Showing 5 results for Protein-Protein Interaction
F. Zare Mirak-Abad, Z. Ghorbanali,
Volume 10, Issue 2 (7-2019)
Abstract
A biological network represents the interaction between a set of macromolecules to drive a particular biological process. In a biological environment, abnormalities happen not only in one molecule but also through a biological network. One of the most effective methods to detect anomaly is the comparison between healthy and diseased networks. In this regard, biological network alignment is one of the most efficient ways to find the difference between healthy and diseased cells. This problem, protein-protein interaction network alignment, has been raised in two main types: Local network alignment and Global network alignment. According to the NP-completeness of this problem, different non-deterministic approaches have been proposed to tackle the Global network alignment problem. Recently, NetAl has been introduced as a common algorithm to align two networks. Although this algorithm can align two networks at the appropriate time, it does not consider biological features. In this study, we present a new framework called PRAF to improve the results of network alignment algorithms such as NetAl by considering some biological features like gene ontology (GO).
J. Hekmati, A. Alami , J. Zahiri,
Volume 10, Issue 4 (12-2019)
Abstract
Hordeum vulgare is a one-year-old herb of the Poaceae family. It is an important cereal used by humans which has been applied in many cases instead of wheat. The limitation of experimental methods is one of the important problems for identifying protein-protein interactions. So, in recent years, computational methods have played an important role in predicting and identifying protein-protein interactions. In this study, for constructing protein-protein interaction (PPI) network, the experimental PPI information of six model organisms includes Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Homo sapiens, Oryza sativa, and Arabidopsis thalian were extracted from the Intact database. Inparanoid was used for identifying barley orthologous proteins with model organisms. The Interolog method which was used in this study can predict protein-protein interactions by mapping protein interactions of the model organisms on orthologous proteins. After removing repetitive interactions, the final predicted barley PPI network contained 235966 interactions between 7350 proteins. This study is the first report presented on protein-protein interaction prediction in barley.
Farshid Shirafkan, Sajjad Gharaghani,
Volume 13, Issue 2 (1-2023)
Abstract
Moonlight proteins are a subset of multifunctional proteins in which more than one independent or usually distinct function occurs in a single polypeptide chain. Analyzing the interactive networks of proteins in the cell makes it possible to understand how complex processes cause disease. With the help of systems biology, larger and more complex systems can be studied, and the molecular basis of several diseases can be considered. The proteins of the human organism that are moonlight are mostly involved in cancer, anemia, and neurodegeneration. In this work, we created a subnet according to the human PPI network, in which the nodes, the proteins that cause the three selected diseases, and the edges, are the connection of these proteins with each other. We measured the power of the indirect effects of non-disease mediators between the three disease groups and identified key disease-binding intermediate proteins. The results show the relationship between mediator role and centrality and between mediator role and functional properties of these proteins. We have shown that a protein that plays a key indirect mediator between two diseases is not necessarily a hub in the PPI network. Therefore, as hub proteins are considered, intermediate proteins should be considered. We have observed that the mediators between anemia and neurodegeneration diseases are functionally important in the cell. The mediator proteins suggested herein should be experimentally tested as hypothetical disease-related proteins.
Volume 21, Issue 1 (1-2019)
Abstract
Peroxidases (POXs) and Catalases (CATs) are the main antioxidant enzymes involved in scavenging H2O2 in living cells. Different POXs and CATs may be capable of exhibiting interaction with the constituents of the plant cell. Whereas the activity or gene expression of POXs and CATs has been investigated in potato plants, their interactions with other proteins in this crop have not been investigated till now. Determining Protein-Protein Interaction (PPI) networks could be important in providing crucial insights into the regulation of plant defense responses to biotic and abiotic stresses. STRING analysis revealed interaction of cationic, suberization-associated anionic, and Class III peroxidases in potato with several enzymes involved in lignin biosynthesis and phenylpropanoid pathways, which was in accordance with close phylogenetic relationship of the three potato peroxidases investigated in this study. The CAT1 enzyme in potato interacted with several enzymes involved in ROS production. Phylogenetic analysis of the CAT1 and CAT2 genes in this plant species referred to their close relationship. Demonstrating how each isoform of these enzymes responds to environmental stimuli and how it interacts with other proteins at transcriptional, translational, and post-translational levels seems to be useful in designing novel and effective plant protection strategies against different stresses.
Volume 25, Issue 4 (5-2023)
Abstract
Mating in honeybees causes dramatic changes not only in its behavior and physiology but in genes’ transcriptional level. To determine the molecular mechanisms regulating post-mating behavioral changes, we examined gene expression modification and exon-specific expression of the virgin queen versus the queen injected with semen in hemocoel. The DESeq2 package of R was used to identify the Differentially Expressed Genes (DEGs). The DEGs were selected for functional enrichment analysis and Protein-Protein Interaction (PPI) network construction. We also performed differential exon usage analysis using the DEXseq R package. Results identified a significant expression (FDR< 0.05) of a total of 971 genes between two groups of insects. The mating process produced significant changes in the expression of cell surface receptor signaling pathway, innate immune response, extracellular region, proteinaceous extracellular matrix, nucleous, G-protein coupled receptor activity, heme binding, and transmembrane transporter activity genes. Protein-Protein Interaction (PPI) network shows that LOC552504 (titin-like) could be considered as a super-hub gene in the mating process of queens. In addition, we identified exons that were differentially expressed in two groups of honeybee queens. At 10% FDR, we found significant differential exon usage in 79 genes. Among them, GB55396 gene had the most differences in exon usage and could be the best candidate gene for mating and reproductive activation in queens.
