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Introduction: Several recent studies pointed out that chromodomain-helicase-DNA-binding protein 1-like (CHD1L) is a putative oncogene in many human tumors. However, up to date, there is no pan-cancer analysis performed to study the different aspects of this gene expression and behavior in tumor tissues.Methods: Here, we applied several bioinformatics tools to make a comprehensive analysis for CHD1L. Firstly we assessed the expression of CHD1L in several types of human tumors and tried to correlate that with the stage and grade of the analyzed tumors. Following that, we performed a survival analysis to study the correlation between CHD1L upregulation in tumors and the clinical outcome. Additionally, we investigated the mutation forms, the correlation with several immune cell infiltration, and the potential molecular mechanisms of CHD1L in the tumor tissue.Result and discussion: The results demonstrated that CHD1L is a highly expressed gene across several types of tumors and that was correlated with a poor prognosis for most cancer patients. Moreover, it was found that CHD1L affects the tumor immune microenvironment by influencing the infiltration level of several immune cells. Collectively, the current study provides a comprehensive overview of the oncogenic roles of CHD1L where our results nominate CHD1L as a potential prognostic biomarker and target for antitumor therapy development.

Introduction:Klebsiella pneumoniae (K. pneumoniae) and Pseudomonas aeruginosa (P. aeruginosa) are the most common Gram-negative bacteria associated with pneumonia and coinfecting the same patient. Despite their high virulence, there is no effective vaccine against them.Methods: In the current study, the screening of several proteins from both pathogens highlighted FepA and OmpK35 for K. pneumonia in addition to HasR and OprF from P. aeruginosa as promising candidates for epitope mapping. Those four proteins were linked to form a multitope vaccine, that was formulated with a suitable adjuvant, and PADRE peptides to finalize the multitope vaccine construct. The final vaccine’s physicochemical features, antigenicity, toxicity, allergenicity, and solubility were evaluated for use in humans.Results: The output of the computational analysis revealed that the designed multitope construct has passed these assessments with satisfactory scores where, as the last stage, we performed a molecular docking study between the potential vaccine construct and K. pneumonia associated immune receptors, TLR4 and TLR2, showing affinitive to both targets with preferentiality for the TLR4 receptor protein. Validation of the docking studies has proceeded through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for K. pneumoniae and P. aeruginosa coinfection. Here, we describe the approach for the design and assessment of our potential vaccine.

Background: Mammalian WD-repeat protein 12 (WDR12), a family member of proteins containing repeats of tryptophan-aspartic acid (WD), is a potential homolog of yeast Ytm1p and consists of seven repeats of WD.Aim of the study: This study aims to investigate the potential oncogenic effects of WDR12 in various human malignancies throughout a pan-cancer analysis that has been carried out to examine the various patterns in which this gene is expressed and behaves in tumor tissues.Methods: Herein, we used The Cancer Genome Atlas (TCGA) and various computational tools to explore expression profiles, prognostic relevance, genetic mutations, immune cell infiltration, as well as the functional characteristics of WDR12 in multiple human cancers.Results: We found that WDR12 was inconsistently expressed in various cancers and that variations in WDR12 expression predicted survival consequences for cancer patients. Furthermore, we observed a significant correlation between WDR12 gene mutation levels and the prognosis of some tumors. Furthermore, significant correlations were found between WDR12 expression patterns and cancer-associated fibroblast (CAF) infiltration, myeloid-derived suppressor cells (MDSCs), tumor mutation burden, microsatellite instability and immunoregulators. Ultimately, pathway enrichment analysis revealed that WDR12-related pathways are involved in carcinogenesis.Conclusions: The findings of our study are stisfactory, demonstrating that WDR12 could serve as a promising reliable prognostic biomarker, as well as a therapeutic target for novel cancer therapeutic approaches.

BackgroundA deep understanding of the causes of liability to SARS-CoV-2 is essential to develop new diagnostic tests and therapeutics against this serious virus in order to overcome this pandemic completely. In the light of the discovered role of antimicrobial peptides [such as human b-defensin-2 (hBD-2) and cathelicidin LL-37] in the defense against SARS-CoV-2, it became important to identify the damaging missense mutations in the genes of these molecules and study their role in the pathogenesis of COVID-19.MethodsWe conducted a comprehensive analysis with multiple in silico approaches to identify the damaging missense SNPs for hBD-2 and LL-37; moreover, we applied docking methods and molecular dynamics analysis to study the impact of the filtered mutations.ResultsThe comprehensive analysis reveals the presence of three damaging SNPs in hBD-2; these SNPs were predicted to decrease the stability of hBD-2 with a damaging impact on hBD-2 structure as well. G51D and C53G mutations were located in highly conserved positions and were associated with differences in the secondary structures of hBD-2. Docking-coupled molecular dynamics simulation analysis revealed compromised binding affinity for hBD-2 SNPs towards the SARS-CoV-2 spike domain. Different protein–protein binding profiles for hBD-2 SNPs, in relation to their native form, were guided through residue-wise levels and differential adopted conformation/orientation.ConclusionsThe presented model paves the way for identifying patients prone to COVID-19 in a way that would guide the personalization of both the diagnostic and management protocols for this serious disease.

The NRAS gene is a well-known oncogene that acts as a major player in carcinogenesis. Mutations in the NRAS gene have been linked to multiple types of human tumors. Therefore, the identification of the most deleterious single nucleotide polymorphisms (SNPs) in the NRAS gene is necessary to understand the key factors of tumor pathogenesis and therapy. We aimed to retrieve NRAS missense SNPs and analyze them comprehensively using sequence and structure approaches to determine the most deleterious SNPs that could increase the risk of carcinogenesis. We also adopted structural biology methods and docking tools to investigate the behavior of the filtered SNPs. After retrieving missense SNPs and analyzing them using six in silico tools, 17 mutations were found to be the most deleterious mutations in NRAS. All SNPs except S145L were found to decrease NRAS stability, and all SNPs were found on highly conserved residues and important functional domains, except R164C. In addition, all mutations except G60E and S145L showed a higher binding affinity to GTP, implicating an increase in malignancy tendency. As a consequence, all other 14 mutations were expected to increase the risk of carcinogenesis, with 5 mutations (G13R, G13C, G13V, P34R, and V152F) expected to have the highest risk. Thermodynamic stability was ensured for these SNP models through molecular dynamics simulation based on trajectory analysis. Free binding affinity toward the natural substrate, GTP, was higher for these models as compared to the native NRAS protein. The Gly13 SNP proteins depict a differential conformational state that could favor nucleotide exchange and catalytic potentiality. A further application of experimental methods with all these 14 mutations could reveal new insights into the pathogenesis and management of different types of tumors.

Marburg virus (MARV) is one of the most harmful zoonotic viruses with deadly effects on both humans and nonhuman primates. Because of its severe outbreaks with a high rate of fatality, the world health organization put it as a risk group 4 pathogen and focused on the urgent need for the development of effective solutions against that virus. However, up to date, there is no effective vaccine against MARV in the market. In the current study, the complete proteome of MARV (seven proteins) was analyzed for the antigenicity score and the virulence or physiological role of each protein where we nominated envelope glycoprotein (Gp), Transcriptional activator (VP30), and membrane-associated protein (VP24) as the candidates for epitope prediction. Following that, a vaccine construct was designed based on CTL, HTL, and BCL epitopes of the selected protein candidates and to finalize the vaccine construct, several amino acid linkers, β-defensin adjuvant, and PADRE peptides were incorporated. The generated potential vaccine was assessed computationally for several properties such as antigenicity, allergenicity, stability, and other structural features where the outcomes of these assessments nominated this potential vaccine to be validated for its binding affinity with two molecular targets TLR-8 and TLR-4. The binding score and the stability of the vaccine-receptor complex, which was deeply studied through molecular docking-coupled dynamics simulation, supported the selection of our designed vaccine as a putative solution for MARV that should be validated through future wet-lab experiments. Here, we describe the computational approach for designing and analysis of this potential vaccine.

Escherichia coli (E. coli) is a Gram-negative bacterium that belongs to the family Enterobacteriaceae. While E. coli can stay as an innocuous resident in the digestive tract, it can cause a group of symptoms ranging from diarrhea to live threatening complications. Due to the increased rate of antibiotic resistance worldwide, the development of an effective vaccine against E. coli pathotypes is a major health priority. In this study, a reverse vaccinology approach along with immunoinformatics has been applied for the detection of potential antigens to develop an effective vaccine. Based on our screening of 5,155 proteins, we identified lipopolysaccharide assembly protein (LptD) and outer membrane protein assembly factor (BamA) as vaccine candidates for the current study. The conservancy of these proteins in the main E. coli pathotypes was assessed through BLASTp to make sure that the designed vaccine will be protective against major E. coli pathotypes. The multitope vaccine was constructed using cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes with suitable linkers and adjuvant. Following that, it was analyzed computationally where it was found to be antigenic, soluble, stable, and non-allergen. Additionally, the adopted docking study, as well as all-atom molecular dynamics simulation, illustrated the promising predicted affinity and free binding energy of this constructed vaccine against the human Toll-like receptor-4 (hTLR-4) dimeric state. In this regard, wet lab studies are required to prove the efficacy of the potential vaccine construct that demonstrated promising results through computational validation.