Biology subjects

Araf, Y.

Publications and source records attributed to Araf, Y..

6 recordsLinked to original sources

bioRxiv2023

Unravelling the Oncogenic Potential and Prognostic Significance of CKS1B in Human Lung Adenocarcinoma and Squamous Cell Carcinoma: A Comprehensive Computational Analysis

Lung cancer (LC) confers to radical malignancy with a limited recourse of therapy worldwide. Consequently, LC has become the leading cause of cancer deaths in both men and women globally. Non-small cell lung cancer (NSCLC), one of the major LC types and accountable for a greater share of these cancer-associated deaths, further branches out to adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC). A dearth of evident clinical symptoms coupled with the diagnosis feasibility only after advanced metastasis raises the need for precision in treatment apart from the existing chemical drug treatments. Precise guidance can be entailed by targeted therapies, utilizing the potential and thoroughly evaluated differentially expressed genes of cancer under speculation for tumor treatments. Cyclin-dependent kinase regulatory subunit 1B (CKS1B), a member of the conserved cyclin kinase subunit 1 (CKS1) protein family, regulates the cell cycle. Increasing evidence revealed that up-regulation of the CKS1B gene is associated with multiple human-related cancers, indicates its potential use as a targeted therapeutic for early detection and treatment. CKS1B has been found to be associated with poor prognosis in both LUAD and LUSC, while the prognostic significance of CKS1B in other types of cancer is not well established. Herein, we have performed a comprehensive bioinformatics analysis of factors involved in LUAD and LUSC with CKS1B and discussed its role as a potential biomarker for early lung cancer detection and treatment. While these evaluations demonstrate the immunotherapeutic features and prognostic value of CKS1B, further in vivo and in vitro studies are required to determine the accuracy of final applications.

cancer biology↗

bioRxiv2022

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

SARS-CoV-2 continues to spread and evolve worldwide, despite intense efforts to develop multiple vaccines and therapeutic options against COVID-19. Moreover, the precise role of SARS-CoV-2 in the pathophysiology of the nasopharyngeal tract (NT) is still unfathomable. Therefore, we used the machine learning methods to analyze 22 RNA-seq datasets from COVID-19 patients (n=8), recovered individuals (n=7), and healthy individuals (n=7) to find disease-related differentially expressed genes (DEGs). In comparison to healthy controls, we found 1960 and 153 DEG signatures in COVID-19 patients and recovered individuals, respectively. We compared dysregulated DEGs to detect critical pathways and gene ontology (GO) connected to COVID-19 comorbidities. 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 most 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, we detected DEGs impacted by SARS-CoV-2 infection and mediated by TFs and miRNA expression, indicating that SARS-CoV-2 infection may contribute to various comorbidities. These pathogenetic findings can provide some crucial insights into the complex interplay between COVID-19 and the recovery stage and support its importance in the therapeutic development strategy to combat against COVID-19 pandemic. IMPORTANCEDespite it has now been over two years since the beginning of the COVID-19 pandemic, many crucial questions about SARS-CoV-2 infection and the different COVID-19 symptoms it causes remain unresolved. An intriguing question about COVID-19 is how SARS-CoV-2 interplays with the host during infection and how SARS-CoV-2 infection can cause so many disease symptoms. Our analysis of three different datasets (COVID-19, recovered, and healthy) revealed significantly higher DEGs in COVID-19 patients than recovered humans and healthy controls. Some of these DEGs were found to be co-expressed in both COVID-19 patients. They recovered humans supporting the notion that DEGs level is directly correlated with the viral load, disease progression, and different comorbidities. The protein-protein interaction consisting of 24 nodes and 72 edges recognized eight hub-nodes as potential hub-proteins (i.e., RPL4, RPS4X, RPL19, RPS12, RPL19, EIF3E, MT-CYB, and MT-ATP6). Protein-chemical interaction analysis identified three chemical agents (e.g., Valproic Acid, Alfatoxin B1, and Cyclosporine) enriched in COVID-19 patients and recovered individuals. Mental retardation, mental deficiency, intellectual disability, muscle hypotonia, micrognathism, and cleft palate were the significant diseases associated with COVID-19 by sharing DEGs.

bioinformatics↗

bioRxiv2022

Exploring different virulent proteins of human respiratory syncytial virus for designing a novel epitope-based polyvalent vaccine: Immunoinformatics and molecular dynamics approaches

Human Respiratory Syncytial Virus (RSV) is one of the most prominent causes of lower respiratory tract infections (LRTI), contributory to infecting people from all age groups - a majority of which comprises infants and children. The implicated severe RSV infections lead to numerous deaths of multitudes of the overall population, predominantly the children, every year. Consequently, despite several distinctive efforts to develop a vaccine against the RSV as a potential countermeasure, there is no approved or licensed vaccine available yet, to control the RSV infection effectively. Therefore, through the utilization of immunoinformatics tools, a computational approach was taken in this study, to design and construct a multi-epitope polyvalent vaccine against the RSV-A and RSV-B strains of the virus. Potential predictions of the T-cell and B-cell epitopes were followed by extensive tests of antigenicity, allergenicity, toxicity, conservancy, homology to human proteome, transmembrane topology, and cytokine-inducing ability. The most promising epitopes (i.e. 13 CTL epitopes, 9 HTL epitopes, and 10 LBL epitopes) exhibiting full conservancy were then selected for designing the peptide fusion with appropriate linkers, having hBD-3 as the adjuvant. The peptide vaccine was modeled, refined, and validated to further improve the structural attributes. Following this, molecular docking analysis with specific TLRs was carried out which revealed excellent interactions and global binding energies. Additionally, molecular dynamics (MD) simulation was conducted which ensured the stability of the interactions between vaccine and TLR. Furthermore, mechanistic approaches to imitate and predict the potential immune response generated by the administration of vaccines were determined through immune simulations. Owing to an overall evaluation, in silico cloning was carried out in efforts to generate recombinant pETite plasmid vectors for subsequent mass production of the vaccine peptide, incorporated within E.coli. However, more in vitro and in vivo experiments can further validate its efficacy against RSV infections.

immunology↗

bioRxiv2020

Choice of assemblers has a critical impact on de novo assembly of SARS-CoV-2 genome and characterizing variants

BackgroundCoronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global pandemic following its initial emergence in China. Using next-generation sequencing technologies, a large number of SARS-CoV-2 genomes are being sequenced at an unprecedented rate and being deposited in public repositories. For the de novo assembly of the SARS-CoV-2 genomes, a myriad of assemblers is being used, although their impact on the assembly quality has not been characterized for this virus. In this study, we aim to understand the variabilities on assembly qualities due to the choice of the assemblers. ResultsWe performed 6,648 de novo assemblies of 416 SARS-CoV-2 samples using 8 different assemblers with different k-mers. We used Illumina paired-end sequencing reads and compared the genome assembly quality to that of different assemblers. We showed the choice of assemblers plays a significant role in reconstructing the SARS-CoV-2 genome. Two metagenomic assemblers e.g. MEGAHIT and metaSPAdes performed better compared to others in most of the assembly quality metrics including, recovery of a larger fraction of the genome, constructing larger contigs and higher N50, NA50 values etc. We showed that at least 09% (259/2,873) of the variants present in the assemblies between MEGAHIT and metaSPAdes are unique to the assembly methods. ConclusionOur analyses indicate the critical role of assembly methods for assembling SARS-CoV-2 genome using short reads and their impact on variant characterization. This study could help guide future studies to determine which assembler is best suited for the de novo assembly of virus genomes.

bioinformatics↗

bioRxiv2020

The Essential Facts of Wuhan Novel Coronavirus Outbreak in China and Epitope-based Vaccine Designing against 2019-nCoV

Wuhan Novel Coronavirus disease (COVID-19) outbreak has become a global outbreak which has raised the concern of scientific community to design and discover a definitive cure against this deadly virus which has caused deaths of numerous infected people upon infection and spreading. To date, no antiviral therapy or vaccine is available which can effectively combat the infection caused by this virus. This study was conducted to design possible epitope-based subunit vaccines against the SARS-CoV-2 virus using the approaches of reverse vaccinology and immunoinformatics. Upon continual computational experimentation three possible vaccine constructs were designed and one vaccine construct was selected as the best vaccine based on molecular docking study which is supposed to effectively act against SARS-CoV-2. Later, molecular dynamics simulation and in silico codon adaptation experiments were carried out in order to check biological stability and find effective mass production strategy of the selected vaccine. Hopefully, this study will contribute to uphold the present efforts of the researches to secure a definitive treatment against this lethal virus.

immunology↗

bioRxiv2020

Curcumin Analogues as the Inhibitors of TLR4 Pathway in Inflammation and Their Drug Like Potentialities: A Computer-based Study

In this study Curcumin and their different analogues have been analyzed as the inhibitors of signaling proteins i.e., Cycloxygenase-2 (COX-2), Inhibitor of Kappa{beta} Kinase (IKK) and TANK binding kinase-1 (TBK-1) of Toll Like Receptor 4 (TLR4) pathway involved in inflammation using computational tools. Multiple analogues showed better binding affinity than the approved drugs for the respective targets. Upon continuous computational exploration 6-Gingerol, Yakuchinone A and Yakuchinone B were identified as the best inhibitors of COX-2, IKK and TBK-1 respectively. Then their drug like potentialities were analyzed in different experiments where they also performed sound and similar. Hopefully, this study will uphold the efforts of researchers to identify anti-inflammatory drugs from natural sources.

pharmacology and toxicology↗