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Showing 4 results for Bioinformatics
Somayeh Moghaddam, Esmaeil Babaei,
Volume 30, Issue 1 (3-2022)
Abstract
Introduction: Long non-coding RNAs (lncRNAs) and miRNAs belong to a class of non-coding RNAs (ncRNAs) that play important roles and functions in the regulation of the expression of genes in main biological processes, such as cell proliferation, apoptosis, and differentiation. LncRNAs can potentially affect miRNAs in the forms of cis/trans to modulate their regulatory role. In this study, mRNA, miRNA, and lncRNA gene networks were predicted by web-based programs for three ectodermal pathway markers (BMP4, NOG, FGF8) in the mouse embryonic stem cells.
Material & Methods: In this theoretical bioinformatics study, the miRNAs of the target genes (BMP4, NOG, and FGF8) were extracted and examined by MirWalk and TARGETSCAN databases to finally obtain the common miRNAs of these three genes. Following that, the target lncRNAs for common miRNAs were then extracted from the DIANA-Tool database.
(Ethic code: 100/21560/2/پ)
Findings: MiRs mmu-miR-92a-2-5p, mmu-miR-129b-5p, mmu-miR-130b-5p, mmu-miR-692, mmu-miR-7009-3P, mmu-miR-7116-3p, and mmu-miR-7689-3p may affect the function of lncRNAs, including Kcnq1ot1, Gm26812, Gm4117, Gm11837, 4930423MO2Rik, Malat1, Gm12594, Gm3414, 5830444B04Rik, Gm2464, and NEAT1.
Discussion & Conclusion: Due to the mutual relationships among lncRNA, miRNA, and mRNA, our results provided a novel perspective on lncRNAs for future research and experimental studies on ectodermal differentiation pathways and molecular mechanisms.
Bahareh Mazrouei, Mohammad Mehdi Heidari, Mehri Khatami,
Volume 30, Issue 3 (8-2022)
Abstract
Introduction: Abortion is a common complication that refers to the early termination of pregnancy with the death of the fetus before the 20th week of pregnancy. Previous studies show that many genes are involved in this disease, including the CX3CR1 gene, which is one of the inflammatory response genes in the immune system. The pathogenicity of these variants was determined in this study using bioinformatics analysis.
Material & Methods: In this study, the effects of rs3732378 and rs3732379 mutation were predicted using bioinformatics tools including SIFT, PolyPhen2, PROVEAN, Predict SNP, and Exome Variant Server. Changes in the stability of mutant proteins were investigated using I-Mutant and DynaMut tools. Moreover, modeling of the protein structure, docking, and protein-ligand interaction were performed using SWISS-MODEL, SwissDock, and FRODOCK tools as well as PyMOL, Hawkdock, and MolSoft software, respectively.
Findings: Many polymorphisms related to the CX3CR1 gene have been known to date. Out of 244 missense mutations in the dbSNP database, two variants (rs3732378 and rs3732379) have been reported in association with recurrent pregnancy loss related to the CX3CR1 gene. The results of bioinformatics analyses showed that both variants were predicted as pathogenic mutations and changed the stability of the protein structure and played a key role in interaction with the ligand.
Discussion & Conclusion: The findings of this study indicate that two missense mutations in the CX3CR1 gene are an important candidate for recurrent miscarriage and their identification in patients with recurrent miscarriage can be regarded as a risk factor.
Tooba Abdizadeh,
Volume 30, Issue 4 (10-2022)
Abstract
Introduction: COVID-19 is an acute respiratory infectious disease caused by the SARS-CoV-2 virus. There is an urgent need to discover antiviral drugs for better performance against new strains of coronaviruses (CoVs) due to the rapid spread of the disease despite scientific advances in vaccine development. This study aimed to evaluate the efficacy of quercetin and its analogues on the COVID-19 Mpro enzyme.
Material & Methods: In this descriptive-analytical study, the three-dimensional structures of quercetin analogues (20 compounds), standard drugs (ritonavir and lopinavir), and the COVID-19 Mpro enzyme were obtained from PubChem and PDB databases for bioinformatics study, respectively. Molecular docking studies of the compounds on the
Mpro were performed using MOE-2014 software. Afterward, the physicochemical properties and biological activity of the compounds were predicted using Swiss ADME, PASS, and Swiss Target Prediction software.
Findings: The findings of the present study showed that the most important bonds involved in drug-receptor binding are hydrogen, hydrophobic, and π-π interaction bonds. The best docking results were obtained for Baicalein, Genistein, Naringenin, and Quercetin compounds with strong binding energy (-12.83 to -13.54 kcal/mol), compared to ritonavir and lopinavir. These compounds have a greater tendency to bind to the catalytic amino acids His41 and Cys145 and other key amino acids of the active site of the COVID-19 Mpro enzyme.
Discussion & Conclusion: Based on the results of bioinformatics studies, quercetin analogues had more effective inhibition than standard chemical drugs due to their suitable placement in the active site of the main protease enzyme of COVID-19 and can be good candidates for in vitro and in vivo studies.
Habib Motieghader,
Volume 32, Issue 3 (8-2024)
Abstract
Introduction: Breast cancer, which is one of the most common cancers with high mortality in women, has always been the focus of researchers, and every day, scientists are trying to identify mechanisms, genes, and medicines related to this disease. Nowadays, bioinformatics methods are used to identify and repurpose drugs for the treatment of diseases, especially cancer.
Material & Methods: In this study, bioinformatics and biological network analysis were used to identify candidate drugs for breast cancer treatment. In this regard, analysis of the protein interaction network and drug-gene network were employed. The needed data were collected from the GEO database with the access code GSE54002. For the selected data set, genes with significant expression changes between two groups of healthy people and people with breast cancer cases were selected and considered primary genes. Thereafter, the protein-protein interaction network was constructed using the STRING database, and a significant gene module was obtained from the network. Following that, gene ontology studies and biological pathways were conducted. Next, the drug-gene network was constructed to identify drugs that target module genes and were introduced as essential drugs for the treatment of breast cancer. Cytoscape software and STRING and OncoDB databases were used to reconstruct and analyze the networks.
Results: After analyzing the protein-protein interaction network and the drug-gene network, three important drugs that target the genes of the modules were identified and introduced as candidate drugs for the treatment of breast cancer. These drugs were RG-1530, R-406, and GW441756x.
Discussion & Conclusion: The obtained results demonstrated that the introduced drugs (RG-1530, R-406, and GW441756x) can be effective in the treatment of breast cancer
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