Simplified molecular input line entry system-based optimal descriptors: QSAR modelling for voltage-gated potassium channel subunit Kv7.2

<div><p>CORAL software has been used to build quantitative structure–activity relationships (QSARs) for the prediction of binding affinities (pEC₅₀, i.e., minus decimal logarithm of the 50% effective concentration) of 35 potent inhibitors towards the voltage-gated potassium channel subunit Kv7.2. The pEC₅₀ has been modelled using eight random splits, with the following representations of the molecular structure: (i) hydrogen-suppressed graph (HSG); (ii) simplified molecular input line entry system (SMILES); (iii) graph atomic orbitals (GAOs) and (iv) hybrid representation, which is HSG together with SMILES. These models have been examined using three methods, the classic scheme, balance correlation, and balance correlation with ideal slope. The QSAR model based on single optimal descriptors using SMILES provided the best accuracy for the prediction of the pEC₅₀. The robustness of these models has been checked using parameters such as <i>r</i>_<i>m</i>², <i>r</i>^<i>*</i>_<i>m</i>², , and using a randomization technique. The best QSAR model based on single optimal descriptors has been applied to study the <i>in vitro</i> structure–activity relationships of pyrazolo[1,5-a]pyrimidin-7(4H)-one derivatives as Kv7.2 modulators. The pEC₅₀ is found to be significantly increased by the incorporation of –OH, –NO₂ or –Br groups in place of one –F, whereas –NH₂ has a negative effect on the pEC₅₀ values.</p></div

Simplified molecular input line entry system-based: QSAR modelling for MAP kinase-interacting protein kinase (MNK1)

<div><p>Quantitative structure–activity relationship (QSAR) models were built for the prediction of inhibition (<i>pIC</i>_<i>50</i>, i.e. negative logarithm of the 50% effective concentration) of MAP kinase-interacting protein kinase (MNK1) by 43 potent inhibitors. The <i>pIC</i>_<i>50</i> values were modelled with five random splits, with the representations of the molecular structures by simplified molecular input line entry system (SMILES). QSAR model building was performed by the Monte Carlo optimisation using three methods: classic scheme; balance of correlations; and balance correlation with ideal slopes. The robustness of these models were checked by parameters as <i>r</i>_<i>m</i>²<i>, r</i>^<i>*</i>_<i>m</i>²<i>,</i> and randomisation technique. The best QSAR model based on single optimal descriptors was applied to study <i>in vitro</i> structure–activity relationships of 6-(4-(2-(piperidin-1-yl) ethoxy) phenyl)-3-(pyridin-4-yl) pyrazolo [1,5-a] pyrimidine derivatives as a screening tool for the development of novel potent MNK1 inhibitors. The effects of alkyl group<i>,</i> –OH, –NO_2, F, Cl, Br, I, etc. on the <i>IC</i>_<i>50</i> values towards the inhibition of MNK1 were also reported.</p></div

Mechanical and morphological properties of halloysite nanotubes filled ethylene-vinyl acetate copolymer nanocomposites

184-191The EVA/HNTs nanocomposites have been synthesized by solution casting technique with 0, 2.5, 5.0, 7.5 and 10 phr HNTs loading. The mechanical properties, thermal decomposition, dynamic mechanical properties of these nanocomposites are reported. The scorch time, cure time and maximum torque increases marginally on the loading of HNTs; however the curing rate index decreases. The interactions between EVA matrix and filler HNTs are evaluated by the Fourier transform infrared spectroscopy (FTIR) study. The SEM images of cryogenically fractured EVA/HNTs nanocomposites show that the roughness of the fracture surface increases with the increase in HNTs loading. The effects of HNTs loading on tensile strength, elongation break and tensile modulus of these nanocomposites have also been reported. The tensile strength and elongation break of nanocomposites increases with increase in HNTs loading up to 5phr and afterwards a decreasing trend is observed. The tensile modulus shows an increasing trend up to 5phr and decreases up to 7.5phr HNTs loading. The good dispersion of HNTs into the EVA matrix is validated by SEM analysis. The tan δmax values of nanocomposites decreases up to 5phr HNTs loading and then increases which may be due to filler-filler interaction at higher HNTs loading

Simplified molecular-input line-entry system based quantitative structure–activity relationship (QSAR) models for serotonin 3 (5-HT₃) receptor

1322-1327Anxiety, emesis and cognition are regulated significantly by the Serotonin 3 (5-HT3) receptor, which are present in the central nervous system (CNS). Quantitative structure–activity relationship (QSAR) models have been built for the prediction of inhibitor constant (−log Ki) with the help 50 potent antagonists for the 5-hydroxytryptamine (5-HT3) receptor. The –log (Ki) values have been modelled with simplified molecular input line entry system (SMILES) based molecular structures. The external validation characteristics such as, the randomization parameters like crp2, rm2 , r*m2 , average rm2 needs to be more than 0.5 and for ∆rm2 if it is less than 0.2 then such models can be robust. All the five reported QSAR models have passed the external validation criteria test such as crp2, rm2, r*m2, average rm2 test and have proved their robustness

EVA/PZT-Composite-Based Triboelectric Nanogenerator for Energy Harvesting

The development of triboelectric nanogenerators (TENGs) has experienced rapid advancement in the past decade. In the present study, ethylene vinyl acetate (EVA) polymer and lead zirconium titanate (PZT) are taken as the host materials. The EVA–PZT elastomer composites are fabricated using different weight percentages (2.5%, 5.0%, 7.5%, and 10.0%) of PZT in EVA by solvent casting. The X-ray diffraction investigation of these films reveals the presence of the PZT material and the formation of composites. TENGs have the potential to revolutionize energy harvesting and provide a sustainable energy source for a variety of applications. The electrical output performance of the single-electrode-mode-based TENG is examined. The maximum output of 60 V and 165 nA is produced by the EVA–PZT 7.5 wt%/Al-based TENG device. Further, TENG is used to power devices and gather biomechanical energy. © 2023 Wiley-VCH GmbH.FALS

Hybrid nanogenerator for self-powered object recognition

Energy harvesting systems, including piezoelectric (PENG), triboelectric (TENG), and pyroelectric (PYNG) nanogenerator technologies, have emerged as one of the major future energy solutions. Energy harvesting eliminates the need for conventional batteries and encourages eco-friendly alternatives. This study reports hydrothermally synthesized BaTiO3 (BTO) particles with a tetragonal symmetry for hybrid energy harvesting. BTO particles are incorporated with PDMS at various wt% to form a flexible composite film. The 15 wt% BTO-PDMS composite/Al hybrid device (PENG-TENG) produces a peak voltage of 100 V, a current of 980 nA, and a charge of 17 nC, generating a peak power output of 33.64 μW at 100 MΩ. Furthermore, integrating this HNG (external hybridization) yielded an output of 101 V and 980 nA, demonstrating practical applicability. HNG is also employed to interact by touching various objects at different temperatures. The pyroelectric behavior of BTO allows direct thermal sensing of the object. The signals produced are processed using a convolutional neural network (CNN)-based object recognition system, which achieved a remarkable classification accuracy of 99.27% for various objects. External hybridization improves energy efficiency, representing a huge step forward in sustainable technology applications. This research paves the way for developing hybrid energy harvesters and can be employed further for extremely precise battery-free object recognition systems. This unique hybrid nanogenerator, which combines pyroelectric, piezoelectric, and triboelectric components, represents a new method of self-powered object detection. External hybridization improves energy efficiency, representing a huge step forward in sustainable technology applications