Network pharmacology, molecular simulation, and binding free energy calculation-based investigation of Neosetophomone B revealed key targets for the treatment of cancer.

In the current study, Neosetophomone B (NSP-B) was investigated for its anti-cancerous potential using network pharmacology, quantum polarized ligand docking, molecular simulation, and binding free energy calculation. Using SwissTarget prediction, and Superpred, the molecular targets for NSP-B were predicted while cancer-associated genes were obtained from DisGeNet. Among the total predicted proteins, only 25 were reported to overlap with the disease-associated genes. A protein-protein interaction network was constructed by using Cytoscape and STRING databases. MCODE was used to detect the densely connected subnetworks which revealed three sub-clusters. Cytohubba predicted four targets, i.e., fibroblast growth factor , FGF20, FGF22, and FGF23 as hub genes. Molecular docking of NSP-B based on a quantum-polarized docking approach with FGF6, FGF20, FGF22, and FGF23 revealed stronger interactions with the key hotspot residues. Moreover, molecular simulation revealed a stable dynamic behavior, good structural packing, and residues' flexibility of each complex. Hydrogen bonding in each complex was also observed to be above the minimum. In addition, the binding free energy was calculated using the MM/GBSA (Molecular Mechanics/Generalized Born Surface Area) and MM/PBSA (Molecular Mechanics/Poisson-Boltzmann Surface Area) approaches. The total binding free energy calculated using the MM/GBSA approach revealed values of -36.85 kcal/mol for the FGF6-NSP-B complex, -43.87 kcal/mol for the FGF20-NSP-B complex, and -37.42 kcal/mol for the FGF22-NSP-B complex, and -41.91 kcal/mol for the FGF23-NSP-B complex. The total binding free energy calculated using the MM/PBSA approach showed values of -30.05 kcal/mol for the FGF6-NSP-B complex, -39.62 kcal/mol for the FGF20-NSP-B complex, -34.89 kcal/mol for the FGF22-NSP-B complex, and -37.18 kcal/mol for the FGF23-NSP-B complex. These findings underscore the promising potential of NSP-B against FGF6, FGF20, FGF22, and FGF23, which are reported to be essential for cancer signaling. These results significantly bolster the potential of NSP-B as a promising candidate for cancer therapy.

Network-base approaches to identify therapeutic biomarkers in hepatocellular carcinoma and search for drug hunting utilizing molecular dynamics simulations.

The presence of conditions like Alpha-1 antitrypsin deficiency, hemochromatosis, non-alcoholic fatty liver diseases and metabolic syndrome can elevate the susceptibility to hepatic cellular carcinoma (HCC). Utilizing network-based gene expression profiling via network analyst tools, presents a novel approach for drug target discovery. The significance level (p-score) obtained through Cytoscape in the intended center gene survival assessment confirms the identification of all target center genes, which play a fundamental role in disease formation and progression in HCC. A total of 1064 deferential expression genes were found. These include MCM2 with the highest degree, followed by 4917 MCM6 and MCM4 with a 3944-degree score. We investigated the regulatory kinases involved in establishing the protein-protein interactions network using X2K web tool. The docking approach yields a favorable binding affinity of -8.7 kcal/mol against the target MCM2 using Auto-Dock Vina. Interestingly after simulating the complex system via AMBER16 package, results showed that the root mean square deviation values remained within 4.74 Å for a protein and remains stable throughout the time intervals. Additionally, the ligand's fit to the protein exhibited fluctuations at some intervals but remains stable. Finally, Gibbs free energy was found to be at its lowest at 1 kcal/mol which presents the real time interactive binding of the atomic residues among inhibitor and protein. The displacement of the ligand was measured showing stable movement and displacement along the active site. These findings increased our understanding for potential biomarkers in hepatocellular carcinoma and an experimental approach will further enhance our outcomes in future.Communicated by Ramaswamy H. Sarma.

Structural vaccinology, molecular simulation and immune simulation approaches to design multi-epitopes vaccine against John Cunningham virus.

The JCV (John Cunningham Virus) is known to cause progressive multifocal leukoencephalopathy, a condition that results in the formation of tumors. Symptoms of this condition such as sensory defects, cognitive dysfunction, muscle weakness, homonosapobia, difficulties with coordination, and aphasia. To date, there is no specific and effective treatment to completely cure or prevent John Cunningham polyomavirus infections. Since the best way to control the disease is vaccination. In this study, the immunoinformatic tools were used to predict the high immunogenic and non-allergenic B cells, helper T cells (HTL), and cytotoxic T cells (CTL) epitopes from capsid, major capsid, and T antigen proteins of JC virus to design the highly efficient subunit vaccines. The specific immunogenic linkers were used to link together the predicted epitopes and subjected to 3D modeling by using the Robetta server. MD simulation was used to confirm that the newly constructed vaccines are stable and properly fold. Additionally, the molecular docking approach revealed that the vaccines have a strong binding affinity with human TLR-7. The codon adaptation index (CAI) and GC content values verified that the constructed vaccines would be highly expressed in E. coli pET28a (+) plasmid. The immune simulation analysis indicated that the human immune system would have a strong response to the vaccines, with a high titer of IgM and IgG antibodies being produced. In conclusion, this study will provide a pre-clinical concept to construct an effective, highly antigenic, non-allergenic, and thermostable vaccine to combat the infection of the John Cunningham virus.

Antioxidant activity of Carica papaya & Persea americana fruits against cadmium induced neurotoxicity, nephrotoxicity, and hepatotoxicity in rats with a computational approach.

BACKGROUND: Cadmium is widely reported to interfere with the proper functioning of cells by disrupting cellular redox balance, causing apoptosis, and leading to hepatocellular damage, neurotoxicity, pulmonary edema, cancer, and cardiac and neurodegenerative diseases. Treatment of Cd toxicity with drugs brings undesirable side effects, making it necessary to remove Cd from the body safely without harmful effects. OBJECTIVE: This study aimed to determine how Cd causing malfunctioning of cells could be treated with antioxidant-rich avocado and papaya fruit juices. This work fixated on elucidating and comparing the effects of avocado and papaya fruit juice on Cd-dependent impairment in memory and spatial learning. In addition, various markers of tissue damage, such as the concentration of biomarkers in liver and kidney tissue, the expression of antioxidant enzymes and Cd-induced lipid peroxidation, were analyzed. METHODOLOGY: in silico studies of the phytochemical constituents of avocado and papaya (ligands) were docked against antioxidant enzymes Catalase (CAT), glutathione peroxidase (GPx) and superoxide dismutase (SOD) as macromolecules showed strong hydrogen binding with significant binding capacities. To develop the Cd in vivo model, rats were administered CdCl2 (200 ppm) in drinking water for 7 weeks. After induction of Cd toxicity, rats were post-treated with avocado and papaya (10% w/v each) in a standard diet. After post-treatment, memory and learning were assessed using the Morris water maze behavioural test. Biochemical tests for liver and kidney biomarkers were monitored. To determine the level of ROS, lipid peroxidation was determined by Malondialdehyde (MDA) assay. Gene expression of SOD, CAT and GPx were determined via qRT-PCR. RESULTS: This study demonstrated that Cd accumulation in the liver, kidney and hippocampal tissues was reduced after treatment with avocado and papaya. SOD, CAT and GPX gene expression were upregulated after avocado and papaya juice treatment. Moreover, a comparative analysis between avocado and papaya fruit juices clarified that papaya has more active potential for improving memory and learning, upregulating the expression of antioxidant enzymes, and reducing lipid peroxidation in the liver, kidney, and hippocampus. CONCLUSION: This study suggests that a diet containing papaya and avocado can help treat the lethal effects caused by Cd. Because their active constituents can improve health at the cellular and molecular levels.

Identification of potential drug molecules against fibroblast growth factor receptor 3 (FGFR3) by multi-stage computational-biophysics correlate.

The fibroblast growth factor receptor 3 (FGFR3) is warranted as a promising therapeutic target in bladder cancer as it is described in 75% of papillary bladder tumors. Considering this, the present study was conducted to use different approaches of computer-aided drug discovery (CADD) to identify the best binding compounds against the active pocket of FGFR3. Compared to control pyrimidine derivative, the study identified three promising lead structures; BDC_24037121, BDC_21200852, and BDC_21206757 with binding energy value of -14.80 kcal/mol, -12.22 kcal/mol, and -11.67 kcal/mol, respectively. The control molecule binding energy score was -9.85 kcal/mol. The compounds achieved deep pocket binding and produced balanced interactions of hydrogen bonds and van der Waals. The FGFR3 enzyme residues such as Leu478, Lys508, Glu556, Asn562, Asn622, and Asp635. The molecular dynamic (MD) simulation studies additionally validated the docked conformation stability with respect to FGFR3 with a mean root mean square deviation (RMSD) value of < 3 Å. The root mean square fluctuation (RMSF) complements the complexes structural stability and the residues showed less fluctuation in the presence of compounds. The Poisson-Boltzmann or generalized Born and surface area continuum solvation (MM/PBSA and MM/GBSA) methods revalidated compounds better binding and highlighted van der Waals energy to dominate the overall net energy. The docked stability was additionally confirmed by WaterSwap and AMBER normal mode entropy energy analyses. In a nutshell, the compounds shortlisted in this study are promising in term of theoretical binding affinity for FGFR3 but experimental validation is needed.Communicated by Ramaswamy H. Sarma.

Computational design of experimentally validated multi-epitopes vaccine against hepatitis E virus: An immunological approach.

Hepatitis E virus (HEV) is one of the leading acute liver infections triggered by viral hepatitis. Patients infected with HEV usually recover and the annual death rate is negligible. Currently, there is no HEV licensed vaccine available globally. This study was carried out to design a multi-epitope HEV peptide-based vaccine by retrieving already experimentally validated epitopes from ViPR database leading to epitope prioritization. Epitopes selected as potential vaccine candidates were non-allergen, immunogenic, soluble, non-toxic and IFN gamma positive. The epitopes were linked together by AAY linkers and the linker EAAAK was used to join adjuvant with epitopes. Toll-like receptor (TLR)-4 agonist was used as an adjuvant to boost efficacy of the vaccine. Furthermore, codon optimization followed by disulfide engineering was performed to analyse the designed vaccine's structural stability. Computational modeling of the immune simulation was done to examine the immune response against the vaccine. The designed vaccine construct was docked with TLR-3 receptor for their interactions and then subjected to molecular dynamic simulations. The vaccine model was examined computationally towards the capability of inducing immune responses which showed the induction of both humoral and cell mediated immunity. Taken together, our study suggests an In-silico designed HEV based multi-epitope peptide-based vaccine (MEPV) that needs to be examined in the wet lab-based data that can help to develop a potential vaccine against HEV.

A novel therapeutic approach to prevent Helicobacter pylori induced gastric cancer using networking biology, molecular docking, and simulation approaches.

Helicobacter pylori infects 50% of the world population and in 80% of cases, the infection progresses to the point where an ulcer develops leading to gastric cancer (GC). This study aimed to prevent GC by predicting Hub genes that are inducing GC. Furthermore, the study objective was to screen inhibitory molecules that block the function of predicted genes through several biophysical approaches. These proteins, such as Mucin 4 (MUC4) and Baculoviral IAP repeat containing 3 (BIRC3), had LogFC values of 2.28 and 3.39, respectively, and were found to be substantially expressed in those who had H. pylori infection. The MUC4 and BIRC3 inhibit apoptosis of infected cells and promote cancerous cell survival. The proteins were examined for their Physico-chemical characteristics, 3D structure and secondary structure analysis, solvent assessable surface area (SASA), active site identification, and network analysis. The MUC4 and BIRC3 expression was inhibited by docking eighty different compounds collected from the ZINC database. Fifty-seven compounds were successfully docked into the active site resulting in the lowest binding energy scores. The ZINC585267910 and ZINC585268691 compounds showed the lowest binding energy of -8.5 kcal/mol for MUC4 and -7.1 kcal/mol for BIRC3, respectively, and were considered best-docked solutions for molecular dynamics simulations. The mean root mean square deviation (RMSD) value for the ZINC585267910-MUC4 complex was 0.86 Å and the ZINC585268691-BIRC3 complex was 1.01 Å. The net MM/GBSA energy value of the ZINC585267910-MUC4 complex estimated was -46.84 kcal/mol and that of the ZINC585268691-BIRC3 complex was -44.84 kcal/mol. In a nutshell, the compounds might be investigated further as an inhibitor of the said proteins to stop the progress of GC induced by H. pylori.Communicated by Ramaswamy H. Sarma.

Emerging Applications of Nanotechnology in Healthcare and Medicine.

Knowing the beneficial aspects of nanomedicine, scientists are trying to harness the applications of nanotechnology in diagnosis, treatment, and prevention of diseases. There are also potential uses in designing medical tools and processes for the new generation of medical scientists. The main objective for conducting this research review is to gather the widespread aspects of nanomedicine under one heading and to highlight standard research practices in the medical field. Comprehensive research has been conducted to incorporate the latest data related to nanotechnology in medicine and therapeutics derived from acknowledged scientific platforms. Nanotechnology is used to conduct sensitive medical procedures. Nanotechnology is showing successful and beneficial uses in the fields of diagnostics, disease treatment, regenerative medicine, gene therapy, dentistry, oncology, aesthetics industry, drug delivery, and therapeutics. A thorough association of and cooperation between physicians, clinicians, researchers, and technologies will bring forward a future where there is a more calculated, outlined, and technically programed field of nanomedicine. Advances are being made to overcome challenges associated with the application of nanotechnology in the medical field due to the pathophysiological basis of diseases. This review highlights the multipronged aspects of nanomedicine and how nanotechnology is proving beneficial for the health industry. There is a need to minimize the health, environmental, and ethical concerns linked to nanotechnology.

Identification of Novel Genes and Pathways of Ovarian Cancer Using a Comprehensive Bioinformatic Framework.

Ovarian cancer (OC) is a significant contributor to gynecological cancer-related deaths worldwide, with a high mortality rate. Despite several advances in understanding the pathogenesis of OC, the molecular mechanisms underlying its development and prognosis remain poorly understood. Therefore, the current research study aimed to identify hub genes involved in the pathogenesis of OC that could serve as selective diagnostic and therapeutic targets. To achieve this, the dataset GEO2R was used to retrieve differentially expressed genes. The study identified a total of five genes (CDKN1A, DKK1, CYP1B1, NTS, and GDF15) that were differentially expressed in OC. Subsequently, a network analysis was performed using the STRING database, followed by the construction of a network using Cytoscape. The network analyzer tool in Cytoscape predicted 276 upregulated and 269 downregulated genes. Furthermore, KEGG analysis was conducted to identify different pathways related to OC. Subsequently, survival analysis was performed to validate gene expression alterations and predict hub genes, using a p-value of 0.05 as a threshold. Four genes (CDKN1A, DKK1, CYP1B1, and NTS) were predicted as significant hub genes, while one gene (GDF15) was predicted as non-significant. The adjusted P values of said predicted genes are 2.85E - 07, 5.49E - 06, 4.28E - 07, 1.43E - 07, and 3.70E - 07 for CDKN1A, DKK1, NTS, GDF15, and CYP1B1 respectively; additionally 6.08, 5.76, 5.74, 5.01, and 4.9 LogFc values of the said genes were predicted in GEO data set. In a boxplot analysis, the expression of these genes was analyzed in normal and tumor cells. The study found that three genes were highly expressed in tumor cells, while two genes (CDKN1A and DKK1) were more elevated in normal cells. According to the boxplot analysis for CDKN1A, 50% of tumor cells ranged between approx 3.8 and 5, while 50% of normal cells ranged between approx 6.9 and 7.9, which is greater than tumor cells. This shows that in normal cells, the CYP1B1 has a high expression level according to the GEPIA boxplot; addtionally the boxplot for DKK1 indicated that 50% of tumor cells ranged between approx 0 and 0.5, which was less than that of normal cells which ranged between approx 0.3 and 0.9. It shows that DKK1 is highly expressed in normal genes. Overall, the current study provides novel insights into the molecular mechanisms underlying OC. The identified hub genes and drug candidate targets could potentially serve as alternative diagnostic and therapeutic options for OC patients. Further research is needed to investigate the clinical significance of these findings and develop effective interventions that can improve the prognosis of patients with OC.

Clinical Performance of Cobas 6800 for the Detection of High-Risk Human Papillomavirus in Urine Samples.

Testing for high-risk human papillomavirus (HPV) as part of primary cervical cancer screening has become more common recently. The Cobas 6800, an FDA-approved cervical screening platform, detects 14 high-risk HPVs, including HPV16 and HPV18. However, this test is limited to only women, which leads to low screening rates in trans men and other non-binary people. The cervical screening of trans men and other genders, especially those lying on the female-to-male spectrum, is equally important. Furthermore, cisgender males, particularly homosexuals, are also prone to chronic HPV infections and serve as HPV carriers, transmitting it to women and other men through sexual contact. Another limitation of the test is its invasive specimen collection, which induces discomfort and genital dysphoria. Therefore, there is a need for an innovative, less invasive method that would allow the sampling process to be more comfortable. In this study, we assess the performance of the Cobas 6800 for high-risk HPV detection in urine samples spiked with HPV16, HPV18, and HPV68. The limit of detection (LOD) was calculated using a dilution series (1.25-10,000 copies/mL) over a course of three days. Furthermore, the clinical validation was performed by calculating sensitivity, specificity, and accuracy. The limit of detection ranged from 50-1000 copies/mL depending upon the genotype. Moreover, the urine test demonstrated a high clinical sensitivity of 93%, 94%, and 90% for HPV16, HPV18, and HPV68, with 100% specificity. The overall percent agreement was calculated to be 95% for both HPV16 and HPV18, and 93% for HPV68. The high concordance, reproducibility, and clinical performance of the current assay suggest that the urine-based HPV test fulfills the requirements for its use in primary cervical screening. Moreover, it has the potential to be used for mass screening to not only identify high-risk individuals, but also to monitor vaccine effectiveness.

Tracking HPV Infection, Associated Cancer Development, and Recent Treatment Efforts-A Comprehensive Review.

Human papillomaviruses (HPVs) are high-risk causative factors for HPV infection. This infection does not come alone; it is often seen with co-infection with other viruses and acts as a causative agent for several malignancies. The major purpose of this comprehensive study was to highlight some recent advances in biotechnology associated with HPV infection, including understanding its host interactions and cancerous progression. A systematic research strategy was used to gather data from recent, and the most advanced published electronic sources. The compiled data explain the recent understanding of biology, host-viral interaction cycles, co-infection with other viral diseases, and cellular transformation toward malignancies associated with HPV. In recent years, some vaccination protocols have been introduced in the form of live attenuated, subunit, and DNA-based vaccines. Moreover, some strategies of nanotechnology are being employed to synthesize drugs and vaccines with a whole new approach of plant-based products. The data are immense for the proposed research question, yet the need is to implement modern follow-up screening and modern therapeutics at the clinical level and to conduct wide-scale public awareness to lessen the HPV-related disease burden.

Sequence-structure functional implications and molecular simulation of high deleterious nonsynonymous substitutions in IDH1 revealed the mechanism of drug resistance in glioma.

In the past few years, various somatic point mutations of isocitrate dehydrogenase (IDH) encoding genes (IDH1 and IDH2) have been identified in a broad range of cancers, including glioma. Despite the important function of IDH1 in tumorigenesis and its very polymorphic nature, it is not yet clear how different nsSNPs affect the structure and function of IDH1. In the present study, we employed different machine learning algorithms to screen nsSNPs in the IDH1 gene that are highly deleterious. From a total of 207 SNPs, all of the servers classified 80 mutations as deleterious. Among the 80 deleterious mutations, 14 were reported to be highly destabilizing using structure-based prediction methods. Three highly destabilizing mutations G15E, W92G, and I333S were further subjected to molecular docking and simulation validation. The docking results and molecular simulation analysis further displayed variation in dynamics features. The results from molecular docking and binding free energy demonstrated reduced binding of the drug in contrast to the wild type. This, consequently, shows the impact of these deleterious substitutions on the binding of the small molecule. PCA (principal component analysis) and FEL (free energy landscape) analysis revealed that these mutations had caused different arrangements to bind small molecules than the wild type where the total internal motion is decreased, thus consequently producing minimal binding effects. This study is the first extensive in silico analysis of the IDH1 gene that can narrow down the candidate mutations for further validation and targeting for therapeutic purposes.

SARS-CoV-2 induced hepatic injuries and liver complications.

Background: Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which is resilient, highly pathogenic, and rapidly transmissible. COVID-19 patients have been reported to have underlying chronic liver abnormalities linked to hepatic dysfunction. Discussion: Viral RNAs are detectable in fecal samples by RT-PCR even after negative respiratory samples, which suggests that SARS-CoV-2 can affect the gastrointestinal tract and the liver. The case fatality rates are higher among the elderly and those with underlying comorbidities such as hypertension, diabetes, liver abnormality, and heart disease. There is insufficient research on signaling pathways. Identification of molecular mechanisms involved in SARS-CoV-2-induced damages to hepatocytes is challenging. Herein, we demonstrated the multifactorial effects of SARS-CoV-2 on liver injury such as psychological stress, immunopathogenesis, systemic inflammation, ischemia and hypoxia, drug toxicity, antibody-dependent enhancement (ADE) of infection, and several others which can significantly damage the liver. Conclusion: During the COVID-19 pandemic, it is necessary for clinicians across the globe to pay attention to SARS-CoV-2-mediated liver injury to manage the rising burden of hepatocellular carcinoma. To face the challenges during the resumption of clinical services for patients with pre-existing liver abnormalities and HCC, the impact of SARS-CoV-2 on hepatocytes should be investigated both in vitro and in vivo.

Risk of Malignancy in Breast FNAB Categories, Classified According to the Newly Proposed International Academy of Cytology (IAC) Yokohama System.

Background: A new category system comprising five classes (C1-insufficient material, C2-benign, C3-atypical, C4-suspicious, and C5-malignant) has been proposed by the International Academy of Cytology (IAC) for fine needle aspiration biopsy cytology (FNAB) for proper diagnosis of breast cancer. Aims and Objectives: This study is designed to categorize institutional FNAB data according to the new system and calculation of the absolute risk of malignancy (ROM), sensitivity, specificity, positive predictive values, false negative and false-positive rate. Study Design: We conducted a retrospective cross-sectional study involving 2133 cases collected between June, 2008 and August, 2019, at Foundation University Medical College's Department of Histopathology and the Surgery and Oncology Department at the Fauji Foundation Hospital. All cases fulfilling the inclusion and exclusion criteria were retrieved from the archives and reviewed by two expert pathologists. Matching histopathology was compared with the cytology reports for concordance or discordance of results. Findings: We found 6.9% (n = 147) insufficient, 65.8% (n = 1403) benign, 7.2% (n = 153) atypical, 7.5% (n = 160) suspicious and 12.6% (n = 270) malignant cases. Cyto-histological correlation was found in 421 cases from the year 2014 to 2019 with 370 concordant and 51 discordant cases. The maximum number of concordant cases was 151 in the C5 category and discordant cases had a diagnosis of C3 and C4 on cytology with 16 cases in each category. The calculated values of ROM were 45.45%, 10.3%, 30.6%, 82.79% and 99.34% from C1 to C5, respectively. We calculated 83.42% absolute sensitivity and 85.24% specificity. The positive predictive value for category 3, 4 and 5 was 67.34%, 82.7% and 99.34%, respectively, while false-negative rate was 7.9% and false-positive rate was 0.66%. Conclusion: The ROM for C1 category calculated from this study is quite high (45.45%) compared to previous studies; therefore, it is recommended to perform core needle biopsy in all these cases. The higher sensitivity and specificity of this method of diagnosing malignant lesions supports its use.

Prognostic Role of Monocytic Myeloid-Derived Suppressor Cells in Advanced Non-Small-Cell Lung Cancer: Relation to Different Hematologic Indices.

METHODS: We recruited 40 cases of advanced NSCLC, stages III and IV, aged > 18-<70 years old, and eligible to receive chemotherapy with or without radiotherapy, along with 20 healthy controls of comparable age and sex; after diagnosis and staging of patients, blood samples were collected for flow cytometric detection of Mo-MDSCs. RESULTS: Significant accumulation of Mo-MDSCs in patients compared to their controls (p < 0.0001). Furthermore, these cells accumulated significantly in stage IV compared to stage III (p = 0.006) and correlated negatively with overall survival (r = -0.471, p = 0.002), lymphocyte to monocyte ratio (r = -0.446, p = 0.004), and mean platelet volume to platelet count ratio (MPV/PC) (r = -0.464, p = 0.003), patients with Mo-MDSCs < 13% had significantly better survival than those with Mo-MDSCs ≥ 13% (p = 0.041). CONCLUSION: Mo-MDSCs represent one of the key mechanisms in the immunosuppressive tumor microenvironment (TME) to play major roles not only in the carcinogenesis of lung cancer but also in disease progression and prognosis and, in addition, predict the efficacy of immune checkpoint inhibitors; our results provided some support to target Mo-MDSCs and needed to be augmented by further studies.

Structure-Based Virtual Screening Identifies Multiple Stable Binding Sites at the RecA Domains of SARS-CoV-2 Helicase Enzyme.

With the emergence and global spread of the COVID-19 pandemic, the scientific community worldwide has focused on search for new therapeutic strategies against this disease. One such critical approach is targeting proteins such as helicases that regulate most of the SARS-CoV-2 RNA metabolism. The purpose of the current study was to predict a library of phytochemicals derived from diverse plant families with high binding affinity to SARS-CoV-2 helicase (Nsp13) enzyme. High throughput virtual screening of the Medicinal Plant Database for Drug Design (MPD3) database was performed on SARS-CoV-2 helicase using AutoDock Vina. Nilotinib, with a docking value of -9.6 kcal/mol, was chosen as a reference molecule. A compound (PubChem CID: 110143421, ZINC database ID: ZINC257223845, eMolecules: 43290531) was screened as the best binder (binding energy of -10.2 kcal/mol on average) to the enzyme by using repeated docking runs in the screening process. On inspection, the compound was disclosed to show different binding sites of the triangular pockets collectively formed by Rec1A, Rec2A, and 1B domains and a stalk domain at the base. The molecule is often bound to the ATP binding site (referred to as binding site 2) of the helicase enzyme. The compound was further discovered to fulfill drug-likeness and lead-likeness criteria, have good physicochemical and pharmacokinetics properties, and to be non-toxic. Molecular dynamic simulation analysis of the control/lead compound complexes demonstrated the formation of stable complexes with good intermolecular binding affinity. Lastly, affirmation of the docking simulation studies was accomplished by estimating the binding free energy by MMPB/GBSA technique. Taken together, these findings present further in silco investigation of plant-derived lead compounds to effectively address COVID-19.

Evaluation of the Whole Proteome of Achromobacter xylosoxidans to Identify Vaccine Targets for mRNA and Peptides-Based Vaccine Designing Against the Emerging Respiratory and Lung Cancer-Causing Bacteria.

Achromobacter xylosoxidans is a rod-shaped Gram-negative bacterium linked with causing several infections which mostly includes hematological malignancies. It has been recently reported to be associated with the development and progression of lung cancer and is an emerging respiratory disease-causing bacterium. The treatment of individuals infected with A. xylosoxidans bacteremia is difficult due to the fact that this pathogen has both intrinsic and acquired resistance mechanisms, typically resulting in a phenotype of multidrug resistance (MDR). Efforts are needed to design effective therapeutic strategies to curtail the emergence of this bacterium. Computational vaccine designing has proven its effectiveness, specificity, safety, and stability compared to conventional approaches of vaccine development. Therefore, the whole proteome of A. xylosoxidans was screened for the characterization of potential vaccine targets through subtractive proteomics pipeline for therapeutics design. Annotation of the whole proteome confirmed the three immunogenic vaccine targets, such as (E3HHR6), (E3HH04), and (E3HWA2), which were used to map the putative immune epitopes. The shortlisted epitopes, specific against Cytotoxic T Lymphocytes, Helper T-cell Lymphocytes, and linear B-Cell, were used to design the mRNA and multi-epitopes vaccine (MEVC). Initial validations confirmed the antigenic and non-allergenic properties of these constructs, followed by docking with the immune receptor, TLR-5, which resulted in robust interactions. The interaction pattern that followed in the docking complex included formation of 5 hydrogen bonds, 2 salt bridges, and 165 non-bonded contacts. This stronger binding affinity was also assessed through using the mmGBSA approach, showing a total of free binding energy of -34.64 kcal/mol. Further validations based on in silico cloning revealed a CAI score of 0.98 and an optimal percentage of GC contents (54.4%) indicated a putatively higher expression of the vaccine construct in Escherichia coli. Moreover, immune simulation revealed strong antibodies production upon the injection of the designed MEVC that resulted in the highest peaks of IgM+ IgG production (>3,500) between 10 and 15 days. In conclusion the current study provide basis for vaccine designing against the emerging A. xylosoxidans, which demands further experimental studies for in vitro and in vivo validations.

Familial clustering of hepatitis C virus in a Pakistani population.

Pakistan has the second-highest burden of hepatitis C patients in the world. A total of 683 individuals, who visited the Liver Clinic during the study period, were screened for the presence of hepatitis C virus (HCV) infection. A total of 534 individuals who showed positive HCV infection were grouped into the case group and 149 individuals with HCV negative status were grouped into the control group. A detailed questionnaire was used to collect demographic, clinical, HCV risk factor, and familial clustering data. HCV familial clustering was found in 30.1% in the case group compared with 17.4% in the control group. We also found 17% of patients had spouses who were also infected with HCV compared to 4% spouse infection in the control group. Only 3.7% of patients had HCV positive mothers. These results were further expanded by regression analysis that showed that family history and sexual history are independent risk factors for transmission of hepatitis C infection and mother's history has no significance as a risk factor for transmission. The major risk factor for getting HCV infection are dental procedures, unsafe injections, surgery, and blood transfusions. There is a strong need to increase awareness about HCV transmission routes among positive patients to reduce the chances of HCV familial clustering.

CORRIGENDUM to: Correlation of Apolipoprotein B mRNA-editing Enzyme, Catalytic Polypeptide- like 3G Genetic Variant rs8177832 with HIV-1 Predisposition in Pakistani Population.

Due to oversight of an author, in the manuscript entitled "Correlation of Apolipoprotein B mRNA-editing Enzyme, Catalytic Polypeptide- like 3G Genetic Variant rs8177832 with HIV-1 Predisposition in Pakistani Population" one author's name in the authors' list was erroneously published in the Journal "Current HIV Research" 2018; 16(4): 297-301.

Evaluation of Three Rapid Screening Tests for Detection of Hepatitis C Antibodies on Mass Scale.

Hepatitis C virus (HCV) is a leading health problem across the globe. Only 20% of HCV positive individuals know their positive disease status. Effective HCV screening tests are required to screen both general and high-risk populations and identify the silent cases of HCV. In this study, we analyzed the performance of three rapid HCV screening kits. A total of 300 subjects from three populations groups, were enrolled from Rawalpindi and Islamabad cities of Pakistan. The three groups were blood donors (n = 50), pregnant women (n = 50), and hepatitis C positive individuals (200). Blood samples of all the individuals were screened on three rapid screening tests for anti-HCV: CTK Biotech's OnSite HCV Ab Rapid Test, SD Bioline One Step anti-HCV test, and Intec Products Advanced Quality Rapid Anti-HCV Test. The performance of these three rapid tests was also compared with the Roche Anti-HCV II test performed on the cobas 601 platform based on the electrochemiluminescence immunoassay principle. In total, 300 samples were analyzed in this study, out of which 208 were positive for anti-HCV positive and 92 were negative for anti-HCV. The sensitivities of the Intec product, SD Bioline, and CTK Biotech were 98.56%, 97.59%, and 95.67%, respectively. The specificity of SD Bioline and CTK Biotech were 100%, whereas Intec products showed 98.91% specificity. The positive predictive value (PPV) of SD Bioline and CTK Biotech was 100%, but Intec products showed 99.51% PPV. The negative predictive values of the Intec product, SD Bioline, and CTK Biotech were 96.80%, 94.84%, and 91.09%, respectively. There is a dire need to speed up HCV screening to achieve the targets in the World Health Organization global viral hepatitis strategy (2016-2021). The rapid tests evaluated in this study can be used in hepatitis screening on much larger scales.