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SARS-CoV-2 has mutated many times among different populations. We analyzed wild-type spike protein and 18 different variants of SARS-CoV-2 spike protein known until the beginning of 2022 (alpha, beta, B.1.429, B.1.616, B.1.620, B.1.617.3, C.1.2, delta, epsilon, eta, gamma, iota, kappa, lambda, mu, omicron, theta, and zeta) for their interaction with 16 phytocompounds and remdesivir, resulting into 425 combinations. The largest number of mutations has been reported in the omicron followed by delta variant. However, the virulence of the delta variant has been reported higher as compared to omicron. Mutations at a few locations (D215G, K417N, E484K, N501Y, D614G, and P681H) were common in most of the variants. 3 D structures of all the 18 spike proteins were created using SWISS-MODEL to test the binding affinities with caffeine theophylline, emodin, vitexin, berberine, curcumin, piperine, quercetin, artemisinin, carvacrol, capsaicin, tetrahydrocannabinol, cannabidiol, α- pinene, β- pinene and gingerol. Phytocompounds and mutant variants were prepared using AutoDock 4.2.6 software. Binding affinities of the selected phytocompounds with the different mutant spike proteins were achieved using AutoDock Vina. Out of all combinations investigated, the best binding affinities were observed with 3 variants of SAR-CoV-2 with 5 phytocompounds along with remdesivir. The range of best binding energies varied from −9.1 to −8.0 kcal/mol. Further, MD simulation was done for selected 9 phytocompound-spike mutant complexes for analyzing the stability of interactions for 100 ns. ADMET studies via ProTox-II and SwissADME displayed that phytocompounds are safe and less toxic in comparison to remdesivir. Communicated by Ramaswamy H. Sarma

Hypertension has been a significant cause of death due to elevated blood pressure worldwide. The results of molecular docking showed out of selected 40 compounds, chasmanthin (-11.05 kcal/mol), and palmarin (-11.22 kcal/mol) showed strong binding with angiotensin-converting enzyme (ACE) target. The inhibitory action of the selected phytocompounds for ACE protein was also validated by comparing it with the reference drugs, lisinopril (-9.42 kcal/mol), and enalapril (-5.07 kcal/mol). MD simulations study of 100 ns also demonstrated stability of chasmanthin, and palmarin within the active sites of ACE protein. Molecular mechanics generalised born surface area (MMGBSA) analysis of MD trajectories exhibited significant binding of palmarin with ACE (dG Bind= −38.65 ± 2.59 kcal/mol) and chasmanthin (dG Bind= −37.64 ± 2.67 kcal/mol). Drug likeness and pharmacokinetics properties of palmarin and chasmanthin was also found to be permissible, thereby suggesting the use of chasmanthin and palmarin as a novel target inhibitor against ACE protein to combat hypertension.

Novel SARS-CoV-2, an etiological factor of Coronavirus disease 2019 (COVID-19), poses a great challenge to the public health care system. Among other druggable targets of SARS-Cov-2, the main protease (Mpro) is regarded as a prominent enzyme target for drug developments owing to its crucial role in virus replication and transcription. We pursued a computational investigation to identify Mpro inhibitors from a compiled library of natural compounds with proven antiviral activities using a hierarchical workflow of molecular docking, ADMET assessment, dynamic simulations and binding free-energy calculations. Five natural compounds, Withanosides V and VI, Racemosides A and B, and Shatavarin IX, obtained better binding affinity and attained stable interactions with Mpro key pocket residues. These intermolecular key interactions were also retained profoundly in the simulation trajectory of 100 ns time scale indicating tight receptor binding. Free energy calculations prioritized Withanosides V and VI as the top candidates that can act as effective SARS-CoV-2 Mpro inhibitors.

Since December 2019, coronavirus disease (COVID‐19) has claimed the lives of millions of people across the globe. To date, no medicine is available for the responsible virus SARS‐CoV‐2. 3CLpro, that is, 3‐chymotrypsin‐like protease, the main protease (Mpro), has an important role in cleaving pp1a and pp1ab polyproteins. This Mpro serves as an important target in drug designing against COVID‐19. Herein, the study includes the investigation, screening, and identification of potent leads from (Withania sps.), against SARS‐CoV‐2, using virtual screening, molecular docking, and molecular dynamics (MD) simulations. Seventy‐three natural compounds from this important medicinal plant were screened. The Binding affinity was used to identify the most probable target to inhibit the Mpro, compounds 27‐hydroxywithanolide F (W32, −11.5 kcal/mol), withanolide A (W56, −11.4 kcal/mol), and withacoagulin H (W30, −11.1 kcal/mol) showed highest binding energy. Lipinski's rule, followed by drug‐likability and likeness screening, resulted in 36 molecules. Further, MD simulation of 50 ns predicted withacoagulin H possessing strong binding affinity and hydrogen‐bonding interactions with the active site. The binding free energy calculation showed the most negative energy of withacoagulin H (−63.463 KJ/mol) compared to other selected compounds. The study also compared the bonding energy of already reported repurposed and newly synthesized drugs. Further, absorption, distribution, metabolism, and excretion predictions were made to found a good balance of potency. Hence the following screened compounds from Withania sps. could serve as the potential leads for drug development against COVID‐19.

Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype that lacks hormonal receptors. This reduces the therapeutic options for TNBC patients creating more focus on chemotherapy. Drug resistance has posed as a major hurdle in treating TNBC patients. Deregulation of drug transporter proteins is one of major factors that cause resistance to chemotherapeutic drugs. In this study, ABCC6 a drug transporter protein that is found dysregulated in several resistant cancer cells has been docked with natural compounds or phytochemicals with known anti-cancer activities. Subtrifloralactone G, a withanolide extracted from Deprea subtriflora is found to show highest binding energy with ABCC6 protein. Molecular dynamics simulations further prove the stability of the ABCC6 protein- Subtrifloralactone G ligand complex. ADMET analysis shows that phytochemical Subtrifloralactone G can be used as an anti-cancer therapeutic drug in treating resistant cancer cells. The study mainly focuses on the role of phytochemicals in treating resistant TNBC cells.

Receptor-based QSAR approaches can enumerate the energetic contributions of amino acid residues toward ligand binding only when experimental binding affinity is associated. The structural data of protein-ligand complexes are witnessing a tremendous growth in the Protein Data Bank deposited with a few entries on binding affinity. We present here a new approach to compute the Energetic CONTributions of Amino acid residues and its possible Cross-Talk (ECONTACT) to study ligand binding using per-residue energy decomposition, molecular dynamics simulations and rescoring method without the need for experimental binding affinity. This approach recognizes potential cross-talks among amino acid residues imparting a nonadditive effect to the binding affinity with evidence of correlative motions in the dynamics simulations. The protein-ligand interaction energies deduced from multiple structures are decomposed into per-residue energy terms, which are employed as variables to principal component analysis and generated cross-terms. Out of 16 cross-talks derived from eight datasets of protein-ligand systems, the ECONTACT approach is able to associate 10 potential cross-talks with site-directed mutagenesis, free energy, and dynamics simulations data strongly. We modeled these key determinants of ligand binding using joint probability density function (jPDF) to identify cross-talks in protein structures. The top two cross-talks identified by ECONTACT approach corroborated with the experimental findings. Furthermore, virtual screening exercise using ECONTACT models better discriminated known inhibitors from decoy molecules. This approach proposes the jPDF metric to estimate the probability of observing cross-talks in any protein-ligand complex. The source code and related resources to perform ECONTACT modeling is available freely at https://www.gujaratuniversity.ac.in/econtact/.

Coronaviruses (CoVs) belong to a group of RNA viruses that cause diseases in vertebrates including. Newer and deadlier than SARS CoV-2 are sought to appear in future for which the scientific community must be prepared with the strategies for their control. Spike protein (S-protein) of all the CoVs require angiotensin-converting enzyme2 (ACE2), while CoVs also require hemagglutinin-acetylesterase (HE) glycoprotein receptor to simultaneously interact with O-acetylated sialic acids on host cells, both these interactions enable viral particle to enter host cell leading to its infection. Target inhibition of viral S-protein and HE glycoprotein receptor can lead to a development of therapy against the SARS CoV-2. The proposition is to recognize molecules from the bundle of phytochemicals of medicinal plants known to possess antiviral potentials as a lead that could interact and mask the active site of, HE glycoprotein which would ideally bind to O-acetylated sialic acids on human host cells. Such molecules can be addressed as 'HE glycoprotein blockers'. A library of 110 phytochemicals from

The aim of the present study was to test the binding affinity of methylxanthines (caffeine/theine, methylxanthine, theobromine, theophylline and xanthine) to three potential target proteins namely Spike protein (6LZG), main protease (6LU7) and nucleocapsid protein N-terminal RNA binding domain (6M3M) of SARS-CoV-2. Proteins and ligand were generated using AutoDock 1.5.6 software. Binding affinity of methylxanthines with SARS-CoV-2 target proteins was determined using Autodock Vina. MD simulation of the best interacting complexes was performed using GROMACS 2018.3 (in duplicate) and Desmond program version 2.0 (academic version) (in triplicate) to study the stabile interaction of protein-ligand complexes. Among the selected methylxanthines, theophylline showed the best binding affinity with all the three targets of SARS-CoV-2 (6LZG - 5.7 kcal molThe online version contains supplementary material available at 10.1007/s40495-021-00276-3.

The assessment of major organ toxicities through in silico predictive models plays a crucial role in drug discovery. Computational tools can predict chemical toxicities using the knowledge gained from experimental studies which drastically reduces the attrition rate of compounds during drug discovery and developmental stages. The purpose of in silico predictions for drug leads and anticipating toxicological endpoints of absorption, distribution, metabolism, excretion and toxicity, clinical adverse impacts and metabolism of pharmaceutically active substances has gained widespread acceptance in academia and pharmaceutical industries. With unrestricted accessibility to powerful biomarkers, researchers have an opportunity to contemplate the most accurate predictive scores to evaluate drug’s adverse impact on various organs. A multiparametric model involving physico-chemical properties, quantitative structure-activity relationship predictions and docking score was found to be a more reliable predictor for estimating chemical toxicities with potential to reflect atomic-level insights. These in silico models provide informed decisions to carry out in vitro and in vivo studies and subsequently confirms the molecules clues deciphering the cytotoxicity, pharmacokinetics, and pharmacodynamics and organ toxicity properties of compounds. Even though the drugs withdrawn by USFDA at later phases of drug discovery which should have passed all the state-of-the-art experimental approaches and currently acceptable toxicity filters, there is a dire need to interconnect all these molecular key properties to enhance our knowledge and guide in the identification of leads to drug optimization phases. Current computational tools can predict ADMET and organ toxicities based on pharmacophore fingerprint, toxicophores and advanced machine-learning techniques.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was declared as a global emergency in January 2020 due to its pandemic outbreak. To examine this Coronavirus disease 2019 (COVID-19) effects various data are being generated through different platforms. This study was focused on the clinical data of COVID-19 which relied on python programming. Here, we proposed a machine learning approach to provide a insights into the COVID-19 information. PySpark is a machine learning approach which also known as Apache spark an accurate tool for the searching of results with minimum time intervals as compare to Hadoop and other tools. World Health Organization (WHO) started gathering corona patients’ data from last week of the February 2020. On March 11, 2020, the WHO declared COVID-19 a global pandemic. The cases became more evident and common after mid-March. This paper used the live owid (our world in data) dataset and will analyse and find out the following details on the live COVID-19 dataset. (1) The daily Corona virus scenario on various continents using PySpark in microseconds of Processor time. (2) After the various antibodies have been implemented, how they impact new cases on a regular basis utilizing various graphs. (3) Tabular representation of COVID-19 new cases in all the continents.

The viral particle, SARS-CoV-2 is responsible for causing the epidemic of Coronavirus disease 2019 (COVID-19). To combat this situation, numerous strategies are being thought for either creating its antidote, vaccine, or agents that can prevent its infection. For enabling research on these strategies, several target proteins are identified where, Spike (S) protein is of great potential. S-protein interacts with human angiotensin-converting-enzyme-2 (ACE2) for entering the cell. S-protein is a large protein and a portion of it designated as a receptor-binding domain (RBD) is the key region that interacts with ACE2, following to which the viral membrane fuses with the alveolar membrane to enter the human cell. The hypothesis is to identify molecules from the pool of anticancer phytochemicals as a lead possessing the ability to interact and mask the amino acids of RBD, making them unavailable to form associations with ACE2. Such a molecule is termed as 'fusion inhibitor'. We hypothesized to identify fusion inhibitors from the NPACT library of anticancer phytochemicals. For this, all the molecules from the NPACT were screened using molecular docking, the five top hits (Theaflavin, Ginkgetin, Ursolic acid, Silymarin and Spirosolane) were analyzed for essential Pharmacophore features and their ADMET profiles were studied following to which the best two hits were further analyzed for their interaction with RBD using Molecular Dynamics (MD) simulation. Binding free energy calculations were performed using MM/GBSA, proving these phytochemicals containing anticancer properties to serve as fusion inhibitors.Communicated by Ramaswamy H. Sarma.

The novel SARS-CoV-2 is an etiological factor that triggers Coronavirus disease in 2019 (COVID-19) and tends to be an imminent occurrence of a pandemic. Out of all recognized solved complexes linked to SARS-CoV, Main protease (Mpro) is considered a desirable antiviral phytochemical that play a crucial role in virus assembly and possibly non-interactive capacity to adhere to any viral host protein. In this research, SARS-CoV-2 MPro was chosen as a focus for the detection of possible inhibitors using a variety of different analytical methods such as molecular docking, ADMET analysis, dynamic simulations and binding free energy measurements. Virtual screening of known natural compounds recognized Withanoside V, Withanoside VI, Racemoside B, Racemoside A and Shatavarin IX as future inhibitors of SARS-CoV-2 MPro with stronger energy binding. Also, simulations of molecular dynamics for a 100 ns time scale showed that much of the main SARS-CoV-2 MPro interactions had been maintained in the simulation routes. Binding free energy calculations using the MM/PBSA method ranked the top five possible natural compounds that can act as effective SARS-CoV-2 MPro inhibitors.

Wild thyme (Thymus serpyllum L.) of family Laminaceae is an unexplored perennial medicinal shrub. Aerial part of this plant is traditionally used for the treatment of respiratory and gastrointestinal problems. The current study was designed to evaluate the GC-MS, antimicrobial and synergistic potential of T. serpyllum essential oil (TEO). Chemical characterization of TEO showed the presence of thymol (15.79%), Phenol, 2-(1,1-dimethylethyl) (11.55%), o-Cymene (10.96%) as major phytocompounds. Antimicrobial activity of TEO in terms zone of inhibition (ZOI) varied from 13.66 ± 0.58 mm to 33.66 ± 1.52 mm, while, thymol (10%, v/v) showed ZOI ranged from 15.5 ± 0.5 mm to 26.33 ± 2.08 mm against tested bacterial and fungal species. MIC of TEO was 0.039% to 0.078% against tested bacterial and fungal species, whereas, thymol showed 1.25% to 2.5% MIC against tested bacterial and fungal species. Different combinations of TEO (2MIC to ½MIC) and thymol (2MIC to ½MIC) with antibacterial and antifungal antibiotics (2MIC to ½MIC) were found to increase the efficacy of antibiotics by 4-130 folds against bacterial and fungal pathogens. Molecular docking showed the good binding of thymol with both bacterial and fungal targets. Whereas MD simulation showed the stability of thymol complexed with target proteins over 100 ns time scale. Thymol also fulfills the Lipinski rule and showed characteristics similar to that of drugs. Therefore, it can be concluded from the present study that TEO and its major phytocompound, thymol can act as a bioactivity enhancer of antibacterial and antifungal antibiotics and could be used as a potential candidate to fight against antimicrobial drug resistance. Communicated by Ramaswamy H. Sarma

Cymbopogon citratus (DC.) Stapf is an aromatic perennial herb of Gramineae (Poaceae) family and is known for its application in food and healthcare industry. The present study aimed to evaluate anti-inflammatory and antioxidant potential of C. citratus essential oil (CEO) through in vitro and in silico studies. Chemical characterization of CEO was done using Gas chromatography-mass spectrophotometry (GC-MS) method. In vitro antioxidant activity was evaluated by 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and ferric ion reducing antioxidant power (FRAP) assays, while egg albumin denaturation method was used to evaluate in vitro anti-inflammatory activity of CEO. Molecular docking investigation of major phytocompounds of CEO was done using Autodock vina software against human peroxiredoxin 5 (PDB ID: 1HD2) and human cyclooxygenase 2 (PDB ID: 5IKQ) proteins, which were further analyzed through molecular dynamics (MD) simulation using YASARA. GC-MS analysis of CEO showed the presence of geranial (48%) neral (34.04%), ��-myrcene (9.77%), geraniol (1.88%), linalool (0.84%), isogeranial (0.81%), ��-caryophyllene (0.80%), D-limonene (0.51%) as major constituents. CEO showed significant antioxidant activity with DPPH (IC50-47.53 �� 2.16 ��g/ml), FRAP (IC50-30.7 �� 0.31 ��M), and ABTS assays (IC50-27.87 �� 0.09 ��g/ml). CEO also exhibited significant in-vitro anti-inflammatory activity with IC50-29.71 �� 1.95 ��g/ml as compared to that of Diclofenac sodium (IC50-36.52 �� 1.95 ��g/ml). Molecular docking revealed that ��-caryophyllene showed considerable binding potential with human peroxiredoxin 5 receptor (-6.0 kcal/mol) and human cyclooxygenase 2 receptor (-10.1 kcal/mol). Further, MD simulations demonstrated considerable and stable interactions of ��-caryophyllene with 1HD2 and 5IKQ proteins up to 100 ns. Drug-likeness and ADME/T features also showed that ��-caryophyllene can be used as a potential candidate to replace the synthetic anti-inflammatory drugs with side effects and also act as natural antioxidants. Communicated by Ramaswamy H. Sarma

Novel severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has claimed more than 3.3 million lives worldwide and still counting. As per the GISAID database, the genomics of SARS-CoV-2 has been extensively studied, with more than 500 genome submissions per day. Out of several hotspot mutations within the SARS-CoV-2 genome, recent research has focused mainly on the missense variants. Moreover, significantly less attention has been accorded to delineate the role of the untranslated regions (UTRs) of the SARS-CoV-2 genome in the disease progression and etiology. One of the most frequent 5’ UTR variants in the SARS-CoV-2 genome is the C241T, with a global frequency of more than 95 %. In the present study, the effect of the C241T mutation has been studied with respect to the changes in RNA structure and its interaction with the host replication factors MADP1 Zinc finger CCHC-type and RNA-binding motif 1 (hnRNP1). The results obtained from molecular docking and molecular dynamics simulation indicated weaker interaction of C241T mutant stem-loops with the host transcription factor MADP1, indicating a reduced replication efficiency. The results are also correlated with increased recovery rates and decreased death rates of global SARS-CoV-2 cases.

Background: Bioinformatics and statistical analysis have been employed to develop a classification model to distinguish toxic and non-toxic molecules. Aims: The primary objective of this study is to enumerate the cut-off values of various physico-chemical (ligand-centric) and target interaction (receptor-centric) descriptors which forms the basis for classifying cardiotoxic and non-toxic molecules. We also sought correlation of molecular docking, absorption, distribution, metabolism, excretion, and toxicology (ADMET) parameters, Lipinski rules, physico-chemical parameters, etc. of human cardiotoxicity drugs. Methods: A training and test set of 91 compounds were applied to linear discriminant analysis (LDA) using 2D and 3D descriptors as discriminating variables representing various molecular modeling parameters to identify which function of descriptor type is responsible for cardiotoxicity. Internal validation was performed using the leave-one-out cross-validation methodology ensuing in good results, assuring the stability of the discriminant function (DF). Results: The values of the statistical parameters Fisher Discriminant Analysis (FDA) and Wilk’s λ for the DF showed reliable statistical significance, as long as the success rate in the prediction for both the training and the test set attained more than 93% accuracy, 87.50% sensitivity and 94.74% specificity. Conclusion: The predictive model was built using a hybrid approach using organ-specific targets for docking and ADMET properties for the FDA (Food and Drug Administration) approved and withdrawn drugs. Classifiers were developed by linear discriminant analysis and the cut-off was enumerated by receiver operating characteristic curve (ROC) analysis to achieve reliable specificity and sensitivity.

The pandemic outbreak of COVID-19 virus (SARS-CoV-2) has become critical global health issue. The biophysical and structural evidence shows that SARS-CoV-2 spike protein possesses higher binding affinity towards angiotensin-converting enzyme 2 (ACE2) and hemagglutinin-acetylesterase (HE) glycoprotein receptor. Hence, it was selected as a target to generate the potential candidates for the inhibition of HE glycoprotein. The present study focuses on extensive computational approaches which contains molecular docking, ADMET prediction followed by molecular dynamics simulations and free energy calculations. Furthermore, virtual screening of NPACT compounds identified 3,4,5-Trihydroxy-1,8-bis[(2R,3R)-3,5,7-trihydroxy-3,4-dihydro-2H-chromen-2-yl]benzo[7]annulen-6-one, Silymarin, Withanolide D, Spirosolane and Oridonin were interact with high affinity. The ADMET prediction revealed pharmacokinetics and drug-likeness properties of top-ranked compounds. Molecular dynamics simulations and binding free energy calculations affirmed that these five NPACT compounds were robust HE inhibitor.

The pandemic outbreak of COVID-19 virus (SARS-CoV-2) has become critical global health issue. The biophysical and structural evidence shows that SARS-CoV-2 spike protein possesses higher binding affinity towards angiotensin-converting enzyme 2 (ACE2) and hemagglutinin-acetylesterase (HE) glycoprotein receptor. Hence, it was selected as a target to generate the potential candidates for the inhibition of HE glycoprotein. The present study focuses on extensive computational approaches which contains molecular docking, ADMET prediction followed by molecular dynamics simulations and free energy calculations. Furthermore, virtual screening of NPACT compounds identified 3,4,5-Trihydroxy-1,8-bis[(2R,3R)-3,5,7-trihydroxy-3,4-dihydro-2H-chromen-2-yl]benzo[7]annulen-6-one, Silymarin, Withanolide D, Spirosolane and Oridonin were interact with high affinity. The ADMET prediction revealed pharmacokinetics and drug-likeness properties of top-ranked compounds. Molecular dynamics simulations and binding free energy calculations affirmed that these five NPACT compounds were robust HE inhibitor.

The design and creation of thiacalixphenyl[4]arene tetraacetohydrazide (TPTAH) has been utilized for the construction of palladium nanoparticles (PdNps). The molecular modelling studies give an insight into the surface properties of TPTAH capped PdNps. The plausible reduction mechanism of Pd(II) to Pd(0) is due to the presence of hydrazide group on the periphery. The charge transfer for this reduction was initiated by the carbonyl group and N-atom. TPTAH behaves as a reducing and stabilizing agent for the formation of catalytically active TPTAH-PdNps that were characterized by UV-Vis spectroscopy, selected area electron diffraction (SAED), transmission electron microscopy (TEM), and powder X-ray diffraction. The TPTAH-PdNps with size 4 ± 2 nm were found to be catalytically active for C–C cross-coupling reactions such as the Suzuki–Miyaura, Heck, and Stille reactions. TPTAH-PdNps are superior to the conventional Pd catalyst in terms of yield, catalyst loading, reaction time, and recyclability.

The functionalized molecules with specific molecular sites appear to be a promising approach for detection of cation in UV–visible and fluorescence spectroscopy. The synthesized receptor 4-((5-methylfuran-2-yl)methylene)hydrazono)methyl)phenol MFMHMP was found selective for La3+ among Ag+, K+, Na+, Be2+, Mg2+, Ca2+, Eu3+, Al3+, La3+, Zr4+, Th4+, UO22+, Fe3+, Fe2+, Co2+, Ni2+, Cu2+, Zn2+, Cd2+ and Hg2+ metal ions used as their nitrates by UV–visible spectroscopy and fluorescence spectroscopy. The binding nature of MFMHMP with La3+ ion was analyzed by UV–visible, fluorescence, IR, mass spectroscopy and cyclic voltammetric studies. The stoichiometry was established to be 1:1 by Benesi-Hildebrand, mole-ratio method and method of continuous variation (Job's method) with good association affinity K = 6.245 × 104 M−1. Computational studies and Density functional theory (DFT) calculation gives the proof of electron transfer during excitation and emission. Binding energy of complex through Density Function Theory −62.387 kcal/mol has also indication of strong binding. The electron transfer energy of Higher occupied molecular orbital (HOMO) to Lower unoccupied molecular orbital (LUMO) is about 4.662 eV for MFMHMP+La3+ Complex. Among that all transitions HOMO → LUMO + 8 and HOMO → LUMO + 9 play a key role for the blue shift transition during complexation.

Epidermal growth factor receptors (EGFRs) are transmembrane receptors present on cell membranes, play an important role in controlling cell growth, apoptosis and other cellular functions. They have...

Bisphenol A (BPA), a phenyl ring containing synthetic xenoestrogen, is widely used in the manufacture of polycarbonate plastics, epoxy resins and as a non-polymer additive to other plastics. Food is considered as the main source of exposure to BPA as it leaches out from food containers as well as surface coatings. It causes toxicity in the liver, kidney, brain, and other organs by initiating the process of lipid peroxidation. The present investigation was an attempt to evaluate the effect of BPA on steroidogenesis and its amelioration by quercetin. Inbred Swiss strain male albino mice were orally administered with 80, 120 and 240 mg per kg body weight per day of BPA for 45 days. The results revealed that BPA causes significant (p < 0.05) and dose-dependent changes in the body weight and biochemical parameters like protein, cholesterol and lipid contents as well as activities of 3β-and 17β-hydroxysteroid dehydrogenases in the testis of mice. It was also found to significantly reduce the testosterone level in serum. Oral administration of quercetin (30, 60 and 90 mg per kg body weight per day) along with a high dose of BPA (240 mg per kg body weight per day) for 45 days caused significant amelioration in the body weight and steroidogenesis as compared to the BPA alone treated group. The effect was dose-dependent. This amelioration in BPA-induced toxicity might be due to the antioxidative properties of quercetin. The reduction in the function of enzymes was confirmed by in silico bindings. BPA and quercetin show competitive binding with steroidogenic enzymes as well as binding with each other. This could be a possible mechanism to reduce the toxic effect of BPA which has been supported by molecular dynamics simulations for molecular level recognition with structural insights.

Bisphenol A (BPA) is an endocrine disruptor of xenobiotic type, mainly used for the production of polycarbonate plastic, epoxy resins and non-polymer additives. Because of its wide usages in the environment, the toxic effects of BPA have proved to be harmful to human health. However, its effects on human haemoglobin remain unclear. The affinity between BPA and haemoglobin, as well as erythrocytes, is an important factor in understanding the mechanism of the toxicity of BPA. Flavonoids are strong antioxidants that prevent oxidative stress and Quercetin is a flavonoid found in numerous vegetables and fruits. Therefore, the present investigation was undertaken to investigate whether Quercetin can be used to alleviate the toxic effects of BPA in vitro in human red blood cells (RBC). Venous blood samples were collected from healthy, well-nourished adult volunteers (25-30 years old) by phlebotomy. In a RBC suspension with a cell density of 2 × 104 cell per mL, the concentration of BPA (25-150 µg mL-1) was found to cause an increase in the lipid peroxidation (LPO) and a decrease in the activities of superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPX) in human RBC. However, the concurrent addition of BPA (150 µg mL-1) and quercetin (10-50 µg mL-1) lead to significant amelioration. In silico studies gave structural insight into BPA and quercetin to decipher the plausible binding mechanism and molecular level recognition.

A new fluorescent thiacalix[4]arene dinaphthalene sulfonate (TCDNS) was synthesized by a reaction of thiacalix[4]arene with naphthalene sulfonyl chloride. TCDNS was characterized by 1H-NMR, 13C-NMR, and ESI-MS spectrometric analyses. The selectivity of fluoroionophore was analyzed for 4-nitrotoluene (4-NT) and 2,3-dinitrotoluene (2,3-DNT) among various nitroaromatic compounds (NACs) using the spectrofluorimetric technique. 4-NT and 2,3-DNT behave as the strong emission quenchers for TCDNS. The information about the complexation of TCDNS with 4-NT and 2,3-DNT was revealed by ESI-MS and 1H NMR analysis. A standard addition method was used for the detection of 4-NT and 2,3-DNT in a water sample. The complex formation in the cases of TCDNS⊃4-NT and TCDNS⊃2,3-DNT has been demonstrated by molecular docking and dynamics simulation techniques.

Alzheimer's disease (AD) is one of the most significant neurodegenerative disorders and its symptoms mostly appear in aged people. Catechol-o-methyltransferase (COMT) is one of the known target enzymes responsible for AD. With the use of 23 known inhibitors of COMT, a query has been generated and validated by screening against the database of 1500 decoys to obtain the GH score and enrichment value. The crucial features of the known inhibitors were evaluated by the online ZINC Pharmer to identify new leads from a ZINC database. Five hundred hits were retrieved from ZINC Pharmer and by ADMET (absorption, distribution, metabolism, excretion, and toxicity) filtering by using FAF-Drug-3 and 36 molecules were considered for molecular docking. From the COMT inhibitors, opicapone, fenoldopam, and quercetin were selected, while ZINC63625100_413 ZINC39411941_412, ZINC63234426_254, ZINC63637968_451, and ZINC64019452_303 were chosen for the molecular dynamics simulation analysis having high binding affinity and structural recognition. This study identified the potential COMT inhibitors through pharmacophore-based inhibitor screening leading to a more complete understanding of molecular-level interactions.

The traditional drug design strategy centrally focuses on optimizing binding affinity with the receptor target and evaluates pharmacokinetic properties at a later stage which causes high rate of attrition in clinical trials. Alternatively, parallel screening allows evaluation of these properties and affinity simultaneously. In a case study to identify leads from natural compounds with experimental HIV-1 reverse transcriptase (RT) inhibition, we integrated various computational approaches including Caco-2 cell permeability QSAR model with applicability domain (AD) to recognize drug-like natural compounds, molecular docking to study HIV-1 RT interactions and shape similarity analysis with known crystal inhibitors having characteristic butterfly-like model. Further, the lipophilic properties of the compounds refined from the process with best scores were examined using lipophilic ligand efficiency (LLE) index. Seven natural compound hits viz. baicalien, (+)-calanolide A, mniopetal F, fagaronine chloride, 3,5,8-trihydroxy-4-quinolone methyl ether derivative, nitidine chloride and palmatine, were prioritized based on LLE score which demonstrated Caco-2 well absorption labeling, encompassment in AD structural coverage, better receptor affinity, shape adaptation and permissible AlogP value. We showed that this integrative approach is successful in lead exploration of natural compounds targeted against HIV-1 RT enzyme.

A new Tetra-Methoxy Resorcinarene-N-(2-ethyl) Phthalimide (TMRN2Ph) has been synthesized for the selective and sensitive recognition of 4-nitrotoluene (4-NT) among various nitroaromatic compounds (NACs) by using a spectrofluorimetric method. Strong quenching in the fluorescence intensity of TMRN2Ph was displayed upon the addition of 4-NT in the linear concentration range of 50 µM to 1 mM. The complexation between TMRN2Ph and 4-NT is supported by ESI-MS and 1H NMR analysis. The complex of TMRN2Ph with 4-NT has been investigated by computational methods such as molecular docking and molecular dynamics to determine the binding interactions and conformational changes. The detection of 4-NT from a water sample has also been performed successfully.

Thiacalix[4]arene based fluorescent sensor bearing two naphthoyl groups, thiacalix-1-naphthalene carboxylate (TCNC) has been synthesized and characterized by 1H NMR, 13C NMR, FTIR, ESI-MS spectroscopic techniques. The interaction behavior of TCNC with various metal ions like Fe3+, Hg2+, Co2+, Ni2+, Cu2+, Cd2+, Pb2+, Mg2+, K+, Na+, and Zn2+ was studied by UV-visible and emission spectrophotometry. It was observed that TCNC recognizes Zn2+ ions with high selectivity and sensitivity. The enhancement of fluorescence intensity due to presence of Zn2+ ions was not perturbed in the presence of high concentration of other associated metal ions. The 1:1 stoichiometry of TCNC:Zn2+ complex was confirmed by job's plot, ESI-MS study and 1H NMR titration. The binding constant and quantum yield were also calculated by using spectrofluorimetric titration data. Linear detection range of zinc ions was found to be 1 nM–740 nM. Furthermore, molecular docking study was performed to evaluate the binding affinity and possible interactions between TCNC and Zn2+ depicting that TCNC interact with Zn2+ via weak intramolecular forces. In addition to that molecular dynamics has also been performed to evaluate the conformational changes and it's structural stability in the particular environment.

Murraya koenigii (Linn.) Spreng, commonly known as curry leaf tree, is popular as a condiment and spice among Asian countries. Ethnobotanical studies suggest that certain phytochemicals in different parts of the plant are involved in anti-inflammatory, anti-oxidant and anti-cancer activities. There is a knowledge gap in connecting the ethnobotanical applications of M. koenigii, identification of chief phytochemicals through computational approaches and and evaluation of phytochemical’s effect on cancer cell lines. We present here a comprehensive study to identify the phytochemicals responsible for anti-inflammation using random forest (RF) models, the interactions with COX-1 and COX-2 enzymes using molecular docking, dynamics simulation and free energy calculations. The RF models prioritised four phytochemicals viz. girinimbine, murrayanine, murrastinine-B and mukolidine with COX-1 and COX-2 binding potential. These phytochemicals developed key contacts with COX targets which were largely retained in the trajectories of the dynamics simulations. Phytochemicals ranking based on the binding free energy suggested that girinimbine (a carbazole alkaloid) is selective towards COX-2 supported by the experimental studies on COX anti-inflammation. Cytotoxicity assessment on the breast cancer cell line MDA-MB-231 illustrated that the presence of this phytochemical in root, stem and leaf (IC50 value: 0.006 µg/ml) parts highlight its role as a COX-2 inhibitor.