Immunoinformatics approach for designing a universal multiepitope vaccine against Chandipura Virus.

Chandipura vesiculovirus (CHPV) is a fast-emerging virus that causes acute encephalitis with a high death rate. Because of its extensive prevalence in African and Asian countries, this infection has become a global hazard, and there is an urgent need to create an effective and non-allergenic vaccine or appropriate treatment to combat it. A vaccine candidate is offered utilizing a computational technique in this study. To build a potential vaccine candidate, viral protein sequences were acquired from the National Center for Biotechnology Information database and evaluated with several bioinformatics techniques to identify B-cell and T-cell epitopes. V1 was shown to be superior in terms of various physicochemical qualities, as well as highly immunogenic and non-allergic. Molecular docking revealed that the CHPV vaccine construct had a greater binding affinity with human Toll-like receptors (TLR-3 and TLR-8) and that it was stable in molecular dynamics simulations. MEC-CHPV was in silico cloned in the pET28a (+) expression vector using codon optimization. The current research identifies potential antigenic epitopes that could be used as vaccine candidates to eradicate the CHPV. This in-silico development of a CHPV vaccine with multiple epitopes could open the path for future rapid laboratory tests.

Identification of potential inhibitory analogs of metastasis tumor antigens (MTAs) using bioactive compounds: revealing therapeutic option to prevent malignancy.

The deeper understanding of metastasis phenomenon and detection of drug targets could be a potential approach to minimize cancer mortality. In this study, attempts were taken to unmask novel therapeutics to prevent metastasis and cancer progression. Initially, we explored the physiochemical, structural and functional insights of three metastasis tumor antigens (MTAs) and evaluated some plant-based bioactive compounds as potent MTA inhibitors. From 50 plant metabolites screened, isoflavone, gingerol, citronellal and asiatic acid showed maximum binding affinity with all three MTA proteins. The ADME analysis detected no undesirable toxicity that could reduce the drug likeness properties of top plant metabolites. Moreover, molecular dynamics studies revealed that the complexes were stable and showed minimum fluctuation at molecular level. We further performed ligand-based virtual screening to identify similar drug molecules using a large collection of 376,342 compounds from DrugBank. The results suggested that several structural analogs (e.g., tramadol, nabumetone, DGLA and hydrocortisone) may act as agonist to block the MTA proteins and inhibit cancer progression at early stage. The study could be useful to develop effective medications against cancer metastasis in future. Due to encouraging results, we highly recommend further in vitro and in vivo trials for the experimental validation of the findings.

Utilizing machine learning to enhance performance of thin-film solar cells based on Sb2(S x Se1-x )3: investigating the influence of material properties.

Antimony chalcogenides (Sb2(S x Se1-x )3) have drawn attention as a potential semiconducting substance for heterojunction photovoltaic (PV) devices due to the remarkable optoelectronic properties and wide range of bandgaps spanning from 1.1 to 1.7 eV. In this investigation, SCAPS-1D simulation software is employed to design an earth abundant, non-toxic, and cost-effective antimony sulfide-selenide (Sb2(S,Se)3)-based thin-film solar cell (TFSC), where tungsten disulfide (WS2) and cuprous oxide (Cu2O) are used as an electron transport layer (ETL) and hole transport layer (HTL), respectively. The PV performance parameters such as power conversion efficiency, open-circuit voltage (V oc), short-circuit current (J sc), and fill factor (FF) are assessed through adjustments in material properties including thickness, acceptor concentration, bulk defect density of the absorber, defect state of absorber/ETL and HTL/absorber interfaces, operating temperature, work function of the rear electrode, and cell resistances. This analysis aims to validate their collective impact on the overall efficiency of the designed Ni/Cu2O/Sb2(S,Se)3/WS2/FTO/Al TFSC. The optimized physical parameters for the Sb2(S,Se)3 TFSC lead to impressive PV outputs with an efficiency of 30.18%, V oc of 1.02 V, J sc of 33.65 mA cm-2, and FF of 87.59%. Furthermore, an artificial neural network (ANN) machine learning (ML) algorithm predicts the optimal PCE by considering five semiconductor parameters: absorber layer thickness, bandgap, electron affinity, electron mobility, and hole mobility. This model, which has an approximate correlation coefficient (R 2) of 0.999, is able to predict the data with precision. This numerical analysis provides valuable data for the fabrication of an environmentally friendly, economical, and incredibly non-toxic efficient heterojunction TFSC.

Improving the efficiency of a CIGS solar cell to above 31% with Sb2S3 as a new BSF: a numerical simulation approach by SCAPS-1D.

The remarkable performance of copper indium gallium selenide (CIGS)-based double heterojunction (DH) photovoltaic cells is presented in this work. To increase all photovoltaic performance parameters, in this investigation, a novel solar cell structure (FTO/SnS2/CIGS/Sb2S3/Ni) is explored by utilizing the SCAPS-1D simulation software. Thicknesses of the buffer, absorber and back surface field (BSF) layers, acceptor density, defect density, capacitance-voltage (C-V), interface defect density, rates of generation and recombination, operating temperature, current density, and quantum efficiency have been investigated for the proposed solar devices with and without BSF. The presence of the BSF layer significantly influences the device's performance parameters including short-circuit current (Jsc), open-circuit voltage (Voc), fill factor (FF), and power conversion efficiency (PCE). After optimization, the simulation results of a conventional CIGS cell (FTO/SnS2/CIGS/Ni) have shown a PCE of 22.14% with Voc of 0.91 V, Jsc of 28.21 mA cm-2, and FF of 86.31. Conversely, the PCE is improved to 31.15% with Voc of 1.08 V, Jsc of 33.75 mA cm-2, and FF of 88.50 by introducing the Sb2S3 BSF in the structure of FTO/SnS2/CIGS/Sb2S3/Ni. These findings of the proposed CIGS-based double heterojunction (DH) solar cells offer an innovative method for realization of high-efficiency solar cells that are more promising than the previously reported traditional designs.

Evaluating the performance of efficient Cu2NiSnS4 solar cell-A two stage theoretical attempt and comparison to experiments.

In this work, copper nickel tin sulfide (Cu2NiSnS4) as an encouraging alternative absorber for thin-film photovoltaic devices is explored. Here, the Cu2NiSnS4 (CNTS) absorber-based heterojunction solar cell is designed through a two-stage theoretical approach using Solar Cell Capacitance Simulator in one-dimension (SCAPS-1D). Initially four different hole transport materials (MoO3, SnS, NiOx, and PEDOT.PSS) are incorporated at the back interface in experimentally configured Au/Cu2NiSnS4/ZnS/ZnO/ITO cell to boost the device outputs. The MoO3 semiconductor is anticipated as a hole transport layer (HTL) in the heterojunction Ni/MoO3/Cu2NiSnS4/ZnS/ZnO/ITO solar configuration. It is revealed that an appropriate band alignment can be formed at MoO3/Cu2NiSnS4 interface with less interfacial defects among other HTLs with CNTS absorber, thus improving the solar cell outputs. Efficiency is increased from 2.71% to 8.79% for the proposed CNTS-based solar cell. Further optimization is accomplished concerning thickness, defect states, and doping density of the various materials utilized in the heterojunction structure. Defect characteristics at the MoO3/Cu2NiSnS4 and Cu2NiSnS4/ZnS interfaces are also evaluated and optimized to boost the conversion efficiency significantly. Moreover, the effects of operating temperature and rear electrode work function on the outputs of the designed solar device are studied. The aforesaid two-stage optimization yields efficiency of 12.46% with VOC of 1.23 V, JSC of 12.66 mA/cm2, and FF of 79.78%. Therefore, these findings will facilitate the scientific communities to further progress an economical and extremely efficient CNTS-based solar device with a promising MoO3 HTL.

Therapeutic Promises of Plant Metabolites against Monkeypox Virus: An In Silico Study.

The monkeypox virus was still spreading in May 2022, with the first case identified in a person with travel ties to Nigeria. Using molecular docking-based techniques, we evaluated the efficiency of different bioactive chemicals obtained from plants against the monkeypox virus. A total of 56 plant compounds were evaluated for antimonekypox capabilities, with the top four candidates having a higher binding affinity than the control. We targeted the monkeypox profilin-like protein, which plays a key role in viral replication and assembly. Among the metabolites, curcumin showed the strongest binding affinity with a value of -37.43 kcal/mol, followed by gedunin (-34.89 kcal/mol), piperine (-34.58 kcal/mol), and coumadin (-34.14 kcal/mol). Based on ADME and toxicity assessments, the top four substances had no negative impacts. Furthermore, four compounds demonstrated resistance to deformability, which was corroborated by normal mode analysis. According to the bioactivity prediction study, the top compound target class was an enzyme, membrane receptor, and oxidoreductase. Furthermore, the study discovered that wortmannin, a gedunin analogue, can behave as an orthopoxvirus. The study found that these bioactive natural drug candidates could potentially work as monkeypox virus inhibitors. We recommended further experimental validation to confirm the promising findings of the study.

A qualitative Design and optimization of CIGS-based Solar Cells with Sn2S3 Back Surface Field: A plan for achieving 21.83 % efficiency.

Conventional Copper Indium Gallium Di Selenide (CIGS)-based solar cells are more efficient than second-generation technology based on hydrogenated amorphous silicon (a-Si: H) or cadmium telluride (CdTe). So, herein the photovoltaic (PV) performance of CIGS-based solar cells has been investigated numerically using SCAPS-1D solar simulator with different buffer layer and less expensive tin sulfide (Sn2S3) back-surface field (BSF). At first, three buffer layer such as cadmium sulfide (CdS), zinc selenide (ZnSe) and indium-doped zinc sulfide ZnS:In have been simulated with CIGS absorber without BSF due to optimized and non-toxic buffer. Then the optimized structure of Al/FTO/ZnS:In/CIGS/Ni is modified to become Al/FTO/ZnS:In/CIGS/Sn2S3/Ni by adding a Sn2S3 BSF to enhanced efficiency. The detailed analysis have been investigated is the influence of physical properties of each absorber and buffer on photovoltaic parameters including layer thickness, carrier doping concentration, bulk defect density, interface defect density. This study emphasizes investigating the reasons for the actual devices' poor performance and illustrates how each device's might vary open-circuit voltage (VOC), short-circuit current density (JSC), fill factor (FF), power conversion efficiency (PCE), and quantum efficiency (QE). The optimized structure offers outstanding power conversion efficiency (PCE) of 21.83 % with only 0.80 µm thick CIGS absorber. The proposed CIGS-based solar cell performs better than the previously reported conventional designs while also reducing CIGS thickness and cost.

Therapeutic Promises of Medicinal Plants in Bangladesh and Their Bioactive Compounds against Ulcers and Inflammatory Diseases.

When functioning properly, the stomach is the center of both physical and mental satisfaction. Gastrointestinal disorders, or malfunctioning of the stomach, due to infections caused by various biological entities and physiochemical abnormalities, are now widespread, with most of the diseases being inflammatory, which, depending on the position and degree of inflammation, have different names such as peptic or gastric ulcers, irritable bowel diseases, ulcerative colitis, and so on. While many synthetic drugs, such as non-steroidal anti-inflammatory drugs, are now extensively used to treat these diseases, their harmful and long-term side effects cannot be ignored. To treat these diseases safely and successfully, different potent medicinal plants and their active components are considered game-changers. In consideration of this, the present review aimed to reveal a general and comprehensive updated overview of the anti-ulcer and anti-inflammatory activities of medicinal plants. To emphasize the efficacy of the medicinal plants, various bioactive compounds from the plant extract, their experimental animal models, and clinical trials are depicted.

Screening and druggability analysis of some plant metabolites against SARS-CoV-2: An integrative computational approach.

The sudden outbreak of novel coronavirus has caused a global concern due to its infection rate and mortality. Despite extensive research, there are still no specific drugs or vaccines to combat SARS-CoV-2 infection. Hence, this study was designed to evaluate some plant-based active compounds for drug candidacy against SARS-CoV-2 by using virtual screening methods and various computational analyses. A total of 27 plant metabolites were screened against SARS-CoV-2 main protease proteins (MPP), Nsp9 RNA binding protein, spike receptor binding domain, spike ecto-domain and HR2 domain using a molecular docking approach. Four metabolites, i.e., asiatic acid, avicularin, guajaverin, and withaferin showed maximum binding affinity with all key proteins in terms of lowest global binding energy. The crucial binding sites and drug surface hotspots were unravelled for each viral protein. The top candidates were further employed for ADME (absorption, distribution, metabolism, and excretion) analysis to investigate their drug profiles. Results suggest that none of the compounds render any undesirable consequences that could reduce their drug likeness properties. The analysis of toxicity pattern revealed no significant tumorigenic, mutagenic, irritating, or reproductive effects by the compounds. However, withaferin was comparatively toxic among the top four candidates with considerable cytotoxicity and immunotoxicity. Most of the target class by top drug candidates belonged to enzyme groups (e.g. oxidoreductases hydrolases, phosphatases). Moreover, results of drug similarity prediction revealed two approved structural analogs of Asiatic acid i.e. Hydrocortisone (DB00741) (previously used for SARS-CoV-1 and MERS) and Dinoprost-tromethamine (DB01160) from DrugBank. In addition, two other biologically active compounds, Mupirocin (DB00410) and Simvastatin (DB00641) could be an option for the treatment of viral infections. The study may pave the way to develop effective medications and preventive measure against SARS-CoV-2. Due to the encouraging results, we highly recommend further in vivo trials for the experimental validation of our findings.