Genome-Wide Investigation Reveals Potential Therapeutic Targets in Shigella spp.

Shigella stands as a major contributor to bacterial dysentery worldwide scale, particularly in developing countries with inadequate sanitation and hygiene. The emergence of multidrug-resistant strains exacerbates the challenge of treating Shigella infections, particularly in regions where access to healthcare and alternative antibiotics is limited. Therefore, investigations on how bacteria evade antibiotics and eventually develop resistance could open new avenues for research to develop novel therapeutics. The aim of this study was to analyze whole genome sequence (WGS) of human pathogenic Shigella spp. to elucidate the antibiotic resistance genes (ARGs) and their mechanism of resistance, gene-drug interactions, protein-protein interactions, and functional pathways to screen potential therapeutic candidate(s). We comprehensively analyzed 45 WGS of Shigella, including S. flexneri (n = 17), S. dysenteriae (n = 14), S. boydii (n = 11), and S. sonnei (n = 13), through different bioinformatics tools. Evolutionary phylogenetic analysis showed three distinct clades among the circulating strains of Shigella worldwide, with less genomic diversity. In this study, 2,146 ARGs were predicted in 45 genomes (average 47.69 ARGs/genome), of which only 91 ARGs were found to be shared across the genomes. Majority of these ARGs conferred their resistance through antibiotic efflux pump (51.0%) followed by antibiotic target alteration (23%) and antibiotic target replacement (18%). We identified 13 hub proteins, of which four proteins (e.g., tolC, acrR, mdtA, and gyrA) were detected as potential hub proteins to be associated with antibiotic efflux pump and target alteration mechanisms. These hub proteins were significantly (p < 0.05) enriched in biological process, molecular function, and cellular components. Therefore, the finding of this study suggests that human pathogenic Shigella strains harbored a wide range of ARGs that confer resistance through antibiotic efflux pumps and antibiotic target modification mechanisms, which must be taken into account to devise and formulate treatment strategy against this pathogen. Moreover, the identified hub proteins could be exploited to design and develop novel therapeutics against MDR pathogens like Shigella.

Clinical Evaluation of Coronally Advanced Flap with or without a Platelet-Rich Fibrin Membrane for the Root Coverage.

Aim: To evaluate "coronally advanced flap" with or without "a platelet-rich fibrin membrane for the root coverage." Materials and Methods: All the clinical parameters were assessed at different time intervals (at baseline, 1, 3, and 6 months) in both experimental and control group. Following "clinical parameters" were recorded using "UNC-15" "Probe-Plaque Index (PI)" (Silness and Loe, 1964), "Gingival Index" (GI) (Loe and Silness, 1963), "Recession depth (RD)," "Recession width (RW)," "Clinical attachment level (CAL)," and "Width of keratinized gingiva (WKG)". Results: At final evaluation (i.e., mean change from baseline to 6 months), "the decrease in Plaque Index was 2.5% higher in Group B (66.0%) as compared to Group A (63.5%). The decrease in Gingival Index was 6.1% higher in Group B (91.4%) as compared to Group A (85.3%), and the decrease in recession width was 4.0% higher in Group B (75.2%) as compared to Group A (71.2%). The decrease in clinical attachment level was 4.4% higher in Group B (53.2%) as compared to Group A (48.4%). The increase in width of keratinized gingiva was 1.9% higher in Group A (28.8%) as compared to Group B (26.9%)." Conclusion: The controlled, randomized, split mouth design showed that CAF surgery, either by alone or in combination with PRF, is an efficient treatment method for covering denuded roots. "This design was used to treat bilateral isolated Miller's class I and II recessions in gingival part. When compared to the CAF approach, the results from a combination of CAF and PRF after a 6-month period showed additional advantages in addition to mean root coverage in the treatment of Miller's classes I and II recessions in gingival part."

System biology approaches to identify hub genes linked with ECM organization and inflammatory signaling pathways in schizophrenia pathogenesis.

Schizophrenia (SZ) is a chronic and devastating mental illness that affects around 20 million individuals worldwide. Cognitive deficits and structural and functional changes of the brain, abnormalities of brain ECM components, chronic neuroinflammation, and devastating clinical manifestation during SZ are likely etiological factors shown by affected individuals. However, the pathophysiological events associated with multiple regulatory pathways involved in the brain of this complex disorder are still unclear. This study aimed to develop a pipeline based on bioinformatics and systems biology approaches for identifying potential therapeutic targets involving possible biological mechanisms from SZ patients and healthy volunteers. About 420 overlapping differentially expressed genes (DEGs) from three RNA-seq datasets were identified. Gene ontology (GO), and pathways analysis showed several biological mechanisms enriched by the commonly shared DEGs, including extracellular matrix organization (ECM) organization, collagen fibril organization, integrin signaling pathway, inflammation mediated by chemokines and cytokines signaling pathway, and GABA-B receptor II and IL4 mediated signaling. Besides, 15 hub genes (FN1, COL1A1, COL3A1, COL1A2, COL5A1, COL2A1, COL6A2, COL6A3, MMP2, THBS1, DCN, LUM, HLA-A, HLA-C, and FBN1) were discovered by comprehensive analysis, which was mainly involved in the ECM organization and inflammatory signaling pathway. Furthermore, the miRNA target of the hub genes was analyzed with the random-forest-based approach software miRTarBase. In addition, the transcriptional factors and protein kinases regulating overlapping DEGs in SZ, namely, SUZ12, EZH2, TRIM28, TP53, EGR1, CSNK2A1, GSK3B, CDK1, and MAPK14, were also identified. The results point to a new understanding that the hub genes (fibronectin 1, collagen, matrix metalloproteinase-2, and lumican) in the ECM organization and inflammatory signaling pathways may be involved in the SZ occurrence and pathogenesis.

Screening out molecular pathways and prognostic biomarkers of ultraviolet-mediated melanoma through computational techniques.

PURPOSE: Ultraviolet radiation causes skin cancer, but the exact mechanism by which it occurs and the most effective methods of intervention to prevent it are yet unknown. For this purpose, our study will use bioinformatics and systems biology approaches to discover potential biomarkers of skin cancer for early diagnosis and prevention of disease with applicable clinical treatments. METHODS: This study compared gene expression and protein levels in ultraviolet-mediated cultured keratinocytes and adjacent normal skin tissue using RNA sequencing data from the National Center for Biotechnology Information-Gene Expression Omnibus (NCBI-GEO) database. Then, pathway analysis was employed with a selection of hub genes from the protein-protein interaction (PPI) network and the survival and expression profiles. Finally, potential clinical biomarkers were validated by receiver operating characteristic (ROC) curve analysis. RESULTS: We identified 32 shared differentially expressed genes (DEGs) by analyzing three different subsets of the GSE85443 dataset. Skin cancer development is related to the control of several DEGs through cyclin-dependent protein serine/threonine kinase activity, cell cycle regulation, and activation of the NIMA kinase pathways. The cytoHubba plugin in Cytoscape identified 12 hub genes from PPI; among these 3 DEGs, namely, AURKA, CDK4, and PLK1 were significantly associated with survival (P < 0.05) and highly expressed in skin cancer tissues. For validation purposes, ROC curve analysis indicated two biomarkers: AURKA (area under the curve (AUC) value = 0.8) and PLK1 (AUC value = 0.7), which were in an acceptable range. CONCLUSIONS: Further translational research, including clinical experiments, teratogenicity tests, and in-vitro or in-vivo studies, will be performed to evaluate the expression of these identified biomarkers regarding the prognosis of skin cancer patients.

In-silico prediction of highly promising natural fungicides against the destructive blast fungus Magnaporthe oryzae.

Magnaporthe oryzae causes destructive blast disease in more than 50 species of the major cereal crops rice, wheat and maize and destroys food of millions of people worldwide. Application of synthetic chemical fungicides are environmentally hazardous and unreliable in controlling M. oryzae. Conversely, naturally occurring biofungicides with multiple modes of actions are needed to be discovered for combatting the blast fungus. To find the effective biofungicides, we performed molecular docking study of some potential antifungal natural compounds targeting two proteins including a single-stranded DNA binding protein MoSub1 (4AGH), and an effector protein AVR-Pik (5E9G) of M. oryzae that regulates transcription in fungus and/or suppresses the host cell immunity. The thirty-nine natural compounds previously shown to inhibit M. oryzae growth and reproduction were put under molecular docking against these two proteins followed by simulation, free energy, and interaction analysis of protein-ligand complexes. The virtual screening revealed that two alkaloidal metabolites, camptothecin and GKK1032A2 showed excellent binding energy with any of these target proteins compared to reference commercial fungicides, azoxystrobin and strobilurin. Of the detected compounds, GKK1032A2 bound to both target proteins of M. oryzae. Both compounds showed excellent bioactivity scores as compared to the reference fungicides. Results of our computational biological study suggest that both camptothecin and GKK1032A2 are potential fungicides that could also be considered as lead compounds to design novel fungicides against the blast fungus. Furthermore, the GKK1032A2 acted as a multi-site mode of action fungicide against M. oryzae.

Role of T cells in cancer immunotherapy: Opportunities and challenges.

Immunotherapies boosting the immune system's ability to target cancer cells are promising for the treatment of various tumor types, yet clinical responses differ among patients and cancers. Recently, there has been increasing interest in novel cancer immunotherapy practices aimed at triggering T cell-mediated anti-tumor responses. Antigen-directed cytotoxicity mediated by T lymphocytes has become a central focal point in the battle against cancer utilizing the immune system. The molecular and cellular mechanisms involved in the actions of T lymphocytes have directed new therapeutic approaches in cancer immunotherapy, including checkpoint blockade, adoptive and chimeric antigen receptor (CAR) T cell therapy, and cancer vaccinology. This review addresses all the strategies targeting tumor pathogenesis, including metabolic pathways, to evaluate the clinical significance of current and future immunotherapies for patients with cancer, which are further engaged in T cell activation, differentiation, and response against tumors.

Highly potent natural fungicides identified in silico against the cereal killer fungus Magnaporthe oryzae.

Magnaporthe oryzae is one of the most notorious fungal pathogens that causes blast disease in cereals, and results in enormous loss of grain production. Many chemical fungicides are being used to control the pathogen but none of them are fully effective in controlling blast disease. Therefore, there is a demand for the discovery of a new natural biofungicide to manage the blast disease efficiently. A large number of new natural products showed inhibitory activities against M. oryzae in vitro. To find out effective biofungicides, we performed in silico molecular docking analysis of some of the potent natural compounds targeting four enzymes namely, scytalone dehydratase, SDH1 (PDB ID:1STD), trihydroxynaphthalene reductase, 3HNR (PDB ID:1YBV), trehalose-6-phosphate synthase, Tps1 (PDB ID:6JBI) and isocitrate lyase, ICL1 (PDB ID:5E9G) of M. oryzae fungus that regulate melanin biosynthesis and/or appresorium formation. Thirty-nine natural compounds that were previously reported to inhibit the growth of M. oryzae were subjected to rigid and flexible molecular docking against aforementioned enzymes followed by molecular dynamic simulation. The results of virtual screening showed that out of 39, eight compounds showed good binding energy with any one of the target enzymes as compared to reference commercial fungicides, azoxystrobin and strobilurin. Among the compounds, camptothecin, GKK1032A2 and chaetoviridin-A bind with more than one target enzymes of M. oryzae. All of the compounds except tricyclazole showed good bioactivity score. Taken together, our results suggest that all of the eight compounds have the potential to develop new fungicides, and remarkably, camptothecin, GKK1032A2 and chaetoviridin-A could act as multi-site mode of action fungicides against the blast fungus M. oryzae.

Differential gene expression profiling reveals potential biomarkers and pharmacological compounds against SARS-CoV-2: Insights from machine learning and bioinformatics approaches.

The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has created an urgent global situation. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability and disease comorbidities. The pandemic continues to spread worldwide, despite intense efforts to develop multiple vaccines and therapeutic options against COVID-19. However, the precise role of SARS-CoV-2 in the pathophysiology of the nasopharyngeal tract (NT) is still unfathomable. This study utilized machine learning approaches to analyze 22 RNA-seq data from COVID-19 patients (n = 8), recovered individuals (n = 7), and healthy individuals (n = 7) to find disease-related differentially expressed genes (DEGs). We compared dysregulated DEGs to detect critical pathways and gene ontology (GO) connected to COVID-19 comorbidities. We found 1960 and 153 DEG signatures in COVID-19 patients and recovered individuals compared to healthy controls. In COVID-19 patients, the DEG-miRNA, and DEG-transcription factors (TFs) interactions network analysis revealed that E2F1, MAX, EGR1, YY1, and SRF were the highly expressed TFs, whereas hsa-miR-19b, hsa-miR-495, hsa-miR-340, hsa-miR-101, and hsa-miR-19a were the overexpressed miRNAs. Three chemical agents (Valproic Acid, Alfatoxin B1, and Cyclosporine) were abundant in COVID-19 patients and recovered individuals. Mental retardation, mental deficit, intellectual disability, muscle hypotonia, micrognathism, and cleft palate were the significant diseases associated with COVID-19 by sharing DEGs. Finally, the detected DEGs mediated by TFs and miRNA expression indicated that SARS-CoV-2 infection might contribute to various comorbidities. Our results provide the common DEGs between COVID-19 patients and recovered humans, which suggests some crucial insights into the complex interplay between COVID-19 progression and the recovery stage, and offer some suggestions on therapeutic target identification in COVID-19 caused by the SARS-CoV-2.

Designing potential siRNA molecules for silencing the gene of the nucleocapsid protein of Nipah virus: A computational investigation.

Nipah virus (NiV), a zoonotic virus, engenders severe infections with noticeable complications and deaths in humans and animals. Since its emergence, it is frightening, this virus has been causing regular outbreaks in various countries, particularly in Bangladesh, India, and Malaysia. Unfortunately, no efficient vaccine or drug is available now to combat this baneful virus. NiV employs its nucleocapsid protein for genetic material packaging, which is crucial for viral replication inside the host cells. The small interfering RNAs (siRNAs) can play a central role in inhibiting the expression of disease-causing viral genes by hybridization and subsequent inactivation of the complementary target viral mRNAs through the RNA interference (RNAi) pathway. Therefore, potential siRNAs as molecular therapeutics against the nucleocapsid protein gene of NiV were designed in this study. First, ten prospective siRNAs were identified using the conserved nucleocapsid gene sequences among all available NiV strains collected from various countries. After that, off-target binding, GC (guanine-cytosine) content, secondary structure, binding affinity with the target, melting temperature, efficacy analysis, and binding capacity with the human argonaute protein 2 (AGO2) of these siRNAs were evaluated to predict their suitability. These designed siRNA molecules bear promise in silencing the NiV gene encoding the nucleocapsid protein and thus can alleviate the severity of this dangerous virus. Further in vivo experiments are recommended before using these designed siRNAs as alternative and effective molecular therapeutic agents against NiV.

Strategy for Conjugating Oligopeptides to Mesoporous Silica Nanoparticles Using Diazirine-Based Heterobifunctional Linkers.

Successful strategies for the attachment of oligopeptides to mesoporous silica with pores large enough to load biomolecules should utilize the high surface area of pores to provide an accessible, protective environment. A two-step oligopeptide functionalization strategy is examined here using diazirine-based heterobifunctional linkers. Mesoporous silica nanoparticles (MSNPs) with average pore diameter of ~8 nm and surface area of ~730 m2/g were synthesized and amine-functionalized. Tetrapeptides Gly-Gly-Gly-Gly (GGGG) and Arg-Ser-Ser-Val (RSSV), and a peptide comprised of four copies of RSSV (4RSSV), were covalently attached via their N-terminus to the amine groups on the particle surface by a heterobifunctional linker, sulfo-succinimidyl 6-(4,4'-azipentanamido)hexanoate (sulfo-NHS-LC-diazirine, or SNLD). SNLD consists of an amine-reactive NHS ester group and UV-activable diazirine group, providing precise control over the sequence of attachment steps. Attachment efficiency of RSSV was measured using fluorescein isothiocyanate (FITC)-tagged RSSV (RSSV-FITC). TGA analysis shows similar efficiency (0.29, 0.31 and 0.26 mol peptide/mol amine, respectively) for 4G, RSSV and 4RSSV, suggesting a generalizable method of peptide conjugation. The technique developed here for the conjugation of peptides to MSNPs provides for their attachment in pores and can be translated to selective peptide-based separation and concentration of therapeutics from aqueous process and waste streams.

Systems biology and in silico-based analysis of PCOS revealed the risk of metabolic disorders.

Background: Polycystic ovarian syndrome (PCOS) is a common condition of hyperandrogenism, chronic ovulation, and polycystic ovaries in females during the reproduction and maturation of the ovum. Although PCOS has been associated with metabolic disorders, including type 2 diabetes (T2D), obesity (OBE), and cardiovascular disease (CVD), Causal connection and molecular features are still unknown. Purpose: Therefore, we investigated the shared common differentially expressed genes (DEGs), pathways, and networks of associated proteins in PCOS and metabolic diseases with therapeutic intervention. Methods: We have used a bioinformatics pipeline to analyze transcriptome data for the polycystic ovarian syndrome (PCOS), type 2 diabetes (T2D), obesity (OBE), and cardiovascular diseases (CVD) in female patients. Then we employed gene-disease association network, gene ontology (GO) and signaling pathway analysis, selection of hub genes from protein-protein interaction (PPI) network, molecular docking, and gold benchmarking approach to screen potential hub proteins. Result: We discovered 2225 DEGs in PCOS patients relative to healthy controls and 34, 91, and 205 significant DEGs with T2D, Obesity, and CVD, respectively. Gene Ontology analysis revealed several significant shared and metabolic pathways from signaling pathway analysis. Furthermore, we identified ten potential hub proteins from PPI analysis that may serve as a therapeutic intervention in the future. Finally, we targeted one significant hub protein, IGF2R (PDB ID: 2V5O), out of ten hub proteins based on the Maximal clique centrality (MCC) algorithm and literature review for molecular docking study. Enzastaurin (-12.5), Kaempferol (-9.1), Quercetin (-9.0), and Coumestrol (-8.9) kcal/mol showed higher binding affinity in the molecular docking approach than 19 drug compounds. We have also found that the selected four compounds displayed favorable ADMET properties compared to the native ligand. Conclusion: Our in-silico research findings identified a shared molecular etiology between PCOS and metabolic diseases that may suggest new therapeutic targets and warrants future experimental validation of the key targets.

Designing potent inhibitors against the multidrug resistance P-glycoprotein.

The multidrug transporter P-glycoprotein is an ATP binding cassette (ABC) exporter responsible for resistance to tumor cells during chemotherapy. This study was designed with computational approaches aimed at identifying the best potent inhibitors of P-glycoprotein. Although many compounds have been suggested to inhibit P-glycoprotein, however, their information on bioavailability, selectivity, ADMET properties, and molecular interactions has not been revealed. Molecular docking, ADMET analysis, molecular dynamics, Principal component analysis (PCA), and binding free energy calculations were performed. Two compounds D1 and D2 showed the best docking score against P-glycoprotein and both compounds have 4-thiazolidinone derivatives containing indolin-3 one moiety are novel anti-tumor compounds. ADMET calculation analysis predicted D1 and D2 to have acceptable pharmacokinetic properties. The MD simulation discloses that D1-P-glycoprotein and D2-P-glycoprotein complexes are in stable conformation as apo-form. Hydrophobic amino acid such as phenylalanine plays significant on the interactions of inhibitors. Principal component analysis shows that both complexes are relatively similar variables as apo-form except planarity and Columbo energy profile. In addition, Quantitative Structural Activity Relationship (QSAR) of the ligand candidates were subjected to the principal component analysis (PCA) for pattern recognition. Partial-least-square (PLS) regression analysis was further utilized to model drug candidates' QSAR for subsequent prediction of the binding energy of validated drug candidates. PCA revealed groupings of the drug candidates based on the similarity or differences in drug candidates QSAR. Moreover, the developed PLS regression accurately predicted the values of the binding energy of drug candidates, with low residual error of prediction.Communicated by Ramaswamy H. Sarma.

Identification of deleterious single nucleotide polymorphism (SNP)s in the human TBX5 gene & prediction of their structural & functional consequences: An in silico approach.

T-box transcription factor 5 gene (TBX5) encodes the transcription factor TBX5, which plays a crucial role in the development of heart and upper limbs. Damaging single nucleotide variants in this gene alter the protein structure, disturb the functions of TBX5, and ultimately cause Holt-Oram Syndrome (HOS). By analyzing the available single nucleotide polymorphism information in the dbSNP database, this study was designed to identify the most deleterious TBX5 SNPs through in silico approaches and predict their structural and functional consequences. Fifty-eight missense substitutions were found damaging by sequence homology-based tools: SIFT and PROVEAN, and structure homology-based tool PolyPhen-2. Various disease association meta-predictors further scrutinized these SNPs. Additionally, conservation profile of the amino acid residues, their surface accessibility, stability, and structural integrity of the native protein upon mutations were assessed. From these analyses, finally 5 SNPs were detected as the most damaging ones: [rs1565941579 (P85S), rs1269970792 (W121R), rs772248871 (V153D), rs769113870 (E208D), and rs1318021626 (I222N)]. Analyses of stop-lost, nonsense, UTR, and splice site SNPs were also conducted. Through integrative bioinformatics analyses, this study has identified the SNPs that are deleterious to the TBX5 protein structure and have the potential to cause HOS. Further wet-lab experiments can validate these findings.

An Analysis Based on Molecular Docking and Molecular Dynamics Simulation Study of Bromelain as Anti-SARS-CoV-2 Variants.

The rapid spread of a novel coronavirus known as SARS-CoV-2 has compelled the entire world to seek ways to weaken this virus, prevent its spread and also eliminate it. However, no drug has been approved to treat COVID-19. Furthermore, the receptor-binding domain (RBD) on this viral spike protein, as well as several other important parts of this virus, have recently undergone mutations, resulting in new virus variants. While no treatment is currently available, a naturally derived molecule with known antiviral properties could be used as a potential treatment. Bromelain is an enzyme found in the fruit and stem of pineapples. This substance has been shown to have a broad antiviral activity. In this article, we analyse the ability of bromelain to counteract various variants of the SARS-CoV-2 by targeting bromelain binding on the side of this viral interaction with human angiotensin-converting enzyme 2 (hACE2) using molecular docking and molecular dynamics simulation approaches. We have succeeded in making three-dimensional configurations of various RBD variants using protein modelling. Bromelain exhibited good binding affinity toward various variants of RBDs and binds right at the binding site between RBDs and hACE2. This result is also presented in the modelling between Bromelain, RBD, and hACE2. The molecular dynamics (MD) simulations study revealed significant stability of the bromelain and RBD proteins separately up to 100 ns with an RMSD value of 2 Å. Furthermore, despite increases in RMSD and changes in Rog values of complexes, which are likely due to some destabilized interactions between bromelain and RBD proteins, two proteins in each complex remained bonded, and the site where the two proteins bind remained unchanged. This finding indicated that bromelain could have an inhibitory effect on different SARS-CoV-2 variants, paving the way for a new SARS-CoV-2 inhibitor drug. However, more in vitro and in vivo research on this potential mechanism of action is required.

Mechanism of Mesoporous Silica Nanoparticle Interaction with Hairy Root Cultures during Nanoharvesting of Biomolecules.

Cellular uptake and expulsion mechanisms of engineered mesoporous silica nanoparticles (MSNPs) are important in their design for novel biomolecule isolation and delivery applications such as nanoharvesting, defined as using nanocarriers to transport and isolate valuable therapeutics (secondary metabolites) out of living plant organ cultures (e.g., hairy roots). Here, temperature-dependent MSNP uptake and recovery processes in hairy roots are examined as a function of surface chemistry. MSNP uptake into hairy roots and time-dependent expulsion are quantified using Ti content (present for biomolecule binding) and fluorescence spectroscopy of fluorescently tagged MSNPs, respectively. The results suggest that functionalization and surface charge (regulated by amine group attachment) play the biggest role in the effectiveness of uptake and recovery. Comparison of MSNP interactions with hairy roots at 4 and 23 °C shows that weakly charged MSNPs functionalized only with Ti are taken up and expelled by thermally activated mechanisms, while amine-modified positively charged particles are taken up and expelled mainly by direct penetration of cell walls. Amine-functionalized MSNPs move spontaneously in and out of plant cells by dynamic exchange with a residence time of 20 ± 5 min, suggesting promise as a biomolecule nanoharvesting platform for plant organ cultures.

Screening of Potent Phytochemical Inhibitors Against SARS-CoV-2 Main Protease: An Integrative Computational Approach.

Coronavirus disease 2019 (COVID-19) is a potentially lethal and devastating disease that has quickly become a public health threat worldwide. Due to its high transmission rate, many countries were forced to implement lockdown protocols, wreaking havoc on the global economy and the medical crisis. The main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus for COVID-19, represent an effective target for the development of a new drug/vaccine because it is well-conserved and plays a vital role in viral replication. Mpro inhibition can stop the replication, transcription as well as recombination of SARS-CoV-2 after the infection and thus can halt the formation of virus particles, making Mpro a viable therapeutic target. Here, we constructed a phytochemical dataset based on a rigorous literature review and explored the probability that various phytochemicals will bind with the main protease using a molecular docking approach. The top three hit compounds, medicagol, faradiol, and flavanthrin, had binding scores of -8.3, -8.6, and -8.8 kcal/mol, respectively, in the docking analysis. These three compounds bind to the active groove, consisting of His41, Cys45, Met165, Met49, Gln189, Thr24, and Thr190, resulting in main protease inhibition. Moreover, the multiple descriptors from the molecular dynamics simulation, including the root-mean-square deviation, root-mean-square fluctuation, solvent-accessible surface area, radius of gyration, and hydrogen bond analysis, confirmed the stable nature of the docked complexes. In addition, absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis confirmed a lack of toxicity or carcinogenicity for the screened compounds. Our computational analysis may contribute toward the design of an effective drug against the main protease of SARS-CoV-2.

Extensive immunoinformatics study for the prediction of novel peptide-based epitope vaccine with docking confirmation against envelope protein of Chikungunya virus: a computational biology approach.

Chikungunya virus (CHIKV) instigating Chikungunya fever is a global infective menace resulting in high fever, weakened joint-muscle pain, and brain inflammation. Inaccessibility and unavailability of effective drugs have led us to an uncertain arena when it comes to providing proper medical treatment to the affected people. In this study, authentic encroachment has been made concerning the peptide-based epitope vaccine designing against CHIKV. A Proteome-wide search was performed to locate a conserved portion among the accessible viral outer membrane proteins which showcase a remarkable immune response using specific immunoinformatics and docking simulation tools. Primarily, the most probable immunogenic envelope glycoproteins E1 and E2 were identified from the UniProt database depending on their antigenicity scores. Subsequently, we selected two distinctive sequences "SEDVYANTQLVLQRP" and "IMLLYPDHPTLLSYR" in both E1 and E2 glycoproteins respectively. These two sequences identified as the most potent T and B cell epitope-based peptides as they interacted with 6 and 7 HLA-I and 5 HLA-II molecules with an extremely low IC50 score that was verified by molecular docking. Moreover, the sequences possess no allergenicity and are certainly located outside the transmembrane region. In addition, the sequences exhibited 88.46% and 100.00% Conservancy, covering high population coverage of 89.49% to 94.74% and 60.51% to 88.87% respectively in endemic countries. The identified peptide SEDVYANTQLVLQRP and IMLLYPDHPTLLSYR can be utilized next for the development of peptide-based epitope vaccine contrary to CHIKV, so further documentations and experimentations like Antigen testing, Antigen production, Clinical trials are needed to prove the validity of it. Communicated by Ramaswamy H. Sarma.

Comparative molecular investigation of the potential inhibitors against SARS-CoV-2 main protease: a molecular docking study.

Recent outbreak of novel coronavirus and its rapid pandemic escalation in all over the world has drawn the attention to urgent need for effective drug development. However, due to prolonged vaccine and drug development procedure against a newly emerged devastating SARS-CoV-2 virus pathogen, repurposing of existing potential pertinent drug molecules would be preferable strategy to reduce mortality immediately and further development of new drugs to combat overall global Covid-19 crisis in all over the world. Herein, we have filtered 23 prospective drug candidates through literature review. Assessing evidences from molecular docking studies, it was clearly seen that, Epirubicin, Vapreotida, and Saquinavir exhibited better binding affinity against SARS-CoV-2 Main Protease than other drug molecules among the 23 potential inhibitors. However, 50 ns molecular dynamics simulation indicated the less mobile nature of the docked complex maintaining structural integrity. Our overall prediction findings indicate that Epirubicin, Vapreotida, and Saquinavir may inhibit COVID-19 by synergistic interactions in the active cavity and those results can pave the way in drug discovery although it has to be further validated by in-vitro and in-vivo investigations.Communicated by Ramaswamy H. Sarma.

Simultaneous NO and SO2 removal by aqueous persulfate activated by combined heat and Fe2+: experimental and kinetic mass transfer model studies.

This study evaluates the chemistry, kinetics, and mass transfer aspects of the removal of NO and SO2 simultaneously from flue gas induced by the combined heat and Fe2+ activation of aqueous persulfate. The work involves experimental studies and the development of a mathematical model utilizing a comprehensive reaction scheme for detailed process evaluation, and to validate the results of an experimental study at 30-70 °C, which demonstrated that both SO2 and Fe2+ improved NO removal, while the SO2 is almost completely removed. The model was used to correlate experimental data, predict reaction species and nitrogen-sulfur (N-S) product concentrations, to obtain new kinetic data, and to estimate mass transfer coefficient (KLa) for NO and SO2 at different temperatures. The model percent conversion results appear to fit the data remarkably well for both NO and SO2 in the temperature range of 30-70 °C. The conversions ranged from 43.2 to 76.5% and 98.9 to 98.1% for NO and SO2, respectively, in the 30-70 °C range. The model predictions at the higher temperature of 90 °C were 90.0 and 97.4% for NO and SO2, respectively. The model also predicted decrease in KLa for SO2 of 1.097 × 10-4 to 8.88 × 10-5 s-1 (30-90 °C) and decrease in KLa for NO of 4.79 × 10-2 to 3.67 × 10-2 s-1 (30-50 °C) but increase of 4.36 × 10-2 to 4.90 × 10-2 s-1 at higher temperatures (70-90 °C). This emerging sulfate-radical-based process could be applied to the treatment of flue gases from combustion sources. Graphical abstract.

An Immunopharmacoinformatics Approach in Development of Vaccine and Drug Candidates for West Nile Virus.

An outbreak of West Nile Virus (WNV) like the recent Ebola can be more epidemic and fatal to public health throughout the world. WNV possesses utmost threat as no vaccine or drug is currently available for its treatment except mosquito control. The current study applied the combined approach of immunoinformatics and pharmacoinformatics to design potential epitope-based vaccines and drug candidates against WNV. By analyzing the whole proteome of 2994 proteins, the WNV envelope glycoprotein was selected as a therapeutic target based on its highest antigenicity. After proper assessment "KSFLVHREW" and "ITPSAPSYT" were found to be the most potential T and B-cell epitopes, respectively. Besides, we have designed and validated four novel drugs from a known WNV inhibitor, AP30451 by adopting computational approaches. Toxicity assessment and drug score confirmed the effectiveness of these drug candidates. This in silico research might greatly facilitate the wet lab experiments to develop vaccine and drug against WNV.