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With the rise of use of renewable Energy storage systems (ESSs) are gaining a lot of popularity. This paper reviews the different ESSs in power systems, especially microgrids showing their essential role in enhancing the performance of electrical systems. Therefore, the ESSs classified into various technologies as a function of the energy storage form and the main relevant technical parameters. In this review paper, the most common classifications are presented, summarized, and compared according to their characteristics. A specific interest in electrochemical ESSs, especially battery energy storage systems, focusing on their classifications due to their importance in the residential sector. Besides that, the benefits and drawbacks of Lithium-Ion (Li-Ion) batteries are discussed due to their significance. Finally, the environmental impact of these ESSs is discussed.

SARS-CoV-2 encodes eight accessory proteins, one of which, ORF8, has a poorly conserved sequence with SARS-CoV and its role in viral pathogenicity has recently been identified. ORF8 in SARS-CoV-2 has a unique functional feature that allows it to form a dimer structure linked by a disulfide bridge between Cys20 and Cys20 (S-S). This study provides structural characterization of natural mutant variants as well as the identification of potential drug candidates capable of binding directly to the interchain disulfide bridge. The lead compounds reported in this work have a tendency to settle in the dimeric interfaces by direct interaction with the disulfide bridge. These molecules may disturb the dimer formation and may have an inhibition impact on its potential functional role in host immune evasion and virulence pathogenicity. This work provides detailed insights on the sequence and structural variability through computational mutational studies, as well as potent drug candidates with the ability to interrupt the intermolecular disulfide bridge formed between Cys20 and Cys20. Furthermore, the interactions of ORF8 peptides complexed with MHC-1 is studied, and the binding mode reveals that certain ORF8 peptides bind to MHC-1 in a manner similar to other viral peptides. Overall, this study is a narrative of various computational approaches used to provide detailed structural insights into SARS-CoV-2 ORF8 interchain disulfide bond disruptors.

Gene expression varies due to the intrinsic stochasticity of transcription or as a reaction to external perturbations that generate cellular mutations. Co-regulation, co-expression and functional similarity of substances have been employed for indoctrinating the process of the transcriptional paradigm. The difficult process of analysing complicated proteomes and biological switches has been made easier by technical improvements, and microarray technology has flourished as a viable platform. Therefore, this research enables Microarray to cluster genes that are co-expressed and co-regulated into specific segments. Copious search algorithms have been employed to ascertain diacritic motifs or a combination of motifs that are performing regular expression, and their relevant information corresponding to the gene patterns is also documented. The associated genes co-expression and relevant cis-elements are further explored by engaging Escherichia coli as a model organism. Various clustering algorithms have also been used to generate classes of genes with similar expression profiles. A promoter database ‘EcoPromDB’ has been developed by referring RegulonDB database; this promoter database is freely available at www.ecopromdb.eminentbio.com and is divided into two sub-groups, depending upon the results of co-expression and co-regulation analyses.

The measurement of all machining forces and surface finish during the turning process. All types of machining process the cutting tool, workpiece of surfaces roughness, tool wear, quality, and accuracy of the part of machining the present study.to investigate the effect of machining input parameters (spindle speed, feed rate, depth of cut) on measuring the forces after machining (cutting force, feed force, thrust force) and surface roughness for turning operation. Using of workpieces is EN8 steel and a cutting tool is a carbide tool. experiment stabilized on the lathe machine. The force is measured by a triaxial piezoelectric sensors base dynamometer and data is transmitted by a data aquation system. this is controlled by LAB-VIEW software and stores the forces in the computer. there are 27 experiments, and one parameter is changed and two parameters are constant at an experiment. measured the forces and (Ra) is analyzed is by minitab18 software design a regression equation and (ANOVA). The minimum force and (Ra) the experimental (force &surface roughness is nearest to the predicted value

The purpose of this study is to design and fabricate the injection molding die with help of designing software and fabricating it with the help fused deposition modelling based 3d printing machine. Emphasis on designing of the injection die is given on the size and shape of the specimen to be molded and on giving a proper shrinkage allowance to the injection molding die for getting the desired dimension of the specimen molded in the injection molding die. Draft analysis of the injection die was carried out on the designed injection die for easy separation of the specimen and the polymer based injection die. Acrylonitrile butadiene styrene (ABS) polymer based filament is used in the fabrication of the injection die using Fused Deposition Modelling (FDM) working principle based 3d printer. The nozzle temperature requirement of the ABS based filament is 250 degree Celsius and the bed temperature required for printing ABS is around 90 degree Celsius which is recommended by the company which manufactures the used ABS based filament. The time consumption in manufacturing of the die is recorded and then compared to the time taken in manufacturing metal based die. This study concludes the optimum value of shrinkage allowance and proper draft analysis and time taken in the manufacturing of the die in the recommended parameters for the printing of the die.

In this paper, a comparative experimental analysis of die-sinking electric discharge machining (EDM) to two most exhaustively used aluminum metal matrix composites (AMMCs) has been performed using Copper and Tungsten as tool electrodes. AMMCs containing silicon carbide (SiC) and alumina (Al2O[Formula: see text] as reinforcement (10[Formula: see text]wt%) were fabricated by stir casting method. The Box–Behnken Design (BBD) approach of response surface methodology was used to develop experimental models for material removal rate (MRR) and surface roughness (SR). Effect of input parameters such as current ([Formula: see text]–12[Formula: see text]A), gap voltage ([Formula: see text][Formula: see text]V), pulse-on time ([Formula: see text]s), and duty factor ([Formula: see text]–6) on the output responses has been investigated with response surface plots. Effectiveness of design of experiment (DoE) and evolutionary algorithm-based multi-objective optimization (MOO) technique have been compared to find the best feasible optimal solution. ANOVA analysis reveals that for alumina reinforced AMMC interaction between [Formula: see text] has significant effect on both MRR and SR using Cu electrode. But for tungsten, electrode interaction between [Formula: see text], [Formula: see text], and [Formula: see text] have major role on MRR whereas SR is mostly influenced by interaction between [Formula: see text] and [Formula: see text]. The parametric analysis reveals that an increase of current from 4[Formula: see text]A to 12[Formula: see text]A at a higher pulse-ontime increases the MRR more significantly, and higher MRR occurs in cases of alumina-reinforced AMMC. Increase of pulse-ontime at low current (4[Formula: see text]A) reduces the MRR in AMMC/Al2O3. Good surface finish can be obtained by combining high voltage (60[Formula: see text]V) with either small current (4[Formula: see text]A) or small duty factor (4) for both AMMCs. Both DoE and metaheuristic-based MOO technique reveals that copper electrode should be preferred for die-sinking EDM of AMMC/SiC. Metaheuristic approach should be preferred for optimization of die-sinking EDM of AMMCs using different electrodes because it requires low current for effective machining of different AMMCs.

Today’s organizations are primarily dynamic and pose huge challenges and opportunities to the policy makers and corporate practitioners. The philosophy of Bhagavad Gita should not only be viewed from spiritual perspectives but also as a guide in developing Managerial Effectiveness. Today it has found its place as an alternative to the theory of modern management and also as a means to bring back the right path of peace and prosperity for the human beings. This research paper measures empirically the effectiveness of organizational corporate culture and its descriptions in Bhagavad Geeta. With this paper we will see the practical message of Bhagavad Gita has strong linkage to core management practices like establishment of good corporate culture.

The biosurfactants produced by microorganisms have high demand from microbial-enhanced oil recovery (MEOR) and they have focused on a chemical surfactant for the past few decades for degrading petro-based pollutants and oil spills due to its non-toxicity and increasing bioavailability. The study aims to identify and screen potential lipopeptide biosurfactant produced by Paenibacillus species employing a design experiment based on RSM. The bacterial culture was isolated from Chilika Lake, India. The data generated from the biosurfactant stability experiments were used to fit a regression model using the parameters such as ph, temp, and salinity to predict the E24 index. R-squared value 0.91 obtained from the ANOVA model explains that the regression model was significant, and the model p-value obtained was < 0.05 and was also statistically significant. Therefore the statistical regression model obtained in the present investigation can predict the E24 index by using any combination of ph, temp, and salinity parameters. The novel isolates obtained in this research were further named Paenibacillus dendritiformis ANSKLAB02 and deposited in GenBank with accession number KU518891. The growth of this species under controlled conditions has a high potential to help in environmental clean-up and is suitable for use in MEOR applications.

Glioblastoma (GBM) is the most devastating and frequent type of primary brain tumor with high morbidity and mortality. Despite the use of surgical resection followed by radio- and chemotherapy as standard therapy, the progression of GBM remains dismal with a median overall survival of15 months. GBM embodies a populace of cancer stem cells (GSCs) that is associated with tumor initiation, invasion, therapeutic resistance, and post-treatment reoccurrence. However, understanding the potential mechanisms of stemness and their candidate biomarkers remains limited. Hence in this investigation, we aimed to illuminate potential candidate hub genes and key pathways associated with the pathogenesis of GSC in the development of GBM. The integrated analysis discovered differentially expressed genes (DEGs) between the brain cancer tissues (GBM and GSC) and normal brain tissues. Multiple approaches, including gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, were employed to functionally annotate the DEGs and visualize them through the R program. The significant hub genes were identified through the protein-protein interaction network, Venn diagram analysis, and survival analysis. We observed that the upregulated DEGs were prominently involved in the ECM-receptor interaction pathway. The downregulated genes were mainly associated with the axon guidance pathway. Five significant hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) were screened out through multiple analyses. GO and KEGG analyses of hub genes uncovered that these genes were primarily enriched in disease-associated pathways such as the inhibition of apoptosis and the DNA damage repair mechanism, activation of the cell cycle, EMT (epithelial-mesenchymal transition), hormone AR (androgen receptor), hormone ER (estrogen receptor), PI3K/AKT (phosphatidylinositol 3-kinase and AKT), RTK (receptor tyrosine kinase), and TSC/mTOR (tuberous sclerosis complex and mammalian target of rapamycin). Consequently, the epigenetic regulatory network disclosed that hub genes played a vital role in the progression of GBM. Finally, candidate drugs were predicted that can be used as possible drugs to treat GBM patients. Overall, our investigation offered five hub genes (CTNNB1, ITGB1, TNC, EGFR, and SHOX2) that could be used as precise diagnostic and prognostic candidate biomarkers of GBM and might be used as personalized therapeutic targets to obstruct gliomagenesis.

Infertility is defined as difficulty in conceiving children after regular and unprotected coitus for at least one year. Many investigative measures are available now a day to identify the cause of infertility so clinician can assess the chance of achieving pregnancy in couples. Morphology of endometrium is very useful indicator of ovarian function. Our study aims to see the different pattern of endometrium histologically in female infertility patient. We tried to assess the significance anovulatory cycle and incidence of tuberculous endometritis. Study was done in pathology department of UPUMS, Saifai, Etawah. Eighty-four (84) cases of primary and secondary infertility were included in this study. Endometrial biopsy tissues were processed and stained with hematoxylin and eosin stain according to the standard procedure. Out of 84 cases 48(57%) were of primary infertility and 36 (42.85%) were of secondary infertility. Majority of the infertility patient fell in age group of 21 to 30 years. Out of 84 cases 42 (50%) cases showed proliferative endometrium and 33(39.2%) cases showed secretory endometrium. Tuberculous endometritis seen in 2 (2.3%) cases. In present study percentage of anovulatory endometrium was 52.5%, endometrial biopsy is cost-effective, safe and efficient diagnostic tool in cases of both primary and secondary infertility.

Early childhood caries (ECC) significantly affects the quality of life of children due to recurrent pain, infection, and other associated problems.To assess the change in oral health-related quality of life of children aged5 years undergoing complete oral rehabilitation under general anesthesia.A total of 50 healthy children affected with ECC were enrolled for the present study. Oral health-related quality of life (OHRQoL) of every child was assessed by interviewing the mothers using a prevalidated Early Childhood Oral Health Impact Scale (ECOHIS) questionnaire one day prior to the treatment appointment and comparing the scores with those at 1 and 3 months post-treatment to evaluate the changes in the OHRQoL, if any and assess the stability of the changes.The results revealed a statistically significant reduction in Ouality of Life (QoL) scores of all the domains and total ECOHIS scores between baseline and 1 month, and baseline and 3 months.Raghu R, Gauba K, Goyal A

Background: The HIV-1 pandemic is undoubtedly the major public-health crisis of our time. The extensive research on HIV has deepened our understanding of its pathogenesis and transmission dynamics. Some new entity molecules have been approved by the FDA for HIV treatment but till now protective vaccine remains elusive. Scientists are targeting many important proteins of HIV-1; gp41, gp120, CCR5 coreceptor, integrase, reverse transcriptase and protease. Few compounds are used as nucleotide analogues to stop HIV replication. Altogether, these compounds and their derivatives specifically block HIV entry and DNA replication. Using ADMET studies, people are working on these compounds to reduce toxicity and increase potency. Objective: Our main aim is to discuss the Pharmacokinetics properties of 23 important FDA antiretroviral drugs used for the treatment of HIV-1 infections. Methods: We have searched literature related to pharmacokinetics properties in PubMed, Google Scholar search engine. Conclusion: Here, we have reviewed the pharmacokinetic properties such as absorption, bioavailability, distribution, metabolism, and excretion, of important 23 FDA approved drugs. The drugs namely Fuzeon, Selzentry, Complera, Epivir, Retrovir, Emtriva, Ziagen, Edurant, Intelence, Pifeltro, Sustiva, Viramune, Isentress, Genvoya, Tivicay, Reyataz, Prezista, Lexiva, Invirase, Aptivus etc. are classified into five major classes: fusion inhibitors, Nucleoside/Nucleotide Reverse Transcriptase Inhibitors (NRTIs), Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs), Integrase Strand transfer inhibitors (INSTIs) and Protease inhibitors (PIs). This Review may helpful for the future development of potent antiretroviral drugs with improved pharmacokinetic properties.

This paper examines the drivers that influence the green marketing awareness and addresses the role of corporate social responsibility (CSR) as a mediator. Data was collected from 250 respondents by self-administered questionnaire through convenience sampling. The results indicate that competitive advantage, environmental sustainability, green purchase intention are significant influencers for green marketing awareness. CSR enjoys a positive and significant mediating effect on the relationship between the independent variables and green marketing. CSR mediates the relationship between environmental sustainability (ES), competitive advantage (CA) and green purchase intention (GPI) which can provide insights for corporates with respect to the factors influencing green marketing awareness. Also, this paper highlights the importance of green purchase intention, competitive advantage, environmental sustainability and their linkage towards green marketing awareness.

Summary Background Coronavirus disease-2019 (COVID-19) is a global pandemic. Studies reported dyslipidemia in patients with COVID-19. Herein, we conducted a systematic review and meta-analysis of published articles to evaluate the association of the lipid profile with the severity and mortality in COVID-19 patients. Methods PubMed/Medline, Europe PMC, and Google Scholar were searched for studies published between January 1, 2020 and January 13, 2021. Random or Fixed effects models were used to calculate the mean difference (MD) and 95% confidence intervals (CIs). Statistical heterogeneity was assessed using Cochran's Q test and I2 statistics. Results This meta-analysis included 19 studies. Of which, 12 studies were categorized by severity, 04 studies by mortality, and 03 studies by both severity and mortality. Our findings revealed significantly decreased levels of total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in the severe group when compared with the non-severe group in a random effect model. Similarly, random effect model results demonstrated significantly lower levels of HDL-C and LDL-C in the non-survivor group when compared with the survivor group. The level of TC was also found to be decreased in the non-survivor group when compared to the survivor group in a fixed-effect model. Conclusion In conclusion, the lipid profile is associated with both the severity and mortality in COVID-19 patients. Hence, the lipid profile may be used for assessing the severity and prognosis of COVID-19. Prospero registration number CRD42021216316 .

Bacillus anthracis is a gram positive, deadly spore forming bacteria causing anthrax and these bacteria having the complex mechanism in the cell wall envelope, which can adopt the changes in environmental conditions. In this, the membrane bound cell wall proteins are said to progressive drug target for the inhibition of Bacillus anthracis. Among the cell wall proteins, the SrtA is one of the important mechanistic protein, which mediate the ligation with LPXTG motif by forming the amide bonds. The SrtA plays the vital role in cell signalling, cell wall formation, and biofilm formations. Inhibition of SrtA leads to rupture of the cell wall and biofilm formation, and that leads to inhibition of Bacillus anthracis and thus, SrtA is core important enzyme to study the inhibition mechanism. In this study, we have examined 28 compounds, which have the inhibitory activity against the Bacillus anthracis SrtA for developing the 3D-QSAR and also, compounds binding selectivity with both open and closed SrtA conformations, obtained from 100 ns of MD simulations. The binding site loop deviate in forming the open and closed gate mechanism is investigated to understand the inhibitory profile of reported compounds, and results show the closed state active site conformations are required for ligand binding specificity. Overall, the present study may offer an opportunity for better understanding of the mechanism of action and can be aided to further designing of a novel and highly potent SrtA inhibitors.

Disordered proteins serve a crucial part in many biological processes that go beyond the capabilities of ordered proteins. A large number of virus-encoded proteins have extremely condensed proteomes and genomes, which results in highly disordered proteins. The presence of these IDPs allows them to rapidly adapt to changes in their biological environment and play a significant role in viral replication and down-regulation of host defense mechanisms. Since viruses undergo rapid evolution and have a high rate of mutation and accumulation in their proteome, IDPs' insights into viruses are critical for understanding how viruses hijack cells and cause disease. There are many conformational changes that IDPs can adopt in order to interact with different protein partners and thus stabilize the particular fold and withstand high mutation rates. This chapter explains the molecular mechanism behind viral IDPs, as well as the significance of recent research in the field of IDPs, with the goal of gaining a deeper comprehension of the essential roles and functions played by viral proteins.

Molecular level understanding on the role of viral infections causing cervical cancer is highly essential for therapeutic development. In these instances, systems pharmacology along with multi omics approach helps in unraveling the multi-targeted mechanisms of novel biologically active compounds to combat cervical cancer. The immuno-transcriptomic dataset of healthy and infected cervical cancer patients was retrieved from the array express. Further, the phytocompounds from medicinal plants were collected from the literature. Network Analyst 3.0 has been used to identify the immune genes around 384 which are differentially expressed and responsible for cervical cancer. Among the 87 compounds reported in plants for treating cervical cancer, only 79 compounds were targeting the identified immune genes of cervical cancer. The significant genes responsible for the domination in cervical cancer are identified in this study. The virogenomic signatures observed from cervical cancer caused by E7 oncoproteins serve as the potential therapeutic targets whereas, the identified compounds can act as anti-HPV drug deliveries. In future, the exploratory rationale of the acquired results will be useful in optimizing small molecules which can be a viable drug candidate.

HIV-1 latency consists of viral DNA; integrated inside the host genome; it remains transcriptional silent. Combined Antiretroviral Therapy (cART) and the host immune system fail to recognize the latency cells or reservoirs, representing a major barrier to eradicating the HIV-1 infection. The Shock and Kill emerged as a promising strategy to target these cells using Latency reversal agents (LRAs); partially succeeded in producing viral mRNA but failed to reduce the size of reservoirs. In this Context, 2-acylaminothiazole class derivatives appeared as promising HIV-1 latency-reversing agents. In this study, we have developed an atom-based 3 D-QSAR model by utilizing the 49 active compounds of the 5-substituted 2-acylaminothiazoles derivatives. These compounds are further randomly divided into training (37) and test (12) datasets, yielding statistically significant R

In this paper, we obtain characterizations of solution sets of the interval-valued mathematical programming problems with switching constraints. Stationary conditions which are weaker than the standard Karush–Kuhn–Tucker conditions need to be discussed in order to find the necessary optimality conditions. We introduce corresponding weak, Mordukhovich, and strong stationary conditions for the corresponding interval-valued mathematical programming problems with switching constraints (IVPSC) and interval-valued tightened nonlinear problems (IVTNP), because the W-stationary condition of IVPSC is equivalent to Karush–Kuhn–Tucker conditions of the IVTNP. Furthermore, we use strong stationary conditions to characterize the several solutions sets for IVTNP, in which the last ones are particular solutions sets for IVPSC at the same time, because the feasible set of tightened nonlinear problems (IVTNP) is a subset of the feasible set of the mathematical programs with switching constraints (IVPSC).

This present work aims to compare the Tensile properties of 17-4PH stainless steel with two different processes. The first is the ADAM Atomic Diffusion Additive Manufacturing process, and the second process is making a sample for 17-4PH with a metal plate. Markforged ADAM is a patented process for Additive Manufacturing Process Metal Extrusion by Markforged. In this process, the 17-4PH metal powder is converted into a wire filament, and the filament is prepared with metal powder encased in a plastic binder. The ADAM process consists of three processes. 1. Printing, 2. Washing 3. Sintering. In WASH chamber filled with specific liquid under which green part is kept for dissolving the binding substance available in the printed part, leaving the part semi-porous so that the remaining binder may easily burn during sintering. This debinding step cleans your sintering furnace and purifies the finished metal part. The Sinter-2 fits the whole construction volume of the Metal X thanks to its sizeable active hot zone (more than 22,280 cubic cm). It's ideal for large-scale production or batch production. This heavy-duty furnace sinters a wide variety of commercial-grade metals from their brown (washed) state to fully dense metal pieces. The second Sample is made from a 17-4PH stainless steel plate. With the help of some non-conventional machines, the required dogbone shape for the tensile test can be achieved.

Numerous viruses have evolved mechanisms to inhibit or alter the host cell's apoptotic response as part of their coevolution with their hosts. The analysis of virus-host protein interactions require an in-depth understanding of both the viral and host protein structures and repertoires, as well as evolutionary mechanisms and pertinent biological facts. Throughout the course of a viral infection, there is constant battle for binding between virus and cellular proteins. Exogenous interfaces facilitating viral-host interactions are well known for constantly targeting and suppressing endogenous interfaces mediating intraspecific interactions, such as viral-viral and host-host connections. In these interactions, the protein-protein interactions (PPIs), are mostly shown as networks (protein interaction networks, PINs), with proteins represented as nodes and their interactions represented as edges. Host proteins with a higher degree of connectivity are more likely to interact with viral proteins. Due to technical advancements, three-dimensional interactions may now be visualized computationally utilizing molecular modeling and cryo-EM approaches. The uniqueness of viral domain repertoires, their evolution, and their activities during viral infection make viruses fascinating models for research. This chapter aims to provide readers a complete picture of the viral hijacking mechanism in protein-protein interactions.

The present case report highlights the management of a 6 years old female child who suffered oral and maxillofacial injury due to explosion of a fire cracker inside the mouth which was managed by primary closure after complete debridement and to prevent the post treatment microstomia, a modified microstomia prevention intraoral prosthetic appliance was given and followed up for 15 months.

Artificial Intelligence revolutionizes the drug development process that can quickly identify potential biologically active compounds from millions of candidate within a short period. The present review is an overview based on some applications of Machine Learning based tools, such as GOLD, Deep PVP, LIB SVM, etc. and the algorithms involved such as support vector machine (SVM), random forest (RF), decision tree and Artificial Neural Network (ANN), etc. at various stages of drug designing and development. These techniques can be employed in SNP discoveries, drug repurposing, ligand-based drug design (LBDD), Ligand-based Virtual Screening (LBVS) and Structure- based Virtual Screening (SBVS), Lead identification, quantitative structure-activity relationship (QSAR) modeling, and ADMET analysis. It is demonstrated that SVM exhibited better performance in indicating that the classification model will have great applications on human intestinal absorption (HIA) predictions. Successful cases have been reported which demonstrate the efficiency of SVM and RF models in identifying JFD00950 as a novel compound targeting against a colon cancer cell line, DLD-1, by inhibition of FEN1 cytotoxic and cleavage activity. Furthermore, a QSAR model was also used to predict flavonoid inhibitory effects on AR activity as a potent treatment for diabetes mellitus (DM), using ANN. Hence, in the era of big data, ML approaches have been evolved as a powerful and efficient way to deal with the huge amounts of generated data from modern drug discovery to model small-molecule drugs, gene biomarkers and identifying the novel drug targets for various diseases.

Zika virus has been identified in various body fluids such as semen, urine, saliva, cerebrospinal fluid, and vaginal secretion of an infected individual. The pH of these fluids varies from mildly acidic to mildly alkaline. So it is imperative to understand the impact of these conditions on viral protein functioning. We investigated the NS2B-NS3 protease stability and its activity in different denaturing environments. Finding indicates that NS2B-NS3 protease maintains stability at pH 4.8–8.7. Thus it suggests that the complex remains functionally active to hydrolyze the polyprotein within a diverse environmental condition such as variable pH. Despite a stable structure at a broad pH range, a change in environmental conditions dramatically influence its protease activity. Moreover, it is susceptible to structural transformation leading to increased β-strand or helix content in the presence of alcohol. This study may help further to understand the folding-function relationship of the general flaviviral protease complex.

Glioblastoma (GBM) is a WHO Grade IV tumor with poor visibility, a high risk of comorbidity, and limited treatment options. Resurfacing from second-rate glioma was originally classified as either mandatory or optional. Recent interest in personalized medicine has motivated research toward biomarker stratification-based individualized illness therapy. GBM biomarkers have been investigated for their potential utility in prognostic stratification, driving the development of targeted therapy, and customizing therapeutic treatment. Due to the availability of a specific EGFRvIII mutational variation with a clear function in glioma-genesis, recent research suggests that EGFR has the potential to be a prognostic factor in GBM, while others have shown no clinical link between EGFR and survival. The pre-existing pharmaceutical lapatinib (PubChem ID: 208908) with a higher affinity score is used for Structure-based Virtual Screening. As a result, the current study revealed a newly screened chemical (PubChem CID: 59671768) with a higher affinity than the previously known molecule. When the two compounds are compared, the former has the lowest re-rank score. The time-resolved features of a virtually screened chemical and an established compound were investigated using Molecular Dynamics Simulation. Both compounds are equivalent, according to the ADMET study. This report implies that the virtual screened chemical could be a promising Glioblastoma therapy.

Enzymes, which are biological molecules, are constructed from polypeptide chains, and these molecules are activated through reaction mechanisms. It is the role of enzymes to speed up chemical reactions that are used to build or break down cell structures. Activation energy is reduced by the enzymes' selective binding of substrates in a protected environment. In enzyme tertiary structures, the active sites are commonly situated in a "cleft," which necessitates the diffusion of substrates and products. The amino acid residues of the active site may be far apart in the primary structure owing to the folding required for tertiary structure. Due to their critical role in substrate binding and attraction, changes in amino acid structure at or near the enzyme's active site usually alter enzyme activity. At the enzyme's active site, or where the chemical reactions occur, the substrate is bound. Enzyme substrates are the primary targets of the enzyme's active site, which is designed to assist in the chemical reaction. This chapter elucidates the summary of structure and chemistry of enzymes, their active site features, charges and role of water in the structures to clarify the biochemistry of the enzymes in the depth of atomic features.

Estrogen receptor alpha (ERα), a nuclear receptor protein encoded by the estrogen receptor1 (ESR1) gene, is an important biomarker in breast cancer diagnosis. Any dysregulation in its expression can actively implicate the development and progression of the disease. ERα is abnormally expressed in around 60% of the active cases, making it an important therapeutic target. In this study, we report the application of computational approaches to identify suitable drug-like molecules, which share similar ligand binding dynamics with ERα. Structure-based virtual screening(SBVS), docking, and inhibitor dynamics are used to study the ligand binding and interaction profiling of the anticipated ligand molecule, at the active site of the 4-hydroxytamoxifen (OHT) protein (PDB Id: 3ERT). SBVS analysis follows HTVS, SP, and XP protocol in comparison to the ZINC and NCI, to retrieve 20bestligandhits as effective inhibitors; All the compounds have shown significant interaction with active site residues (Leu346, Thr347, Asp351, Glu353, Trp383, Leu387, and Arg394) of the 4-hydroxytamoxifen. Moreover, the docking study was used to screen the top 5 compounds: ZINC13377936, NCI35753, ZINC35465238, ZINC14726791, and NCI663569. We also, employed molecular dynamics simulations to explore the binding dynamics present at the atomic level. Our MDS results have revealed the compounds (ZINC13377936 and NCI35753) with outstanding binding stability and lesser fluctuations. Both above hits possess a high potential as future therapeutic agents, acting by the mechanism of competitive inhibition against the ERα protein in breast cancer.

One of the significant natural pollutants in the atmosphere is the mineral dust aerosols. In the northern hemisphere, Arabian Peninsula is one of the significant sources of dust aerosols with the frequency of dust storms changing seasonally. Dust emitted from the Arabian Peninsula region transports towards the Indian region through prevailing winds, therefore a positive correlation between the extreme dust episodes over the Arabian region and air quality over the Indian region is generally observed. Therefore, there is a need to monitor and forecast such an episodic event over the Arabian Peninsula and surrounding regions so that substantial measures may be taken in Indian subcontinent to mitigate the adverse impact of low air quality on human being and several other sectors such as aviation, energy and infrastructure. In the present study, the WRF-Chem simulations for dust particles are assessed against the observational data sets (i.e. MERRA-2, MODIS-Terra, Aura-OMI, CPCB). Based on the comparison of WRF-Chem simulated data sets with the satellite/reanalysis data, it is noted that in the post-monsoon season, WRF-Chem model can capture the entire dust episode (emission, transportation and dissipation) reasonably well. From the statistical analysis (PDF, CDF, Scatter plot and Temporal evolution), it was noted that there was a consistent underestimation of the simulated dust by WRF-Chem as compared to the observational data sets. A statistically robust categorical analysis has also been carried out for assessing the performance of WRF-Chem with respect to the observations for each dust event, and it is noted that on an average the probability of detection of dust event is about 77% and false alarm ratio is about 15% with an overall accuracy of 76%. Results obtained from the present analysis are encouraging and would be useful for the assessment of WRF-Chem simulations for other seasons also.