Lead-Free Solid State Mechanochemical Synthesis of Cs2NaBi1-xFexCl6 Double Perovskite: Reduces Band Gap and Enhances Optical Properties.

Efficient and stable lead-free halide double perovskites (DPs) have attracted great attention for the future generation of electronic devices. Herein, we have developed a doping approach to incorporate Fe3+ ions into the Cs2NaBiCl6 crystal unit and reveal a crystallographic and optoelectronic study of the Cs2NaBi1-xFexCl6 double perovskite. We report a simple solid-state mechanochemical method that has a solvent-free, one-step, green chemistry approach for the synthesis of Cs2NaBi1-xFexCl6 phosphor. The analysis of powder X-ray diffraction (XRD) data determines the contraction of the lattice due to the incorporation of Fe3+ cations, and this effect is well supported by X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy (FE-SEM), Raman spectroscopy, and solid-state nuclear magnetic resonance spectroscopy (ss-NMR). The band gap is reduced with increasing Fe content owing to the strong overlap of the Fe-3d orbitals with Cl-3p orbitals and shift of the valence band maxima (VBM) toward higher energies, as confirmed by ultraviolet photoelectron spectroscopy (UPS) and density functional theory (DFT) analyses. Photoluminescence (PL) studies of Cs2NaBi1-xFexCl6 phosphors exhibit a large Stokes shift, broadband emission, and increased PL intensity more than ten times for 15% of Fe content phosphor with enhancement in the average decay lifetimes (up to 38 ns) compared to pristine Cs2NaBiCl6 DP. These results indicate that the transition of dark self-trapping of excitons (STEs) into bright STEs enhances yellow emission. XRD, UV, and thermo-gravimetric analysis (TGA) confirmed that the Cs2NaB1-xFexCl6 DPs have good structural and thermal stabilities. Our findings indicate that the doping of Fe3+ cations into the Cs2NaBiCl6 lattice is a constructive strategy to enhance significantly the optoelectronic properties of these phosphors.

Synthesis, Structural and Optical Properties of ZrBi2Se6 Nanoflowers: A Next-Generation Semiconductor Alloy Material for Optoelectronic Applications.

ZrBi2Se6 nanoflower-like morphology was successfully prepared using a solvothermal method, followed by a quenching process for photoelectrochemical water splitting applications. The formation of ZrBi2Se6 was confirmed by field emission scanning electron microscopy (FE-SEM), X-ray diffraction (XRD), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The estimated value of work function and band gap were found to be 5.5 and 2.26 eV measured using diffuse reflection spectroscopy and ultraviolet photoelectron spectroscopy, suggesting the potential candidate for water splitting. The highest current density of 9.7 µA/cm2 has been observed for the ZrBi2Se6 photoanode for the applied potential of 0.5 V vs SCE. The flat-band potential value was -0.46 V, and the 1.85 nm width of the depletion region is estimated from the Mott-Schottky (MS) analysis. It also reveals that the charge carrier density for the ZrBi2Se6 nanoflowers is 4.8 × 1015 cm-3. The negative slope of the MS plot indicates that ZrBi2Se6 is a p-type semiconductor. It was observed that ZrBi2Se6 nanoflowers had a high charge transfer resistance of ∼730 kΩ and equivalent capacitance of ∼40 nF calculated using electrochemical impedance spectroscopy (EIS) measurements. Using chronoamperometry, the estimated rise time and decay time were 50 ms and 0.25 s, respectively, which reveals the fast photocurrent response and excellent PEC performance of the ZrBi2Se6 photoanode. Furthermore, an attempt has been made to explain the PEC activity of ZrBi2Se6 nanoflowers using an energy band diagram. Thus, the initial results on ZrBi2Se6 nanoflowers appear promising for the PEC activity toward water splitting.

2D-QSAR modeling and two-fold classification of 1,2,4-triazole derivatives for antitubercular potency against the dormant stage of Mycobacterium tuberculosis.

The dormant or latent form of Mycobacterium tuberculosis (MTB) is not killed by the conventional antitubercular drugs. The treatment of latent TB is essential to reduce the period of treatment as well as incidences of drug resistance. In this background, we have made an attempt to develop the quantitative structure-activity relationship models (QSAR: regression and classification based) against the dormant form of MTB and later used the developed classifier models (linear discriminant analysis (LDA) and random forest (RF)) for the two-fold classifications. The logic of applying this concept of two-fold classification for the MTB modeling is to increase the confidence of correct classification. The 2D-QSAR modeling suggested the contribution of burden eigen, edge adjacency, van der Waals (vdW) surface area, topological charge, and pharmacophoric indices in predicting the antitubercular activity against the dormant MTB. The prediction qualities of the training and test sets were found to be moderate and good, according to the mean absolute error (MAE)-based criteria's. The LDA and RF models unveiled the importance of burden eigen, edge adjacency, Geary autocorrelation, and drug-like indices as discriminating features to differentiate the antitubercular compounds into higher and lower active groups. The LDA model showed the classification accuracies of 85.14% and 87.10% for the training and test sets, while the RF model exhibited the accuracies of 100.00% and 80.65% for both the sets. The descriptors selected in the final models are only two-dimensional (2D), which are easy to compute and does not require computationally expensive steps of structure conversion, optimization, and energy minimization mandatorily needed before the computation of 3D descriptors. These models could be used for identifying and selection of higher active compounds against the dormant form of the MTB.

Pharmacophore modeling of pretomanid (PA-824) derivatives for antitubercular potency against replicating and non-replicating Mycobacterium tuberculosis.

Pretomanid (PA-824) is the recently (2019) approved drug for the treatment of extensively drug-resistant (XDR) TB and the multidrug-resistant (MDR) TB by US FDA. The experimental data of antitubercular activity of 543 pretomanid derivatives (total 6 datasets) against replicating (active) and non-replicating (dormant) forms of Mycobacterium tuberculosis (strain H37Rv) are available in the literature. Such vast experimental data of pretomanid derivatives against both of these endpoints, and recent approval of pretomanid molecule as a drug encouraged us to utilize this existing experimental information for the development of the 3D-pharmacophore models. The developed model (Hypo-1, MABA) showed the three physicochemical features namely, the oxygen atom of nitro group (HBA_1), fused pyran ring of imidazopyran heterocycle (HYAl_2) and the 4-fluorophenyl moiety (HYAr_3) are crucial for the antitubercular activity against replicating M. tb. Subsequently, the pharmacophore model (Hypo-1, LORA) developed against the non-replicating form of M. tb also showed the contribution of three physicochemical features namely, the 4-tri-fluoromethyl group (HYAl_2) and both the phenyl groups (HYAr_3, HYAr_4) of biaryl moiety in increasing the antitubercular activity. Both the pharmacophoric classifier models showed the classification accuracies of 82.98 and 74.42% for the training set compounds, and 63.91 and 61.60% for the test set compounds respectively, for labelling the compounds into higher and lower active classes. Both the models were also found to be retaining the higher active compounds in top 1.00% of the total number of compounds (decoys and actives), after performing the decoy set screening. Communicated by Ramaswamy H. Sarma.

Computational Approaches as Rational Decision Support Systems for Discovering Next-Generation Antitubercular Agents: Mini-Review.

Tuberculosis, malaria, dengue, chikungunya, leishmaniasis etc. are a large group of neglected tropical diseases that prevail in tropical and subtropical countries, affecting one billion people every year. Minimal funding and grants for research on these scientific problems challenge many researchers to find a different way to reduce the extensive time and cost involved in the drug discovery cycle of these problems. Computer-aided drug design techniques have already been proved successful in the discovery of new molecules rationally by reducing the time and cost involved in the development of drugs. In the current minireview, we are highlighting on the molecular modeling studies published during 2010-2018 for target specific antitubercular agents. This review includes the studies of Structure-Based (SB) and Ligand-Based (LB) modeling and those involving Machine Learning (ML) techniques against different antitubercular targets such as dihydrofolate reductase (DHFR), enoyl Acyl Carrier Protein (ACP) reductase (InhA), catalase-peroxidase (KatG), enzyme antigen 85C, protein tyrosine phosphatases (PtpA and PtpB), dUTPase, thioredoxin reductase (MtTrxR), etc. The information presented in this review will help the researchers to get acquainted with the recent progress in the modeling studies of antitubercular agents.

Design of antimalarial transmission blocking agents: Pharmacophore mapping of ligands active against stage-V mature gametocytes of Plasmodium falciparum.

The discovery of transmission-blocking (T-B) agents is crucial for preventing and complete removal of malaria infection. However, most of the existing antimalarials are only active against the asexual stages of Plasmodium parasite, but ineffective against the sexual stage (gametocytes). In this background, we have developed pharmacophore models against the stage-V mature gametocytes of P. falciparum parasites. The pharmacophore model (Hypo-1) showed five pharmacophoric features namely, one hydrogen bond donor (HBD), one hydrophobic aliphatic (HYAl), one ring aromatic (RA), and two hydrophobic aromatic (HYAr) essential for the anti-gametocytic activity. The amino, methyl, fused phenyl ring of the quinazoline heterocycle, two phenyl rings of biphenyl moiety (HBD, HYAl, HYAr1, HYAr2 and RA) are the crucial features responsible for the non-specific anti-gametocytic activity (PfG). Subsequently, the model (Hypo-2) developed against the stage-V female gametocytes (PffG) showed the contribution of three pharmacophoric features namely, two hydrogen bond acceptor (HYA) and one RA required for the anti-gametocytic activity. The sulfhydryl, imine and pyridyl groups are observed to be essential for anti-gametocytic activity against female gametocytes. Both the models (PfG and PfGG) showed the classification accuracies of 78.26 and 71.64% for training set compounds and 60.80 and 60.18% for the test set compounds, respectively, for classification of compounds into higher and lower active classes. Also, both the models were found to retain the higher active compounds (IC50 <100 nM) in top 1% of total compounds (actives and decoys) as observed after screening the decoy set compounds. Communicated by Ramaswamy H Sarma.

Chemometric modeling of larvicidal activity of plant derived compounds against zika virus vector Aedes aegypti: application of ETA indices.

Dengue, zika and chikungunya have severe public health concerns in several countries. Human modification of the natural environment continues to create habitats in which mosquitoes, vectors of a wide variety of human and animal pathogens, thrive, which can bring about an enormous negative impact on public health if not controlled properly. Quantitative structure-activity relationship (QSAR) modeling has been applied in this work with the aim of exploring features contributing to promising larvicidal properties against the vector Aedes aegypti (Diptera: Culicidae). A dataset of 61 plant derived compounds reported in previous literature was used in this present study. A genetic algorithm (GA) was used for QSAR model development employing the "Double Cross Validation" (DCV) tool available at http://teqip.jdvu.ac.in/QSAR_Tools/. The DCV tool removes any bias in descriptor selection from a fixed composition of a training set and often provides an optimum solution in terms of predictivity. Simple topological descriptors, the "Extended Topochemical Atom" (ETA) indices developed by the present authors' group, were used for model development. These descriptors do not require pretreatment of molecular structures by conformational analysis or energy minimization before model development, thus saving computational time and resources. They also avoid ambiguities with respect to the existence of compounds in various conformational states leading to the loss of predictive capability in QSAR models. A number of models were generated from GA, and further, the descriptors appearing in the best model obtained from GA were subjected to partial least squares (PLS) regression to obtain the final robust model. The developed model was validated extensively using different validation metrics to check the reliability and predictivity of the model for enhancing confidence in QSAR predictions. Based on the insights obtained from the PLS model, we can conclude that the presence of hydrogen bond acceptor atoms, the presence of multiple bonds as well as sufficient lipophilicity and a limited polar surface area play crucial roles in regulating the activity of the compounds.

Understanding the structural requirements in diverse scaffolds for the inhibition of P. falciparum dihydroorotate dehydrogenase (PfDHODH) using 2D-QSAR, 3D-pharmacophore and structure-based energy- optimized pharmacophore models.

P. falciparum dihydroorotate dehydrogenase (PfDHODH) of the pyrimidine biosynthetic pathway offers a promising target for the development of antimalarial drugs in the scenario of widespread P. falciparum resistance. In this background, we have made an effort to decipher the structural requirements for the inhibition of PfDHODH using regression-based 2DQSAR, 3D-pharmacophore modeling and energy-based pharmacophoric (e-pharmacophore) studies. The 2D-QSAR and 3D-pharmacophore models were built from a structurally diverse set of 38 dihydrothiophenone derivatives, while the e-pharmacophore models were developed from two different co-crystal structures (PDB ID: 3O8A, 3I68) with varied scaffolds (benzimidazole, IC50: 22 nM and triazolopyrimidine, IC50: 56 nM) showing an inhibitory activity against the PfDHODH. The 2D-QSAR modeling study depicted the contribution of constitutional (number of oxygen atoms), spatial (molar volume), structural (number of rotatable bonds), and electronic (dipole moment) descriptors in predicting the PfDHODH inhibitory activity. The regression model showed the maximum contribution of constitutional descriptor (number of oxygen atoms representing the hydrogen bond acceptor feature) in determining the inhibitory activity. The best 3D-pharmacophore model (Hypo-1) with a correlation coefficient of 0.960 showed two hydrogen bond acceptor (HBA) and one ring aromatic (RA) features as the essential structural requirements for predicting the inhibitory activity. The e-pharmacophores derived from two different co-crystal structures highlighted the energy-based contribution of one hydrogen bond acceptor (e-HBA), one hydrogen bond donor (e-HBD) and three/four ring aromatic (e-RA) features for the inhibitory activity. The screening of external sets by the e-pharmacophores showed that both the models are capable of identifying the structurally diverse and potent compounds.

First report on two-fold classification of Plasmodium falciparum carbonic anhydrase inhibitors using QSAR modeling approaches.

Quantitative structure-activity relationship (QSAR)-based classification approach is one of the important chemometric tools in drug discovery process for categorizing the target protein inhibitors into more active and less active classes. In this background, we have presented here a novel approach of two-fold QSAR-based classification modeling for the Plasmodium falciparum carbonic anhydrase (PfCA) inhibitors using 2D-QSAR and linear discriminant analysis (LDA) methods. The logic of applying this concept is to ensure more accurate classification of compounds and to draw some concrete conclusion about structure-activity relations for further work, in absence of 3D-protein structure and lack of sufficient experimental data using the PfCA target. The 2D-QSAR modeling analysis suggested the importance of electrotopological, electronic, extended topochemical atom, and spatial (Jurs) indices for modeling the inhibitory activity against PfCA. The LDA model analysis showed that spatial (Jurs), electrotopological and thermodynamic indices were the discriminating features to differentiate the inhibitors into more active and less active groups. The classification ability of both the models for training and test sets was checked by different qualitative validation parameters such as sensitivity, specificity, accuracy, recall, precision, F-measure and G-means. The classification results revealed that the developed models were significant in classifying the more active inhibitors as compared to the less active inhibitors of both training and test sets. The structural features unveiled from these two models could be utilized for the selection of more active compounds against PfCA in the database screening process.

Classification SAR modeling of diverse quinolone compounds for antimalarial potency against Plasmodium falciparum.

Both a development of resistance to artemisinin monotherapy and lack of effective vaccine against malaria have created the urgent need for the development of new and efficient antimalarial agents. In this background, we have developed here a linear discriminant analysis (LDA) model and a few 3D-pharmacophore models for the classification of diverse quinolone compounds based on their antimalarial potency against Plasmodium falciparum. The discriminant model shows 70% correct classification for the test set compounds into higher active and lower active analogues. The best pharmacophore model (Hypo-1) with a correlation coefficient of 0.83 shows one hydrogen bond acceptor (HBA) and two ring aromatic (RA) features as the essential structural requirements for antimalarial activity against P falciparum. Both the models may act as in silico filters for a virtual screening and could be utilized for the selection of higher active molecules falling within the applicability of the models.

Dibenzylideneacetone analogues as novel Plasmodium falciparum inhibitors.

A series of dibenzylideneacetones (A1-A12) and some of their pyrazolines (B1-B4) were synthesized and evaluated in vitro for blood stage antiplasmodial properties in Plasmodium falciparum culture using SYBR-green-I fluorescence assay. The compound (1E, 4E)-1,5-bis(3,4-dimethoxyphenyl)penta-1,4-dien-3-one (A9) was found to be the most active with IC(50) of 1.97 µM against chloroquine-sensitive strain (3D7) and 1.69 µM against chloroquine-resistant field isolate (RKL9). The MTT based cytotoxicity assay on HeLa cell line has confirmed that A9 is selective in its action against malaria parasite (with a therapeutic index of 166). Our results revealed that these compounds exhibited promising antiplasmodial activities which can be further explored as potential leads for the development of cheaper, safe, effective and potent drugs against chloroquine-resistant malarial parasites.

Synthesis of novel alpha-pyranochalcones and pyrazoline derivatives as Plasmodium falciparum growth inhibitors.

Both the lack of a credible malaria vaccine and the emergence and spread of parasites resistant to most of the clinically used antimalarial drugs and drug combination have aroused an imperative need to develop new drugs against malaria. In present work, alpha-pyranochalcones and pyrazoline analogs were synthesized to discover chemically diverse antimalarial leads. Compounds were tested for antimalarial activity by evaluation of the growth of malaria parasite in culture using the microtiter plate based SYBR-Green-I assay. The (E)-3-(3-(2,3,4-trimethoxyphenyl)-acryloyl)-2H-chromen-2-one (Ga6) turned out to be the most potent analog of the series, showing IC(50) of 3.1 microg/ml against chloroquine-sensitive (3D7) strain and IC(50) of 1.1 microg/ml against chloroquine-resistant field isolate (RKL9) of Plasmodium falciparum. Cytotoxicity study of the most potent compounds was also performed against HeLa cell line using the MTT assay. All the tested compounds showed high therapeutic indices suggesting that they were selective in their action against the malaria parasite. Furthermore, docking of Ga6 into active site of falcipain enzyme revealed its predicted interactions with active site residues. This is the first instance wherein chromeno-pyrazolines have been found to be active antimalarial agents. Further exploration and optimization of this new lead could provide novel, antimalarial molecules which can ward off issues of cross-resistance to drugs like chloroquine.