Molecular docking analysis of HSV-1 proteins models with synthetic and plant derived compounds.

The atomic resolution model of US9, UL20, and gH protein of HSV is known. Hence, the ligand protein interaction of the US9, UL20, and gH protein models were carried out with synthetic drugs like acyclovir, bexarotene, vinorelbine, foscarnet, famciclovir, cidofovir and two plant derived natural drug acacetin and anthraquinone. Based on structure and docking study, it is predicted that protein US20 and gH binds with particular anti-HSV drug i.e. acyclovir, cidofovir, acacetin and famciclovir, acacetin respectively, while interaction of different protein is different with drugs.

The use of Multispectral Radio-Meter (MSR5) data for wheat crop genotypes identification using machine learning models.

Satellite remote sensing is widely being used by the researchers and geospatial scientists due to its free data access for land observation and agricultural activities monitoring. The world is suffering from food shortages due to the dramatic increase in population and climate change. Various crop genotypes can survive in harsh climatic conditions and give more production with less disease infection. Remote sensing can play an essential role in crop genotype identification using computer vision. In many studies, different objects, crops, and land cover classification is done successfully, while crop genotypes classification is still a gray area. Despite the importance of genotype identification for production planning, a significant method has yet to be developed to detect the genotypes varieties of crop yield using multispectral radiometer data. In this study, three genotypes of wheat crop (Aas-'2011', 'Miraj-'08', and 'Punjnad-1) fields are prepared for the investigation of multispectral radio meter band properties. Temporal data (every 15 days from the height of 10 feet covering 5 feet in the circle in one scan) is collected using an efficient multispectral Radio Meter (MSR5 five bands). Two hundred yield samples of each wheat genotype are acquired and manually labeled accordingly for the training of supervised machine learning models. To find the strength of features (five bands), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Nonlinear Discernment Analysis (NDA) are performed besides the machine learning models of the Extra Tree Classifier (ETC), Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), k Nearest Neighbor (KNN) and Artificial Neural Network (ANN) with detailed of configuration settings. ANN and random forest algorithm have achieved approximately maximum accuracy of 97% and 96% on the test dataset. It is recommended that digital policymakers from the agriculture department can use ANN and RF to identify the different genotypes at farmer's fields and research centers. These findings can be used for precision identification and management of the crop specific genotypes for optimized resource use efficiency.

An in silico approach unveils the potential of antiviral compounds in preclinical and clinical trials as SARS-CoV-2 omicron inhibitors.

The increased transmissibility and highly infectious nature of the new variant of concern (VOC) that is severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron and lack of effective therapy need the rapid discovery of therapeutic antivirals against it. The present investigation aimed to identify antiviral compounds that would be effective against SARS-CoV-2 Omicron. In this study, molecular docking experiments were carried out using the recently reported experimental structure of omicron spike protein in complex with human angiotensin-converting enzyme 2 (ACE2) and various antivirals in preclinical and clinical trial studies. Out of 36 tested compounds, Abemaciclib, Dasatinib and Spiperone are the three top-ranked molecules which scored binding energies of -10.08 kcal/mol, -10.06 kcal/mol and -9.54 kcal/mol respectively. Phe338, Asp339, and Asp364 are crucial omicron receptor residues involved in hydrogen bond interactions, while other residues were mostly involved in hydrophobic interactions with the lead molecules. The identified lead compounds also scored well in terms of drug-likeness. Molecular dynamics (MD) simulation, essential dynamics (ED) and entropic analysis indicate the ability of these molecules to modulate the activity of omicron spike protein. Therefore, Abemaciclib, Dasatinib and Spiperone are likely to be viable drug-candidate molecules that can block the interaction between the omicron spike protein and the host cellular receptor ACE2. Though our findings are compelling, more research into these molecules is needed before they can be employed as drugs to treat SARS-CoV-2 omicron infections.

Insights into plastome of Fagonia indica Burm.f. (Zygophyllaceae): organization, annotation and phylogeny.

The enhanced understanding of chloroplast genomics would facilitate various biotechnology applications; however, the chloroplast (cp) genome / plastome characteristics of plants like Fagonia indica Burm.f. (family Zygophyllaceae), which have the capability to grow in extremely hot sand desert, have been rarely understood. The de novo genome sequence of F. indica using the Illumina high-throughput sequencing technology determined 128,379 bp long cp genome, encode 115 unique coding genes. The present study added the evidence of the loss of a copy of the IR in the cp genome of the taxa capable to grow in the hot sand desert. The maximum likelihood analysis revealed two distinct sub-clades i.e. Krameriaceae and Zygophyllaceae of the order Zygophyllales, nested within fabids.

In silico analyses of major active constituents of fingerroot (Boesenbergia rotunda) unveils inhibitory activities against SARS-CoV-2 main protease enzyme.

Boesenbergia rotunda (L.) Mansf., commonly known as fingerroot is a perennial herb in the Zingiberaceae family with anticancer, anti-leptospiral, anti-inflammatory, antioxidant, antiulcer, and anti-herpes viral activities. While the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibitory activity of B. rotunda extract has been recently found, the active compounds contributing to this activity are yet unknown. The main protease (Mpro) enzyme is one of the most well established therapeutic targets among coronaviruses which plays a vital role in the maturation and cleavage of polyproteins during viral replication. The current work aims to identify active phytochemical substances from B. rotunda extract that can inhibit the replication of SARS-CoV-2 by using a combined molecular docking and dynamic simulation approaches. The virtual screening experiment revealed that fifteen molecules out of twenty-three major active compounds in the plant extract have acceptable drug-like characteristics. Alpinetin, Pinocembrin, and Pinostrobin have binding energies of -7.51 kcal/mol, -7.21 kcal/mol, and -7.18 kcal/mol, respectively, and can suppress Mpro activity. The stability of the simulated complexes of the lead compounds with the drug-receptor is demonstrated by 100-ns MD simulations. The binding free energies study utilizing molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and molecular mechanics generalized Born surface area (MM-GBSA) show that the compounds and Mpro enzyme have favourable thermodynamic interactions, which are majorly driven by van der Waals forces. Thus, the selected bioactive phytochemicals from B. rotunda might be used as anti-SARS-CoV-2 candidates that target the Mpro enzyme.

Identification of SARS-CoV-2 inhibitors from extracts of Houttuynia cordata Thunb.

Houttuynia cordata Thunb., a perennial herb belonging to the Saururaceae family is a well-known ingredient of Traditional Chinese medicine (TCM) with several therapeutic properties. During the severe acute respiratory syndrome (SARS) outbreak in China, it was one of the approved ingredients in SARS preventative formulations and therefore, the plant may contain novel bioactive chemicals that can be used to suppress the replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a virus for which there are currently no effective drugs available. Like all RNA viruses, SARS-CoV-2 encode RNA-dependent RNA polymerase (RdRp) enzyme which aids viral gene transcription and replication. The present study is aimed at understanding the potential of bioactive compounds from H. cordata as inhibitors of the SARS-CoV-2 RdRp enzyme. We investigated the drug-likeness of the plant's active constituents, such as alkaloids, polyphenols, and flavonoids, as well as their binding affinity for the RdRp enzyme. Molecular docking experiments show that compounds 3 (1,2,3,4,5-pentamethoxy-dibenzo-quinolin-7-one), 14 (7-oxodehydroasimilobine), and 21 (1,2-dimethoxy-3-hydroxy-5-oxonoraporphine) have a high affinity for the drug target and that the complexes are maintained by hydrogen bonds with residues like Arg553, Cys622 and Asp623, as well as hydrophobic interactions with other residues. The lead compounds' complexes with the target enzyme remained stable throughout the molecular dynamics simulation. Analysis of molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) and molecular mechanics generalized Born surface area (MM-GBSA) revealed the key residues contributing considerably to binding free energy. Thus, the findings reveal the potential of H. cordata bioactive compounds as anti-SARS-CoV-2 drug candidate molecules against the target enzyme.

Plastome data analysis of Cucumis melo subsp.agrestis.

It is of interest to refine the taxonomic status of C. melo ssp. agrestis using its plastome data. The chloroplast size and GC% was found to be 1,56,016 bp and 36.92% respectively in Cucumis melo subsp. agrestis. The plastome of C. melo subsp. agrestis comprises of two inverted repeat (IR) regions of 25,797 bp each. It consisted of 133 genes with 88 protein-coding genes, 8 rRNA genes and 37 tRNA genes. Analysis of the C. melo ssp. agrestis plastome data will help breeders to improve the yield the crop.

Temperature-enabled reversible "On/Off" switch-like hazardous herbicide picloram voltammetric sensor in agricultural and environmental samples based on thermo-responsive PVCL-tethered MWCNT@Au catalyst.

Picloram (PCR), a vastly utilized chlorinated herbicide, is very stable in water and soil with severe ecological and health impacts. It is necessary to establish a fast and highly sensitive technique for accurately detecting trace level PCR in agricultural and environmental samples. We employed a temperature-responsive poly(N-vinylcaprolactam)-tethered multiwalled carbon nanotubes (MWCNT-PVCL) decorated gold nanoparticles (Au@MWCNT-PVCL) catalyst on the electrochemical sensor for the sensitive "On/Off" switch-like detection of PCR. The effect of temperature-sensitive catalyst surface chemistry on electrocatalytic activity was scrutinized. Results showed that the hydrophilic surface of PVCL at 25 °C (LCST) that immensely upgraded PCR oxidation on the catalyst in the electrochemical reaction, signifying the "On" state. The detection of the Au@MWCNT-PVCL modified electrode ranged from 0.02-183 µM with a low detection limit (LOD) of 1.5 nM at 40 °C toward PCR. The proposed sensor was successfully used to detect PCR in real agricultural and environmental samples.

High-performance SERS detection of pesticides using BiOCl-BiOBr@Pt/Au hybrid nanostructures on styrofoams as 3D functional substrate.

A 3D flexible domestic waste styrofoam is reported as a surface enhanced Raman scattering (SERS) substrate loaded with BiOCl-BiOBr@Pt/Au semiconductor-plasmonic composites. The hydrothermally prepared BiOCl-BiOBr nanocomposite is thoroughly characterized for its crystal structure using X-Ray diffraction, morphology through scanning electron microscopy, and electronic states of the elements using X-ray photoelectron spectroscopy. The alpha cypermethrin (ACM) is chosen as a model pesticide analyte for SERS investigation. The BiOCl-BiOBr@Pt/Au loaded foam substrate exhibited a high enhancement factor (106) and low limit of detection (10-10 M) upon SERS investigation. The unique architecture of the semiconductor-plasmonic composite enables an efficient charge transfer capability and plasmonic hotspots which aids in the enhancement of target analytes. In order to better demonstrate the versatility towards other pesticides, SERS detection of glyphosate and paraquat pesticides are also performed using the fabricated SERS substrate. The stability of the substrate has been investigated in detail for 30 days and the substrate was highly stable. The BiOCl-BiOBr@Pt/Au-based foam substrate also performed well in rapid real-time sensing of alpha cypermethrin on the kiwi fruit exocarp at lower level concentrations. Graphical abstract.

Structure-based virtual screening of phytochemicals and repurposing of FDA approved antiviral drugs unravels lead molecules as potential inhibitors of coronavirus 3C-like protease enzyme.

Coronaviruses are enveloped positive-strand RNA viruses belonging to family Coronaviridae and order Nidovirales which cause infections in birds and mammals. Among the human coronaviruses, highly pathogenic ones are Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) and the Middle East Respiratory Syndrome coronavirus (MERS-CoV) which have been implicated in severe respiratory syndrome in humans. There are no approved antiviral drugs or vaccines for the treatment of human CoV infection to date. The recent outbreak of new coronavirus pandemic, coronavirus disease 2019 (COVID-19) has caused a high mortality rate and infections around the world which necessitates the need for the discovery of novel anti-coronaviral drugs. Among the coronaviruses proteins, 3C-like protease (3CLpro) is an important drug target against coronaviral infection as the auto-cleavage process catalysed by the enzyme is crucial for viral maturation and replication. The present work is aimed at the identification of suitable lead molecules for the inhibition of 3CLpro enzyme via a computational screening of the Food and Drug Administration (FDA) approved antiviral drugs and phytochemicals. Based on binding energies and molecular interaction studies, we shortlisted five lead molecules (both FDA approved drugs and phytochemicals) for each enzyme targets (SARS-CoV-2 3CLpro, SARS-CoV 3CLpro and MERS-CoV 3CLpro). The lead molecules showed higher binding affinity compared to the standard inhibitors and exhibited favourable hydrophobic interactions and a good number of hydrogen bonds with their respective targets. A few promising leads with dual inhibition potential were identified among FDA approved antiviral drugs which include DB13879 (Glecaprevir), DB09102 (Daclatasvir), molecule DB09297 (Paritaprevir) and DB01072 (Atazanavir). Among the phytochemicals, 11,646,359 (Vincapusine), 120,716 (Alloyohimbine) and 10,308,017 (Gummadiol) showed triple inhibition potential against all the three targets and 102,004,710 (18-Hydroxy-3-epi-alpha-yohimbine) exhibited dual inhibition potential. Hence, the proposed lead molecules from our findings can be further investigated through in vitro and in vivo studies to develop into potential drug candidates against human coronaviral infections.

Ultrasonic preparation and nanosheets supported binary metal oxide nanocomposite for the effective application towards the electrochemical sensor.

Binary metal oxides (La2O3@SnO2) decorated reduced graphene oxide nanocomposite was synthesized by ultrasound process in an environmentally benign solvent with a working frequency of 25 and 40 kHz (6.5 l200 H, Dakshin, India and maximum input power 210 W). Further, to enhance the electrocatalytic activity, the reduced graphene oxide (rGO) was prepared from graphene oxide by ultrasonication method. As prepared La2O3@SnO2/rGO was scrutinized using XRD, TEM, EDX and quantitative test for the structural and morphology properties. As modified La2O3@SnO2/rGO nanocomposite exhibits better electrochemical activity towards the oxidation of methyl nicotinate with higher anodic current compared to other modified and unmodified electrode for the detection of methyl nicotinate with larger linear range (0.035-522.9 µM) and lower limit of detection (0.0197 µM). In addition, the practical feasibility of the sensor was inspected with biological samples, reveals the acceptable recovery of the sensor in real samples.

The potential of antioxidant activity of methanolic extract of Coscinium fenestratum (Goetgh.) Colebr (Menispermaceae).

To explore the possible bioactive compounds and to study the antioxidant capacity of Coscinium fenestratum (Goetgh.) Colebr (Menispermaceae), the qualitative and quantitative phytochemical screening for various secondary metabolites were evaluated. Using the GC-MS analysis, a total number of 30 phytochemical compounds were predicted with their retention time, molecular weight, molecular formula, peak area, structure and activities. The most prevailing heterocyclic compound was Bis(2,4,6- triisopropylphenyl) phosphinicazide (6.70%). The antioxidant activity was evaluated by spectrophotometric methods using the reducing power assay and the DPPH• and ABTS•+ scavenging assays. The activity was determined to be increased in all the test samples with the increase in the volume of the extract. C. fenestratum possess a good source of many bioactive compounds that are used to prevent diseases linked with oxidative stress.

Molecular authentication of Anthemis deserti Boiss. (Asteraceae) based on ITS2 region of nrDNA gene sequence.

The dried plant material of medicinally important Anthemis deserti Boiss. (family: Asteraceae) especially when it remains in the powdered form often look similar to Anthemis melampodina Del.; and therefore, difficult to distinguish, finally lead to chances of adulteration. The adulteration in medicinal plants effects on the efficacy of the drugs. The molecular authentication of herbal plant materials such as based on the internal transcribed spacer 2 (ITS2) sequences of nuclear ribosomal DNA (nrDNA) is considered as more reliable method compared to other the biochemical or histological methods. The present study aims to molecular authentication ofA. deserti based on molecular phylogenetic analyses of ITS2 gene sequence of nrDNA region. The ITS2 region of nrDNA of A. deserti were sequenced, and the molecular phylogenetic analyses were performed together with the GenBank sequences. The Maximum Parsimony tree revealed the close relationships of A. deserti with A. melampodina; however, the Neighbor-Joining and Maximum Likelihood tree clearly revealed that A. deserti is distinct from A. melampodina, which is also supported by the differences in nucleotides at five diffident positions (i.e. 22, 28, 87, 175 and 198) in the DNA sequence alignment.