spectrum activity is a challenging job in the field of modern organic chemistry. Considering this opportunity herein, we report a highly competent selective synthesis of bioactive coumarin core derivative. Using computational drug design software only four selective antibacterial active derivatives was discovered and then synthesized. The efficiency of the synthesized compounds was scrutinized against bacterial pathogens such as P. vulgaris and B. megaterium. All the synthesized compounds showed better theoretical as well as practical results against selected pathogenic species. The minimum inhibitory concentration (MIC) values of the most active heterocycles were compared with that of ciprofloxacin. Results obtained in tyrocinase inhibition assay exactly correlate with MIC results and docking outcomes. The bioactivity of these type moieties provided a novel approach to develop new types of antibacterial drugs like entities effective against pathogens.

3D QSAR and Pharmacophore Modelling of some Pyrimidine Analogs as CDK4 Inhibitors

Cancer has a highest rate of mortality in the current decade. Breast cancer most prevalently observed cancer in recent years. In cancer, occurrence of corrupt cell cycle regulation leads to loss of orderly cell division. Over expression of cyclin-dependent kinases projects to carcinomas, amongst them CDK4 enzyme plays an important role in prevention of cancer. Nowadays, CDK4 is a major challenge in drug discovery to develop new anticancer agents. The present work deals with the 3D-QSAR and pharmacophore modelling of a series of pyrimidine analogs as CDK4 inhibitors.