Structural, material and antibacterial properties of quercetin incorporated soy protein isolate films and its binding behavior through molecular docking.

This study aimed to investigate the three different methods for the fabrication of quercetin (1%-3% w/w of protein) incorporated soy protein isolate (SPI) films and their effect on material properties. The quercetin incorporated SPI films prepared by these methods were characterized by Fourier transform infrared (FTIR) spectroscopy, UV-Vis spectrophotometer, tensile properties, and water uptake and leaching properties. The cross-linking pattern was revealed by the FTIR spectrum that showed formation of an ester group because of interaction between the quercetin hydroxyl group and the carboxyl side chain of SPI amino acids. The tensile strength of SPI films were enhanced with the addition of quercetin as it increased to a maximum of 6.17 MPa while neat SPI film had tensile strength 4.13 MPa. The prepared films exhibit significant antibacterial activity against Listeria monocytogenes and Escherichia coli. The In-silico docking analysis demonstrates that covalent and non-covalent forces play crucial roles in binding interaction. It shows the formation of four hydrogen bonds, two salt bridges along with one pi-alkyl interaction. The simulation studies reflect the crucial amino acid residues involved in SPI-quercetin binding. The effect of quercetin binding with SPI on its stability and compactness is revealed by Root mean square deviation (RMSD) and radius of gyration studies.

In-silico structural characterization and phylogenetic analysis of Nucleoside diphosphate kinase: A novel antiapoptotic protein of Porphyromonas gingivalis.

The Nucleoside diphosphate kinase (NDK) protein of Porphyromonas gingivalis (P. gingivalis) plays a crucial role in immune evasion and inhibition of apoptosis in host cells and has the potential to cause cancer. However, its structure has not yet been characterized. We used an in-silico approach to determine the 3D structure of the P. gingivalis NDK. Furthermore, structural characterization and functional annotation were performed using computational approaches. The 3D structure of NDK was predicted through homology modeling. The structural domains predicted for the model protein belong to the NDK family. Structural alignment of prokaryotic and eukaryotic NDKs with the model protein revealed the conservation of the domain region. Structure-based phylogenetic analysis depicted a significant evolutionary relationship between the model protein and the prokaryotic NDK. Functional annotation of the model confirmed structural homology, exhibiting similar enzymatic functions as NDK, including ATP binding and nucleoside diphosphate kinase activity. Furthermore, molecular dynamic (MD) simulation technique stabilized the model structure and provides a thermo-stable protein structure that can be used as a therapeutic target for further studies.

Mitigating human-wildlife conflict and monitoring endangered tigers using a real-time camera-based alert system.

The recovery of wild tigers in India and Nepal is a remarkable conservation achievement, but it sets the stage for increased human-wildlife conflict where parks are limited in size and where tigers reside outside reserves. We deployed an innovative technology, the TrailGuard AI camera-alert system, which runs on-the-edge artificial intelligence algorithms to detect tigers and poachers and transmit real-time images to designated authorities responsible for managing prominent tiger landscapes in India. We successfully captured and transmitted the first images of tigers using cameras with embedded AI and detected poachers. Notifications of tiger images were received in real time, approximately 30 seconds from camera trigger to appearing in a smart phone app. We review use cases of this AI-based real-time alert system for managers and local communities and suggest how the system could help monitor tigers and other endangered species, detect poaching, and provide early warnings for human-wildlife conflict.

Structure based High-Throughput Virtual Screening, Molecular Docking and Molecular Dynamics Study of anticancer natural compounds against fimbriae (FimA) protein of Porphyromonas gingivalis in oral squamous cell carcinoma.

Oral cancer is among the most common cancer in the world. Tobacco, alcohol, and viruses have been regarded as a well- known risk factors of OCC however, 15% of OSCC cases occurred each year without these known risk factors. Recently a myriad of studies has shown that bacterial infections lead to cancer. Accumulated shreds of evidence have demonstrated the role of Porphyromonas gingivalis (P. gingivalis) in OSCC. The virulence factor FimA of P. gingivalis activates the oncogenic pathways in OSCC by upregulating various cytokines. It also led to the inactivation of a tumor suppressor protein p53. The present Insilico study uses High-Throughput Virtual Screening, molecular docking, and molecular dynamics techniques to find the potential compounds against the target protein FimA. The goal of this study is to identify the anti-cancer lead compounds retrieved from natural sources that can be used to develop potent drug molecules to treat P.gingivalis-related OSCC. The anticancer natural compounds library was screened to identify the potential lead compounds. Furthermore, these lead compounds were subjected to precise docking, and based on the docking score potential lead compounds were identified. The top docked receptor-ligand complex was subjected to molecular dynamics simulation. A study of this insilico finding provides potent lead molecules which help in the development of therapeutic drugs against the target protein FimA in OSCC. Workflow of Structure based High-Throughput Virtual Screening, Molecular Docking and Molecular Dynamics Study of anticancer natural compounds against Fimbriae (FimA) protein of P. gingivalis in oral squamous cell carcinoma.

Oral isotretinoin with desloratadine compared with oral isotretinoin alone in the treatment of moderate to severe acne: a randomized, assessor-blinded study.

BACKGROUND: Our aim was to measure the effectiveness of oral isotretinoin with desloratadine compared with oral isotretinoin alone in treating moderate to severe acne at a tertiary care teaching hospital in North India. In this study, 90 patients with moderate to severe acne were enrolled to participate based on their fulfilling the inclusion criteria. METHODS: A randomized, assessor-blinded, parallel-arm study was conducted. Randomization was done using computer-generated tables to allocate treatments in a 1:1 ratio. A low-dose oral isotretinoin at a dose of 0.3 mg/kg/day with tab desloratadine at 5 mg/day was applied to the study group and compared against the same patients going without the dosage when controls were conducted. Follow-up was at 4, 8, and 12 weeks. RESULTS: The primary outcome was an improved global acne grading system (GAGS) score and decreased acne lesion count. SECONDARY OUTCOME: patient satisfaction with treatment. The 90 participants were randomized and 15 participants dropped out of the study, leaving 75 participants for intention to treat analysis (n = 41, n = 30). At week 12, the GAGS score and acne lesion count between the study and control groups were comparable (P > 0.05). Pruritus reported was 9.76% in the study versus 33.33% in the control group (P = 0.018). Also, 53.66% of participants reported "excellent" treatment satisfaction in the study group versus 36.67% in the control group. CONCLUSIONS: The addition of desloratadine to an isotretinoin regimen has a role in reducing disease and therapy-related pruritus in acne and leads to improved patient satisfaction.

'3D-QSAR-based, pharmacophore modelling, virtual screening, and molecular docking studies for identification of hypoxia-inducible factor-1 inhibitor with potential bioactivity.

Iron overload is a primary cause of vital organ failure in patients with blood transfusion-dependent beta-thalassemia, and the hypoxia-inducible factor-1 α (HIF-1α) plays an important role in iron homeostasis pathway. HIF-1α modulation as a potential therapeutic target approach for iron chelation in hepatocyte cells. In this study, we used a 3D quantitative structure-activity relationship (QSAR) analysis to predict the inhibitory activity of HIF-1α inhibitors for iron chelation in liver cells. These feature descriptors were used to build a 3D-QSAR model, which was validated using Cost analysis and Fischer's randomization test. The model was used to virtually search the chemical compound libraries for potential inhibitor candidates with least inhibitory activity. The High-throughput Docking (Libdock) approach was used to dock large repositories of chemical molecules. Following Libdock score screening, the protein-ligand poses were docked using docking optimization (Cdocker) method. Binding energy were calculated for the protein-ligand poses of lowest -Cdocker Energy and -Cdocker Interaction. Further, side chain hopping method was used to generate lead novel ligand from best hit pose of ligand. Molecular dynamics simulation study to evaluate the lead novel ligand. Our study demonstrates the utility of 3D-QSAR pharmacophore screening in predicting the inhibitory activity for target. Inhibition strategy for iron chelation provides an alternative routes for reducing the iron content.

In silico analysis highlighting the prevalence of BCL2L1 gene and its correlation to miRNA in human coronavirus (HCoV) genetic makeup.

The ongoing pandemic that resulted from coronavirus disease (COVID-19), which is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), had been spiraling out of control with no known antiviral drugs or vaccines. Due to the extremely serious nature of the disease, it has claimed many lives, with a mortality rate of 3.4% declared by the World Health Organization (WHO) on March 3, 2020. The aim of this study is to gain an understanding of the regulatory nature of the proteins involved in COVID-19 and to explore the possibility that microRNA (miRNA) could become a major component in the decoding of the virus. In the study, we were able to correlate the host protein gene BCL2L1 with miRNA miR-23b via network analysis. MiRNAs have previously been associated with the antiviral properties of various viral diseases, such as enterovirus 71 and hepatitis. They have been reported to act as antiviral regulators, since they are an integral component in the direct regulation of viral genes. MiRNAs are also capable of enabling the virus to avoid the host immune response by suppressing the IFN-α/ß signaling pathway or increasing the production of IFN-α/ß and as a result, inhibiting the viral infection. Here, we explain and shed light on the various correlations in the miRNA-gene-disease association that are seen in the host proteins of COVID-19.