scholarly journals Network Protein Interaction in Parkinson's Disease and Periodontitis Interplay: A Bioinformatic Analysis

Author(s):  
João Botelho ◽  
Paulo Mascarenhas ◽  
José João Mendes ◽  
Vanessa Machado

Recent studies supported a clinical association between Parkinson’s Disease (PD) and periodontitis. Hence, investigating possible protein interactions between these two conditions is of interest. In this study, we conducted a protein-protein network interaction analysis with recognized genes encoding proteins for PD and periodontitis. Genes of interest were collected via GWAS database. Then, we conducted a protein interaction analysis using STRING database, with a highest confidence cut-off of 0.9. Our protein network casted a comprehensive analysis of potential protein-protein interactions between PD and periodontitis. This analysis may underpin valuable information for new candidate molecular mechanisms between PD and periodontitis and may serve new potential targets for research purposes. These results should be carefully interpreted giving the limitations of this approach.

Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1385
Author(s):  
João Botelho ◽  
Paulo Mascarenhas ◽  
José João Mendes ◽  
Vanessa Machado

Recent studies supported a clinical association between Parkinson’s disease (PD) and periodontitis. Hence, investigating possible interactions between proteins associated to these two conditions is of interest. In this study, we conducted a protein–protein network interaction analysis with recognized genes encoding proteins with variants strongly associated with PD and periodontitis. Genes of interest were collected via the Genome-Wide Association Studies (GWAS) database. Then, we conducted a protein interaction analysis, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, with a highest confidence cutoff of 0.9 and sensitivity analysis with confidence cutoff of 0.7. Our protein network casts a comprehensive analysis of potential protein–protein interactions between PD and periodontitis. This analysis may underpin valuable information for new candidate molecular mechanisms between PD and periodontitis and may serve new potential targets for research purposes. These results should be carefully interpreted, giving the limitations of this approach.


Author(s):  
Yago Leira ◽  
Paulo Mascarenhas ◽  
Juan Blanco ◽  
Tomás Sobrino ◽  
José João Mendes ◽  
...  

The clinical interaction between stroke and periodontitis has been consistently studied and confirmed. Hence, forecasting potentially new protein interactions in this association using bioinformatic strategies presents potential interest. In this exploratory study, we conducted a protein-protein network interaction (PPI) search with documented encoded proteins for both stroke and periodontitis. Genes of interest were collected via GWAS database. The STRING database was used to predict the PPI networks, first in a sensitivity purpose (confidence cut-off of 0.7), and then with a highest confidence cut-off (0.9). Genes over-representation was inspected in the final network. As a result, we foresee a prospective protein network of interaction between stroke and periodontitis. Inflammation, pro-coagulant/pro-thrombotic state and ultimately atheroma plaque rupture is the main biological mechanism derived from the network. These pilot results may pave the way to future molecular and therapeutic studies to further comprehend the mechanisms between these two conditions.


2019 ◽  
Vol 13 (S1) ◽  
Author(s):  
Qingqing Li ◽  
Zhihao Yang ◽  
Zhehuan Zhao ◽  
Ling Luo ◽  
Zhiheng Li ◽  
...  

Abstract Background Protein–protein interaction (PPI) information extraction from biomedical literature helps unveil the molecular mechanisms of biological processes. Especially, the PPIs associated with human malignant neoplasms can unveil the biology behind these neoplasms. However, such PPI database is not currently available. Results In this work, a database of protein–protein interactions associated with 171 kinds of human malignant neoplasms named HMNPPID is constructed. In addition, a visualization program, named VisualPPI, is provided to facilitate the analysis of the PPI network for a specific neoplasm. Conclusions HMNPPID can hopefully become an important resource for the research on PPIs of human malignant neoplasms since it provides readily available data for healthcare professionals. Thus, they do not need to dig into a large amount of biomedical literatures any more, which may accelerate the researches on the PPIs of malignant neoplasms.


2020 ◽  
Vol 21 (6) ◽  
pp. 2009 ◽  
Author(s):  
Wenming Qiu ◽  
Juliana Soares ◽  
Zhiqian Pang ◽  
Yixiao Huang ◽  
Zhonghai Sun ◽  
...  

Huanglongbing (HLB), a bacterial disease caused by Candidatus Liberibacter asiaticus (CLas), is a major threat to the citrus industry. In a previous study conducted by our laboratory, several citrus transgenic trees expressing the Arabidopsis thaliana NPR1 (AtNPR1) gene remained HLB-free when grown in a field site under high HLB disease pressure. To determine the molecular mechanisms behind AtNPR1-mediated tolerance to HLB, a transcriptome analysis was performed using AtNPR1 overexpressing transgenic trees and non-transgenic trees as control, from which we identified 57 differentially expressed genes (DEGs). Data mining revealed the enhanced transcription of genes encoding pathogen-associated molecular patterns (PAMPs), transcription factors, leucine-rich repeat receptor kinases (LRR-RKs), and putative ankyrin repeat-containing proteins. These proteins were highly upregulated in the AtNPR1 transgenic line compared to the control plant. Furthermore, analysis of protein–protein interactions indicated that AtNPR1 interacts with CsNPR3 and CsTGA5 in the nucleus. Our results suggest that AtNPR1 positively regulates the innate defense mechanisms in citrus thereby boosting resistance and effectively protecting the plant against HLB.


Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 787
Author(s):  
Yago Leira ◽  
Paulo Mascarenhas ◽  
Juan Blanco ◽  
Tomás Sobrino ◽  
José João Mendes ◽  
...  

The clinical interaction between stroke and periodontitis has been consistently studied and confirmed. Hence, exploring potentially new protein interactions in this association using bioinformatic strategies presents potential interest. In this exploratory study, we conducted a protein–protein network interaction (PPI) search with documented encoded proteins for both stroke and periodontitis. Genes of interest were collected via GWAS database. The STRING database was used to predict the PPI networks, first in a sensitivity purpose (confidence cut-off of 0.7), and then with a highest confidence cut-off (0.9). Genes over-representation was inspected in the final network. As a result, we foresee a prospective protein network of interaction between stroke and periodontitis. Inflammation, pro-coagulant/pro-thrombotic state and, ultimately, atheroma plaque rupture is the main biological mechanism derived from the network. These pilot results may pave the way to future molecular and therapeutic studies to further comprehend the mechanisms between these two conditions.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Priyanka Kapoor ◽  
Aman Chowdhry ◽  
Dinesh Kumar Bagga ◽  
Deepak Bhargava ◽  
S. Aishwarya

Abstract Background MicroRNAs (miRNAs) are non-coding short, single-stranded RNA molecules that may serve as biomarkers for various inflammatory and molecular mechanisms underlying bone and tissue remodeling consequent to orthodontic force application. Methods A thorough literature search in major databases was conducted in March 2021 to generate evidence for miRNAs in orthodontics, with prior PROSPERO registration. The initial search revealed 920 articles, subjected to strict selection criteria according to PRISMA, and resulted in final inclusion of four studies. Quality assessment by QUADAS-2 classified three studies as unclear risk-of-bias while the applicability was high. Further, bioinformatic analysis was performed to identify the target genes from the miRNA database (miRDB) and TargetScan databases and their protein-protein interaction pathways with the STRING analysis. Results Multiple miRNAs in gingival crevicular fluid (GCF) of orthodontic patients were seen, including miRNA-21, 27(a/b), 29(a/b/c), 34,146(a/b), 101, and 214 along with matrix metalloproteinases (MMPs)-1, 2, 3, 8, 9, 14 in one study. A statistically significant increase in expression of miRNA-29a/b/c,101, 21 from pre-treatment (before initiation of retraction) was seen to reach a peak at 4–6 weeks (wk) of retraction. On the contrary, miRNA-34a showed downregulation from the 1 day to 4 wk of retraction and also, negatively correlated with MMPs-2,9,14 levels at the same observation times. The distance of canine movement showed mild correlation with miRNA-27a/b, 214 at 2 wk of retraction. Bioinformatics revealed 1213 mutual target genes which were analyzed for inter-relational pathways using Cytoscape plugin, MCODE. Further, 894 prominent protein interactions were identified from the STRING database and SMAD4, IGF1, ADAMTS6, COL4A1, COL1A1, COL3A1, FGFR1, COL19A1, FBN1, COL5A1, MGAT4A, LTBP1, MSR1, COL11A1, and COL5A3 were recognized as the hub genes. Their interactions were able to isolate multiple miRNAs: hsa-miR-34a-5p, hsa-miR-29b-2-5p, hsa-miR-29b-3p, hsa-miR-34a-3p, hsa-miR-27a-5p, hsa-miR-29a-5p, hsa-miR-29b-1-5p, hsa-miR-29c-3p, hsa-miR-214-5p, hsa-miR-27a-3p, hsa-miR-29a-3p, hsamiR-146-5p, which were found promising as biomarkers for tooth movement. Conclusions Our results support using miRNAs as biomarkers in varied orthodontic study designs and for inter-relationships with pathological settings like periodontal disease, pre-malignancies, or conditions like obesity or metabolic irregularities, etc. The identified target genes and their protein interaction pathways can be used to propose precision therapies, focusing on ideal tooth movement with minimal iatrogenic side-effects.


Medicina ◽  
2019 ◽  
Vol 55 (5) ◽  
pp. 191 ◽  
Author(s):  
Md. Rezanur Rahman ◽  
Tania Islam ◽  
Md. Shahjaman ◽  
Toyfiquz Zaman ◽  
Hossain Md. Faruquee ◽  
...  

Background and objectives: Alzheimer’s disease (AD) is a progressive neurodegenerative disease that results in severe dementia. Having ischemic strokes (IS) is one of the risk factors of the AD, but the molecular mechanisms that underlie IS and AD are not well understood. We thus aimed to identify common molecular biomarkers and pathways in IS and AD that can help predict the progression of these diseases and provide clues to important pathological mechanisms. Materials and Methods: We have analyzed the microarray gene expression datasets of IS and AD. To obtain robust results, combinatorial statistical methods were used to analyze the datasets and 26 transcripts (22 unique genes) were identified that were abnormally expressed in both IS and AD. Results: Gene Ontology (GO) and KEGG pathway analyses indicated that these 26 common dysregulated genes identified several altered molecular pathways: Alcoholism, MAPK signaling, glycine metabolism, serine metabolism, and threonine metabolism. Further protein–protein interactions (PPI) analysis revealed pathway hub proteins PDE9A, GNAO1, DUSP16, NTRK2, PGAM2, MAG, and TXLNA. Transcriptional and post-transcriptional components were then identified, and significant transcription factors (SPIB, SMAD3, and SOX2) found. Conclusions: Protein–drug interaction analysis revealed PDE9A has interaction with drugs caffeine, γ-glutamyl glycine, and 3-isobutyl-1-methyl-7H-xanthine. Thus, we identified novel putative links between pathological processes in IS and AD at transcripts levels, and identified possible mechanistic and gene expression links between IS and AD.


Biomedicines ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 895
Author(s):  
Pavel Ershov ◽  
Leonid Kaluzhskiy ◽  
Yuri Mezentsev ◽  
Evgeniy Yablokov ◽  
Oksana Gnedenko ◽  
...  

A global protein interactome ensures the maintenance of regulatory, signaling and structural processes in cells, but at the same time, aberrations in the repertoire of protein–protein interactions usually cause a disease onset. Many metabolic enzymes catalyze multistage transformation of cholesterol precursors in the cholesterol biosynthesis pathway. Cancer-associated deregulation of these enzymes through various molecular mechanisms results in pathological cholesterol accumulation (its precursors) which can be disease risk factors. This work is aimed at systematization and bioinformatic analysis of the available interactomics data on seventeen enzymes in the cholesterol pathway, encoded by HMGCR, MVK, PMVK, MVD, FDPS, FDFT1, SQLE, LSS, DHCR24, CYP51A1, TM7SF2, MSMO1, NSDHL, HSD17B7, EBP, SC5D, DHCR7 genes. The spectrum of 165 unique and 21 common protein partners that physically interact with target enzymes was selected from several interatomic resources. Among them there were 47 modifying proteins from different protein kinases/phosphatases and ubiquitin-protein ligases/deubiquitinases families. A literature search, enrichment and gene co-expression analysis showed that about a quarter of the identified protein partners was associated with cancer hallmarks and over-represented in cancer pathways. Our results allow to update the current fundamental view on protein–protein interactions and regulatory aspects of the cholesterol synthesis enzymes and annotate of their sub-interactomes in term of possible involvement in cancers that will contribute to prioritization of protein targets for future drug development.


Author(s):  
Yu-Miao Zhang ◽  
Jun Wang ◽  
Tao Wu

In this study, the Agrobacterium infection medium, infection duration, detergent, and cell density were optimized. The sorghum-based infection medium (SbIM), 10-20 min infection time, addition of 0.01% Silwet L-77, and Agrobacterium optical density at 600 nm (OD600), improved the competence of onion epidermal cells to support Agrobacterium infection at >90% efficiency. Cyclin-dependent kinase D-2 (CDKD-2) and cytochrome c-type biogenesis protein (CYCH), protein-protein interactions were localized. The optimized procedure is a quick and efficient system for examining protein subcellular localization and protein-protein interaction.


2020 ◽  
Vol 27 (37) ◽  
pp. 6306-6355 ◽  
Author(s):  
Marian Vincenzi ◽  
Flavia Anna Mercurio ◽  
Marilisa Leone

Background:: Many pathways regarding healthy cells and/or linked to diseases onset and progression depend on large assemblies including multi-protein complexes. Protein-protein interactions may occur through a vast array of modules known as protein interaction domains (PIDs). Objective:: This review concerns with PIDs recognizing post-translationally modified peptide sequences and intends to provide the scientific community with state of art knowledge on their 3D structures, binding topologies and potential applications in the drug discovery field. Method:: Several databases, such as the Pfam (Protein family), the SMART (Simple Modular Architecture Research Tool) and the PDB (Protein Data Bank), were searched to look for different domain families and gain structural information on protein complexes in which particular PIDs are involved. Recent literature on PIDs and related drug discovery campaigns was retrieved through Pubmed and analyzed. Results and Conclusion:: PIDs are rather versatile as concerning their binding preferences. Many of them recognize specifically only determined amino acid stretches with post-translational modifications, a few others are able to interact with several post-translationally modified sequences or with unmodified ones. Many PIDs can be linked to different diseases including cancer. The tremendous amount of available structural data led to the structure-based design of several molecules targeting protein-protein interactions mediated by PIDs, including peptides, peptidomimetics and small compounds. More studies are needed to fully role out, among different families, PIDs that can be considered reliable therapeutic targets, however, attacking PIDs rather than catalytic domains of a particular protein may represent a route to obtain selective inhibitors.


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