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Recent years have witnessed a remarkable surge in the study of noncovalent interactions and their role in diverse areas of chemistry, biology, material science and allied fields. Among all, hydrogen bonding is quite extensively studied. Several other noncovalent interactions continue to attract wide attention. Notably, cation-π interactions play a crucial role in the function of several binding sites, reaction mechanisms, self-assemblies, catalytic mechanisms, adhesion and cohesion properties in many biological and chemical systems. The current review focuses on the character of cation-π interactions, its range and its occurrence from a conceptual point of view. The range and nature of cation-π interactions depend on the type of π-system and cation involved, besides solvent and environment. The size and polarizability of the π-systems and the effective nuclear charge on cation and its multiplicity and spin dictate the structural and energetic aspects of cation-π interaction. Further, factors affecting the modulation of strength and nature are brought out in the review. The interplay between the cation-π interaction and the other noncovalent interactions, solvent and counter-ion effects are analysed, and the cooperativity of these forces in organizing supramolecular architectures are discussed.Graphic AbstractHow strong is cation-π interaction depends on various factors: It may be weak, medium or strong depending on the nature of cation, π system and environment. The strength of the interaction was shown to alternate a few orders of magnitude depending on the environment.

Drug repurposing has emerged as an important strategy and it has a great potential in identifying therapeutic applications for COVID-19. An extensive virtual screening of 4193 FDA approved drugs has been carried out against 24 proteins of SARS-CoV2 (NSP1-10 and NSP12-16, envelope, membrane, nucleoprotein, spike, ORF3a, ORF6, ORF7a, ORF8, and ORF9b). The drugs were classified into top 10 and bottom 10 drugs based on the docking scores followed by the distribution of their therapeutic indications. As a result, the top 10 drugs were found to have therapeutic indications for cancer, pain, neurological disorders, and viral and bacterial diseases. As drug resistance is one of the major challenges in antiviral drug discovery, polypharmacology and network pharmacology approaches were employed in the study to identify drugs interacting with multiple targets and drugs such as dihydroergotamine, ergotamine, bisdequalinium chloride, midostaurin, temoporfin, tirilazad, and venetoclax were identified among the multi-targeting drugs. Further, a pathway analysis of the genes related to the multi-targeting drugs was carried which provides insight into the mechanism of drugs and identifying targetable genes and biological pathways involved in SARS-CoV2.

In silico methods of phenotypic screening are necessary to reduce the time and cost of the experimental in vivo screening of anticancer agents through dozens of millions of natural and synthetic chemical compounds. We used the previously developed PASS (Prediction of Activity Spectra for Substances) algorithm to create and validate the classification SAR models for predicting the cytotoxicity of chemicals against different types of human cell lines using ChEMBL experimental data. A training set from 59,882 structures of compounds was created based on the experimental data (IG50, IC50, and % inhibition values) from ChEMBL. The average accuracy of prediction (AUC) calculated by leave-one-out and a 20-fold cross-validation procedure during the training was 0.930 and 0.927 for 278 cancer cell lines, respectively, and 0.948 and 0.947 for cytotoxicity prediction for 27 normal cell lines, respectively. Using the given SAR models, we developed a freely available web-service for cell-line cytotoxicity profile prediction (CLC-Pred: Cell-Line Cytotoxicity Predictor) based on the following structural formula: http://way2drug.com/Cell-line/.

CRISPR/Cas is a breakthrough genome editing system because of its precision, target specificity, and efficiency. As a speed breeding system, it is more robust than the conventional breeding and biotechnological approaches for qualitative and quantitative trait improvement. Tomato ( Solanum lycopersicum L.) is an economically important crop, but its yield and productivity have been severely impacted due to different abiotic and biotic stresses. The recently identified SlHyPRP1 and SlDEA1 are two potential negative regulatory genes in response to different abiotic (drought and salinity) and biotic stress (bacterial leaf spot and bacterial wilt) conditions in S. lycopersicum L. The present study aimed to evaluate the drought, salinity, bacterial leaf spot, and bacterial wilt tolerance response in S. lycopersicum L. crop through CRISPR/Cas9 genome editing of SlHyPRP1 and SlDEA1 and their functional analysis. The transient single- and dual-gene SlHyPRP1 and SlDEA1 CRISPR-edited plants were phenotypically better responsive to multiple stress factors taken under the study. The CRISPR-edited SlHyPRP1 and SlDEA1 plants showed a higher level of chlorophyll and proline content compared to wild-type (WT) plants under abiotic stress conditions. Reactive oxygen species accumulation and the cell death count per total area of leaves and roots under biotic stress were less in CRISPR-edited SlHyPRP1 and SlDEA1 plants compared to WT plants. The study reveals that the combined loss-of-function of SlHyPRP1 along with SlDEA1 is essential for imparting significant multi-stress tolerance (drought, salinity, bacterial leaf spot, and bacterial wilt) in S. lycopersicum L. The main feature of the study is the detailed genetic characterization of SlDEA1 , a poorly studied 8CM family gene in multi-stress tolerance, through the CRISPR/Cas9 gene editing system. The study revealed the key negative regulatory role of SlDEA1 that function together as an anchor gene with SlHyPRP1 in imparting multi-stress tolerance in S. lycopersicum L. It was interesting that the present study also showed that transient CRISPR/Cas9 editing events of SlHyPRP1 and SlDEA1 genes were successfully replicated in stably generated parent-genome-edited line (GEd0) and genome-edited first-generation lines (GEd1) of S. lycopersicum L. With these upshots, the study’s key findings demonstrate outstanding value in developing sustainable multi-stress tolerance in S. lycopersicum L. and other crops to cope with climate change.

Thermus thermophilius isopropylmalate dehydrogenase catalyzes oxidative decarboxylation and dehydrogenation of isopropylmalate. Substitution of leucine to alanine at position 172 enhances the thermal stability among the known point mutants. Exploring the dynamic properties of non-covalent interactions such as saltbridges, hydrogen bonds and hydrophobic interactions to explain thermal stability of a protein is interesting in its own right. In this study dynamic changes in the non-covalent interactions are studied to decipher the deterministic features of thermal stability of a protein considering a case study of a point mutant in Thermus thermophilus isopropylmalate dehydrogenase. A total of four molecular dynamic simulations of 0.2 μs were carried out on wild type and mutant's functional dimers at 300 K and 337 K. Higher thermal stability of the mutant as compared to wild type is revealed by root mean square deviation, root mean square fluctuations and Cα-Cα distance with an increase in temperature from 300 K to 337 K. Most of the regions of wild type fluctuate higher than the corresponding regions of mutant with an increase in temperature. Cα-Cα distance analysis suggests that long distance networks are significantly affected in wild type as compared to the mutant. Short lived contacts are higher in wild type, while long lived contacts are lost at 337 K. The mutant forms less hydrogen bonds with water as compared to wild type at 337 K. In contrast to wild type, the mutant shows significant increase in unique saltbridges, hydrogen bonds and hydrophobic contacts at 337 K. The current study indicates that there is a strong inter-dependence of thermal stability on the way in which non-covalent interactions reorganize, and it is rewarding to explore this connection in single mutant studies.

The present study examines the conformational transitions occurring among the major structural motifs of Aurora kinase (AK) concomitant with the DFG-flip and deciphers the role of non-covalent interactions in rendering specificity. Multiple sequence alignment, docking and structural analysis of a repertoire of 56 crystal structures of AK from Protein Data Bank (PDB) has been carried out. The crystal structures were systematically categorized based on the conformational disposition of the DFG-loop [in (DI) 42, out (DO) 5 and out-up (DOU) 9], G-loop [extended (GE) 53 and folded (GF) 3] and αC-helix [in (CI) 42 and out (CO) 14]. The overlapping subsets on categorization show the inter-dependency among structural motifs. Therefore, the four distinct possibilities a) 2W1C (DI, CI, GE) b) 3E5A (DI, CI, GF) c) 3DJ6 (DI, CO, GF) d) 3UNZ (DOU, CO, GF) along with their co-crystals and apo-forms were subjected to molecular dynamics simulations of 40 ns each to evaluate the variations of individual residues and their impact on forming interactions. The non-covalent interactions formed by the 157 AK co-crystals with different regions of the binding site were initially studied with the docked complexes and structure interaction fingerprints. The frequency of the most prominent interactions was gauged in the AK inhibitors from PDB and the four representative conformations during 40 ns. Based on this study, seven major non-covalent interactions and their complementary sites in AK capable of rendering specificity have been prioritized for the design of different classes of inhibitors.

Characterization of a productive oil/gas well blowout through seismological methods is relatively uncommon. In this paper, we conduct an in-depth seismic evaluation of one of the world’s most significant onshore oil well blowout incidents, which occurred in 2020 at the Baghjan oil field in Assam, northeast India. We show that the blowout and related on-site activities generated distinct signals that can be distinguished by their spectral characteristics, temporal variation in geometric spreading, and sharp attenuation of daytime noise in comparison to the nighttime. A micro-earthquake potentially triggered by the blowout was also detected. Furthermore, we show how seismic data can be used to reasonably estimate blowout gas exit velocity and flame height. Our results demonstrate that a detailed characterization and spatiotemporal variation of blowout activity can be successfully captured through seismic monitoring, opening new opportunities for hazard mitigation and cost-effective disaster management for such catastrophic events.

Capsicum chinense Jacq. (ghost pepper), a naturally occurring chili species of Northeast India is known throughout the world for its high pungency and a pleasant aroma. The economic importance is due to the high capsaicinoid levels, the main source for pharmaceutical industries. The present study focused on identifying important traits necessary for increasing the yield and pungency of ghost pepper and to determine the parameters for the selection of superior genotypes. A total of 120 genotypes with more than 1.2% capsaicin content (>1,92,000 Scoville Heat Unit, w/w on dry weight basis) collected from different northeast Indian regions were subjected to variability, divergence and correlation studies. Levene’s homogeneity test of variance studied for three environments did not show significant deviation and so homogeneity of variance was reasonably met for analysis of variance study. Genotypic and phenotypic coefficient of variation was highest for fruit yield per plant (33.702, 36.200, respectively), followed by number of fruits per plant (29.583, 33.014, respectively) and capsaicin content (25.283, 26.362, respectively). The trait number of fruits per plant had maximum direct contribution to fruit yield per plant and the trait fruit yield per plant towards capsaicin content in the correlation study. High heritability with high genetic advance, which is the most favored selection criteria was observed for fruit yield per plant, number of fruits per plant, capsaicin content, fruit length and fruit girth. The genetic divergence study partitioned the genotypes into 20 clusters, where fruit yield per plant contributed maximum towards total divergence. Principal components analysis (PCA) studied to determine the largest contributor of variation showed 73.48% of the total variability, of which the PC1 and PC2 contributed 34.59% and 16.81% respectively.

In an effort to replace the widely used ruthenium metal complexes with low-cost, earth abundant iron complexes as photosensitizers for dye-sensitized solar cell (DSSC) applications, herein we report the computational design of heteroleptic iron complexes ( FC1–3 ) coordinated with benzimidazole-phenylcarbene (C^N) ligands. DFT and TDDFT calculations predicted the stronger σ-donating and π-accepting nature of phenyl carbene ligands substituted with electron-withdrawing CF 3 , donating –N(CH 3 ) 2 , and benzothiazine annulation than the imidazole carbene ligands ( FC4 ); consequently, the metal-ligand bond distances and interactions that influence the ordering of charge transfer states with respect to metal centered states are altered in FC1–3 complexes. Detailed analysis based on energy decomposition analysis, spin density distribution analysis, and ab initio ligand field theory parameters were enabled to understand the nature of heteroleptic ligand interactions with the rest of the metal complex. The results from the study shed light on the judicious choice of ligands, as the same non-innocent ligand that is experimentally proven as favorable for Ru-dyes ( TC1 ) is found to be detrimental for Fe-dyes ( FC1 ). Among the complexes studied, the FC3 complex is a promising sensitizer for DSSC with 1,3 MLCT energy level well separated from 3,5 MC, thereby preventing the deactivation of MLCT. The outcome of the study is therefore an important step toward the development of photosensitizers based on iron metal. Graphical abstract Potential photosensitzers based on earth-abundant, low cost iron metal have been designed for dye sensitized solar cell applications.

Exploring the new therapeutic indications of known drugs for treating COVID-19, popularly known as drug repurposing, is emerging as a pragmatic approach especially owing to the mounting pressure to control the pandemic. Targeting multiple targets with a single drug by employing drug repurposing known as the polypharmacology approach may be an optimised strategy for the development of effective therapeutics. In this study, virtual screening has been carried out on seven popular SARS-CoV-2 targets (3CLpro, PLpro, RdRp (NSP12), NSP13, NSP14, NSP15, and NSP16). A total of 4015 approved drugs were screened against these targets. Four drugs namely venetoclax, tirilazad, acetyldigitoxin, and ledipasvir have been selected based on the docking score, ability to interact with four or more targets and having a reasonably good number of interactions with key residues in the targets. The MD simulations and MM-PBSA studies showed reasonable stability of protein-drug complexes and sustainability of key interactions between the drugs with their respective targets throughout the course of MD simulations. The identified four drug molecules were also compared with the known drugs namely elbasvir and nafamostat. While the study has provided a detailed account of the chosen protein-drug complexes, it has explored the nature of seven important targets of SARS-CoV-2 by evaluating the protein-drug complexation process in great detail.Graphical abstractDrug repurposing strategy against SARS-CoV2 drug targets. Computational analysis was performed to identify repurposable approved drug candidates against SARS-CoV2 using approaches such as virtual screening, molecular dynamics simulation and MM-PBSA calculations. Four drugs namely venetoclax, tirilazad, acetyldigitoxin, and ledipasvir have been selected as potential candidates.