Protein-protein Interaction Screening Research Articles

Identification of NET formation and the renoprotective effect of degraded NETs in lupus nephritis.

To explore molecular biomarkers associated with the pathophysiology and therapy of lupus nephritis (LN), we conducted a joint analysis of transcriptomic data from 40 peripheral blood mononuclear cells (PBMCs) (GSE81622) and 21 kidney samples (GSE112943) from the Gene Expression Omnibus database using bioinformatics. A total of 976 and 2,427 differentially expressed genes (DEGs) were identified in PBMCs and renal tissues. Seven and two functional modules closely related to LN were identified. Further enrichment analysis revealed that the neutrophil activation pathway was highly active in both PBMCs and the kidney. Subsequently, 16 core genes closely associated with LN were verified by protein-protein interaction screening and quantitative PCR. In vitro cell models and MRL/lpr mouse models confirmed that the abnormal expression of these core genes was closely linked to neutrophil extracellular traps (NETs) generated by neutrophil activation, while degradation of NETs led to downregulation of core gene expression, thereby improving pathological symptoms of LN. Therefore, identification of patients with systemic lupus erythematosus exhibiting abnormal expression patterns for these core genes may serve as a useful indicator for kidney involvement. In addition, targeting neutrophils to modulate their activation levels and inhibit aberrant expression of these genes represents a potential therapeutic strategy for treating LN. NEW & NOTEWORTHY The mechanisms by which immune cells cause kidney injury in lupus nephritis are poorly understood. We integrated and analyzed the transcriptomic features of PBMCs and renal tissues from the GEO database to identify key molecular markers associated with neutrophil activation. We confirmed that neutrophil extracellular traps (NETs) formed by neutrophil activation promoted the upregulation of key genes in cell and animal models. Targeted degradation of NETs significantly ameliorated kidney injury in MRL/lpr mice.

Network pharmacology integrated with molecular docking and molecular dynamics simulations to explore the mechanism of Tongxie Yaofang in the treatment of ulcerative colitis.

Tongxie Yaofang (TXYF), a classical traditional Chinese medicine, is commonly used in China to treat ulcerative colitis (UC). The aim of this study was to integrate network pharmacology with molecular docking and molecular dynamics simulations to explore the mechanism of Tongxie Yaofang in the treatment of UC. The traditional Chinese medicine systems pharmacology database was used to retrieve the relevant chemical compositions of the herbs contained in TXYF. The DisGeNET, GeneCards, Online Mendelian Inheritance in Man, and Therapeutic Target Database databases were used to retrieve UC-related targets. To construct protein-protein interaction networks and screen for key targets, gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses of the key targets of TXYF in the treatment of UC were performed using R 4.3.2 software. AutoDock Tools 1.5.7 was used for molecular docking. Molecular dynamics simulations of protein complexes and complexes of proteins with small-molecule ligands and eutectic ligands were carried out with Gromacs 2022 software. Network pharmacology analysis revealed that TXYF could act on UC through multiple targets and pathways. It may exert therapeutic effects mainly through the AGE/RAGE, TOLL, JAK/STAT, and Th17 signaling pathways. The possible targets of TXYF in the treatment of UC could be AKT1, BCL2, EGFR, HMOX1, HSP90AA1, and TGFβ1. Molecular docking analysis revealed that AKT1 had the highest binding energy (-10.55 kcal/mol). Molecular dynamics simulations revealed that the complexes formed by the AKT1 protein and the chemical compounds MOL001910 and MOL00035 had good stability and high binding strength. AKT1 may be the most critical target of TXYF in treating UC, and the key chemical components of TXYF in treating UC may include β-sitosterol (MOL000358) and 11alpha,12alpha-epoxy-3beta-23-dihydroxy-30-norolean-20-en-28,12beta-olide (MOL00 1910). This study revealed that TXYF may exert therapeutic effects on UC through multiple targets, multiple biological functions, and multiple signaling pathways. This study provides a new insight into the pharmacological mechanism of TXYF in treating UC.

The Mechanism of Action of the Active Ingredients of Coptidis rhizoma against Porcine Epidemic Diarrhea Was Investigated Using Network Pharmacology and Molecular Docking Technology.

The objective of this study was to elucidate the mechanism of action of the active components of Coptidis rhizoma against porcine epidemic diarrhea and to provide a theoretical foundation for further development of novel anti-PED therapeutic agents based on Coptidis rhizoma. The potential targets of Coptidis rhizoma against PEDV were identified through a comprehensive literature review and analysis using the TCMSP pharmacological database, SwissDrugDesign database, GeneCards database, and UniProt database. Subsequently, the STRING database and Cytoscape 3.7.1 software were employed to construct a protein-protein interaction (PPI) network and screen key targets. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were conducted on the identified targets. Molecular docking studies were performed using AutoDock 1.5.7 software to analyze the binding energy and modes of interaction between the active components of Coptidis rhizoma and the target proteins. The PyMOL 2.5.0a0 software was employed to visualize the docking results. Through comprehensive analysis, 74 specific targets of active components of Coptidis rhizoma against PEDV were identified. The core gene targets were screened, and an interaction network diagram was subsequently generated. Ultimately, 14 core targets were identified, with STAT3, ESR1, CASP3, and SRC exhibiting the most significant interactions. GO enrichment analysis revealed a total of 215 molecular items, including 48 biological function items, 139 biological process items, and 28 cellular component items. KEGG enrichment analysis identified 140 signaling pathways. Molecular docking analysis demonstrated that epiberberine and palmatine exhibited high binding affinity with STAT3 protein, worenine showed high binding affinity with ESR1 protein, obacunone exhibited high binding affinity with CASP3 protein, and epiberberine, obacunone, berberine, and berberruine exhibited high binding affinity with SRC protein. A network pharmacology and molecular docking technology approach was employed to screen six important active components of Coptidis rhizoma and four important potential targets against PEDV infection. The findings indicated that the active components of Coptidis rhizoma could serve as promising pharmaceutical agents for the prevention and control of PEDV, with significant potential for clinical application.

Structural basis of the Integrator complex assembly and association with transcription factors

Integrator is a multi-subunit protein complex responsible for premature transcription termination of coding and non-coding RNAs. This is achieved via two enzymatic activities, RNA endonuclease and protein phosphatase, acting on the promoter-proximally paused RNA polymerase Ⅱ (RNAPⅡ). Yet, it remains unclear how Integrator assembly and recruitment are regulated and what the functions of many of its core subunits are. Here, we report the structures of two human Integrator sub-complexes: INTS10/13/14/15 and INTS5/8/10/15, and an integrative model of the fully assembled Integrator bound to the RNAPⅡ paused elongating complex (PEC). An in silico protein-protein interaction screen of over 1,500 human transcription factors (TFs) identified ZNF655 as a direct interacting partner of INTS13 within the fully assembled Integrator. We propose a model wherein INTS13 acts as a platform for the recruitment of TFs that could modulate the stability of the Integrator's association at specific loci and regulate transcription attenuation of the target genes.

Epitope Mapping of Japanese Encephalitis Virus Neutralizing Antibodies by Native Mass Spectrometry and Hydrogen/Deuterium Exchange.

Japanese encephalitis virus (JEV) remains a global public health concern due to its epidemiological distribution and the existence of multiple strains. Neutralizing antibodies against this infection have shown efficacy in in vivo studies. Thus, elucidation of the epitopes of neutralizing antibodies can aid in the design and development of effective vaccines against different strains of JEV. Here, we describe a combination of native mass spectrometry (native-MS) and hydrogen/deuterium exchange mass spectrometry (HDX-MS) to complete screening of eight mouse monoclonal antibodies (MAbs) against JEV E-DIII to identify epitope regions. Native-MS was used as a first pass to identify the antibodies that formed a complex with the target antigen, and it revealed that seven of the eight monoclonal antibodies underwent binding. Native mass spectra of a MAb (JEV-27) known to be non-binding showed broad native-MS peaks and poor signal, suggesting the protein is a mixture or that there are impurities in the sample. We followed native-MS with HDX-MS to locate the binding sites for several of the complex-forming antibodies. This combination of two mass spectrometry-based approaches should be generally applicable and particularly suitable for screening of antigen-antibody and other protein-protein interactions when other traditional approaches give unclear results or are difficult, unavailable, or need to be validated.

Identification of two hub genes and miRNA‑mRNA interactions in chronic obstructive pulmonary disease (COPD) plasma

Background We aimed to identify hub genes in chronic obstructive pulmonary disease (COPD) plasma through the exploration of a putative miRNA–mRNA regulatory network. Methods Three datasets (GSE24709, GSE102915, GSE136390) were utilized to discern differentially expressed miRNAs (DEMs) between COPD and normal plasma. miRNET was employed to predict the potential targets of DEMs. Subsequent GO and KEGG analyses were conducted using DAVID. For the construction of the protein-protein interaction (PPI) network and screening of hub genes, STRING and Cytoscape were employed. The expression validation was assessed through GSE56768. Results The results revealed 395 genes targeted by up-regulated DEMs and 234 genes targeted by down-regulated DEMs. The target genes exhibited significant enrichment in the PI3K-Akt signaling pathway and the p53 signaling pathway. Through the validation of hub genes’ expression, we proposed two potential miRNA-mRNA interactions: miR-126-5p/miR-495-3p/miR-193b-3p - YWHAZ and miR-937-5p/miR-183-5p/miR-34c-5p/miR-98-5p/miR-525-3p/miR-215-5p - ACTB. Conclusions In conclusion, our study posits potential miRNA-mRNA interactions in COPD by analyzing datasets from public databases, contributing valuable insights into the understanding of COPD pathogenesis and potential therapeutic avenues.

Comprehensive analysis of the potential pathogenesis of COVID-19 infection and liver cancer.

A growing number of clinical examples suggest that coronavirus disease 2019 (COVID-19) appears to have an impact on the treatment of patients with liver cancer compared to the normal population, and the prevalence of COVID-19 is significantly higher in patients with liver cancer. However, this mechanism of action has not been clarified. To investigate the disease relevance of COVID-19 in liver cancer. Gene sets for COVID-19 (GSE180226) and liver cancer (GSE87630) were obtained from the Gene Expression Omnibus database. After identifying the common differentially expressed genes (DEGs) of COVID-19 and liver cancer, functional enrichment analysis, protein-protein interaction network construction and screening and analysis of hub genes were performed. Subsequently, the validation of the differential expression of hub genes in the disease was performed and the regulatory network of transcription factors and hub genes was constructed. Of 518 common DEGs were obtained by screening for functional analysis. Fifteen hub genes including aurora kinase B, cyclin B2, cell division cycle 20, cell division cycle associated 8, nucleolar and spindle associated protein 1, etc., were further identified from DEGs using the "cytoHubba" plugin. Functional enrichment analysis of hub genes showed that these hub genes are associated with P53 signalling pathway regulation, cell cycle and other functions, and they may serve as potential molecular markers for COVID-19 and liver cancer. Finally, we selected 10 of the hub genes for in vitro expression validation in liver cancer cells. Our study reveals a common pathogenesis of liver cancer and COVID-19. These common pathways and key genes may provide new ideas for further mechanistic studies.

A Comprehensive Study to Investigate the Tumor-Suppressive Role of Radix Bupleuri on Gastric Cancer with Network Pharmacology and Molecular Docking.

Gastric cancer (GC) is a common fatal malignancy. The aim of this study was to explore and validate the tumor-suppressive role and mechanism of Radix Bupleuri in GC. The active constituents of Radix Bupleuri were screened using TCMSP database. SwissTargetPrediction database was used to predict potential target genes of the compounds. GeneCards, TTD, DisGeNET, OMIM, and PharmGKB databases were used to search for GC-related targets. STRING database and Cytoscape 3.10 software were used for protein-protein interaction network construction and screening of core targets. DAVID database was used for GO and KEGG analyses. Core targets were validated using molecular docking. Cell proliferation and apoptosis were detected using CCK-8 and flow cytometry after GC cells were treated with isorhamnetin. The mRNA and protein expression levels of genes were detected using qRT PCR and Western blot. The metastasis potential of GC cells was evaluated in a nude mouse model. A total of 371 potential targets were retrieved by searching the intersection of Radix Bupleuri and GC targets. Petunidin, 3',4',5',3,5,6,7-Heptamethoxyflavone, quercetin, kaempferol, and isorhamnetin were identified as the main bioactive compounds in Radix Bupleuri. SRC, HSP90AA1, AKT1, and EGFR, were core targets through which Radix Bupleuri suppressed GC. The tumor-suppressive effect of Radix Bupleuri on GC was mediated by multiple pathways, including PI3K-AKT, cAMP, and TNF signaling. The key compounds of Radix Bupleuri had good binding affinity with the core target. Isorhamnetin, a key component of Radix Bupleuri, could inhibit proliferation and metastasis, and induces apoptosis of GC cells. In addition, isorhamnetin could also reduce the mRNA expression of core targets, and the activation of PI3K/AKT pathway. This study identified potential targets and pathways of Radix Bupleuri against GC through network pharmacology and molecular docking, providing new insights into the pharmacological mechanisms of Radix Bupleuri in GC treatment.

Accelerating protein-protein interaction screens with reduced AlphaFold-Multimer sampling.

Discovering new protein-protein interactions (PPIs) across entire proteomes offers vast potential for understanding novel protein functions and elucidate system properties within or between an organism. While recent advances in computational structural biology, particularly AlphaFold-Multimer, have facilitated this task, scaling for large-scale screenings remains a challenge, requiring significant computational resources. We evaluated the impact of reducing the number of models generated by AlphaFold-Multimer from five to one on the method's ability to distinguish true PPIs from false ones. Our evaluation was conducted on a dataset containing both intra- and inter-species PPIs, which included proteins from bacterial and eukaryotic sources. We demonstrate that reducing the sampling does not compromise the accuracy of the method, offering a faster, efficient, and environmentally friendly solution for PPI predictions. The code used in this article is available at https://github.com/MIDIfactory/AlphaFastPPi. Note that the same can be achieved using the latest version of AlphaPulldown available at https://github.com/KosinskiLab/AlphaPulldown.

Comprehensive split TEV based protein-protein interaction screening reveals TAOK2 as a key modulator of Hippo signalling to limit growth.

The conserved Hippo signalling pathway plays a crucial role in tumour formation by limiting tissue growth and proliferation. At the core of this pathway are tumour suppressor kinases STK3/4 and LATS1/2, which limit the activity of the oncogene YAP1, the primary downstream effector. Here, we employed a split TEV-based protein-protein interaction screen to assess the physical interactions among 28 key Hippo pathway components and potential upstream modulators. This screen led us to the discovery of TAOK2 as pivotal modulator of Hippo signalling, as it binds to the pathway's core kinases, STK3/4 and LATS1/2, and leads to their phosphorylation. Specifically, our findings revealed that TAOK2 binds to and phosphorylates LATS1, resulting in the reduction of YAP1 phosphorylation and subsequent transcription of oncogenes. Consequently, this decrease led to a decrease in cell proliferation and migration. Interestingly, a correlation was observed between reduced TAOK2 expression and decreased patient survival time in certain types of human cancers, including lung and kidney cancer as well as glioma. Moreover, in cellular models corresponding to these cancer types the downregulation of TAOK2 by CRISPR inhibition led to reduced phosphorylation of LATS1 and increased proliferation rates, supporting TAOK2's role as tumour suppressor gene. By contrast, overexpression of TAOK2 in these cellular models lead to increased phospho-LATS1 but reduced cell proliferation. As TAOK2 is a druggable kinase, targeting TAOK2 could serve as an attractive pharmacological approach to modulate cell growth and potentially offer strategies for combating cancer.

Identification and Preliminary Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Hashimoto's Thyroiditis by Comprehensive Analysis.

Hashimoto's thyroiditis (HT) is an autoimmune disruption manifested by immune cell infiltration in thyroid tissue and the production of antibodies against thyroid-specific antigens, such as the thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TGAb). TPOAb and TGAb are commonly used in clinical tests; however, handy indicators of the diagnosis and progression of HT are still scarce. Extracellular proteins are glycosylated and are likely to enter body fluids and become readily available and detectable biomarkers. Our research aimed to discover extracellular biomarkers and potential treatment targets associated with HT through integrated bioinformatics analysis and clinical sample validations. A total of 19 extracellular protein-differentially expressed genes (EP-DEGs) were screened by the GSE138198 dataset from the Gene Expression Omnibus (GEO) database and protein annotation databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE, and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Six key EP-DEGs (CCL5, GZMK, CXCL9, CXCL10, CXCL11, and CXCL13) were further validated in the GSE29315 dataset and the diagnostic curves were evaluated, which all showed high diagnostic accuracy (AUC > 0.95) for HT. Immune profiling revealed the correlation of the six key EP-DEGs and the pivotal immune cells in HT, such as CD8+ T cells, dendritic cells, and Th2 cells. Further, we also confirmed the key EP-DEGs in clinical thyroid samples. Our study may provide bioinformatics and clinical evidence for revealing the pathogenesis of HT and improving the potential diagnosis biomarkers and therapeutic strategies for HT.

Review of molecular biological research on the treatment of membranous nephropathy with Tripterygium glycosides based on TCM theory.

To explore the mechanism of Tripterygium wilfordii polyglycoside (TWP) in the treatment of membranous nephropathy (MN) by network pharmacology. TCMSP and DrugBank databases were used to screen the main targets of the main active components of Tripterygium glycosides, and OMIM and Gene Cards databases were used to search the gene targets of MN. UniProt database was used to normalize all the targets to get the intersection targets of TGs and MNs. Synergistic genes were uploaded to the STRING platform to construct a protein-protein interaction network and screen related core targets. Gene Ontology and Kyoto Genome Encyclopedia analyses of core targets were performed using the DAVID database. AutoDockTools software was used to verify the molecular docking between the active components of TGs and the synergistic genes. We identified 126 potential targets for the active component of Tripterygium glycosides, 584 MN-associated disease targets, and 28 co-acting genes. It mainly involves AGE-RAGE signaling pathway, lipid and atherosclerosis, IL-17 signaling pathway, fluid shear stress and atherosclerosis, NF-kappa B signaling pathway and other pathways and biological pathways in diabetic complications. The active component of that Tripterygium glycosides and the active site of the synergistic core target can the bond energy is less than -5kJ/mol. Tripterygium glycosides can regulate the release of inflammatory factors to treat MN through multiple active components, multiple disease targets, multiple biological pathways and multiple pathways, which provides a basis for broadening the clinical use of traditional Chinese medicine in the treatment of MN.

Exploration of Simiao-Yongan Decoction on knee osteoarthritis based on network pharmacology and molecular docking.

Use network pharmacology combined with molecular docking to study the effects of Simiao-Yongan Decoction (SMYAD) intervenes in Knee Osteoarthritis (KOA) related targets and signaling pathways, and explores the molecular mechanism of SMYAD in treating KOA. The active ingredients and targets of SMYAD, which concluded 4 traditional Chinese medicines, were screened in TCMSP, and the related gene targets of KOA were screened in the disease databases GeneCards, MalaCards, DisGeNET, and Comparative Toxicogenomics Database, and their intersection data were obtained after integration. And used Cytoscape 3.9.1, the software topologies the network diagram of "compound-drug-active ingredient-target protein-disease." Obtains the protein-protein interaction network diagram through STRING, and enriches and analyzes the obtained core targets. Carry out molecular docking matching verification on the main active ingredients and key targets of the drug. 106 active ingredients and 175 targets were screened from SMYAD to intervene in KOA, 36 core targets were obtained through protein-protein interaction screening, and 10 key targets played an important role. The enrichment results showed that the biological process of gene ontology mainly involved positive regulation of gene expression, negative regulation of apoptosis process, and positive regulation of apoptosis process. KEGG signaling pathway mainly involves AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, hypoxia-inducible factor-1 signaling pathway, IL-17 signaling pathway. The pathway of Reactome mainly involves interleukin-4 and interleukin-13 signaling, cytokine signaling in immune system, immune system, apoptosis. Molecular docking showed that the mainly effective components of SMYAD can fully combine with TNF, IL1B, IL6, and CASP3. The results show that the main active ingredients and potential mechanism of action of SMYAD in the treatment of KOA have the characteristics of multiple targets and multiple pathways, which provides ideas and basis for further in-depth exploration of its specific mechanism.

Bioinformatical analysis of the key differentially expressed genes for screening potential biomarkers in Wilms tumor

Wilms tumor (WT) is the most common pediatric renal malignant tumor in the world. Overall, the prognosis of Wilms tumor is very good. However, the prognosis of patients with anaplastic tumor histology or disease relapse is still poor, and their recurrence rate, metastasis rate and mortality are significantly increased compared with others. Currently, the combination of histopathological examination and molecular biology is essential to predict prognosis and guide the treatment. However, the molecular mechanism has not been well studied. Genetic profiling may be helpful in some way. Hence, we sought to identify novel promising biomarkers of WT by integrating bioinformatics analysis and to identify genes associated with the pathogenesis of WT. In the presented study, the NCBI Gene Expression Omnibus was used to download two datasets of gene expression profiles related to WT patients for the purpose of detecting overlapped differentially expressed genes (DEGs). The DEGs were then uploaded to DAVID database for enrichment analysis. In addition, the functional interactions between proteins were evaluated by simulating the protein–protein interaction (PPI) network of DEGs. The impact of selected hub genes on survival in WT patients was analyzed by using the online tool R2: Genomics Analysis and Visualization Platform. The correlation between gene expression and the degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA. Top 12 genes were identified for further study after constructing a PPI network and screening hub gene modules. Kinesin family member 2C (KIF2C) was identified as the most significant gene predicting the overall survival of WT patients. The expression of KIF2C in WT was further verified by quantitative real-time polymerase chain reaction and immunohistochemistry. Furthermore, we found that KIF2C was significantly correlated with immune cell infiltration in WT. Our present study demonstrated that altered expression of KIF2C may be involved in WT and serve as a potential prognostic biomarker for WT patients.

Differential Gene Expression Profiles and Pathways Highlight the Role of Osteoimmunology in Neurofibromatosis Type 1-Related Dystrophic Scoliosis With Osteopenia.

Microarray approach and integrated gene network analysis. To explore the differential genetic expression profile, Gene Ontology terms, and Kyoto Encyclopedia of Genes and Genomes pathways in human trabecular bone (HTB)-derived cells of dystrophic scoliosis secondary to neurofibromatosis type 1 (DS-NF1) and compare these to normal controls. The pathogenesis of DS-NF1 and the accompanying generalized osteopenia remain unclear. We hypothesized that HTBs may play a significant role in the etiology and pathogenesis of DS-NF1. Microarray analysis was used to identify differentially expressed genes of HTBs from patients with DS-NF1 compared with those from healthy individuals. Functional and pathway enrichment analysis were implemented through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway database. Then, the "search tool for the retrieval of interacting genes/proteins" database, Cytoscape, and "Molecular Complex Detection" were applied to construct the protein-protein interaction (PPI) network and screen hub genes. Pathway enrichment analysis was further performed for hub genes and gene clusters identified through module analysis. Six potential crucial genes were selected for validation by reverse transcription polymerase chain reaction. Bioinformatic analysis revealed that there are 401 previously unrecognized differentially expressed genes (238 up and 163 downregulated genes) in HTBs from patients with DS-NF1, and they were mainly enriched in terms of immune response, type-I interferon (IFN) signaling, TNF signaling pathway and etinoic acid inducible gene I-like receptor signaling pathway. Five hub genes, including signal transducer and activator of transcription 1, 2'-5'-oligoadenylate synthetase-like, IFN induced with helicase C domain 1, IFN regulatory factor 7, and MX dynamin-like GTPase 1 were identified through PPI network, which were mainly enriched in terms of Jak-STAT and etinoic acid inducible gene I-like receptor signaling pathway. An independently dysregulated protein cluster containing CCL2, CXCL1, CXCL3, CX3CL1, TLR1 , and CXCL12 was also identified through the PPI network. This indicated that the upper abnormally expressed genes may play essential roles in DS-NF1 pathogenesis and accompanied osteopenia. Six key genes were identified in the progression of DS-NF1-related osteopenia. Immune response might play a key role in the progression of osteopenia, whereas a CXCL12 -mediated osteogenic effect might play a protective role.

In silico protein interaction screening uncovers DONSON's role in replication initiation.

CDC45-MCM2-7-GINS (CMG) helicase assembly is the central event in eukaryotic replication initiation. In yeast, a multi-subunit "pre-loading complex" (pre-LC) accompanies GINS to chromatin-bound MCM2-7, leading to CMG formation. Here, we report that DONSON, a metazoan protein mutated in microcephalic primordial dwarfism, is required for CMG assembly in vertebrates. Using AlphaFold to screen for protein-protein interactions followed by experimental validation, we show that DONSON scaffolds a vertebrate pre-LC containing GINS, TOPBP1, and DNA pol ε. Our evidence suggests that DONSON docks the pre-LC onto MCM2-7, delivering GINS to its binding site in CMG. A patient-derived DONSON mutation compromises CMG assembly and recapitulates microcephalic dwarfism in mice. These results unify our understanding of eukaryotic replication initiation, implicate defective CMG assembly in microcephalic dwarfism, and illustrate how in silico protein-protein interaction screening accelerates mechanistic discovery.

Discovering Dynamic Plant Enzyme Complexes in Yeast for Kratom Alkaloid Pathway Identification.

Discovering natural product biosynthetic pathways of medicinal plants is challenging and laborious. Capturing the coregulation patterns of pathway enzymes, particularly transcriptomic regulation, has proven an effective method to accelerate pathway identification. In this study, we developed a yeast-based screening method to capture the protein-protein interactions (PPI) between plant enzymes, which is another useful pattern to complement the prevalent approach. Combining this method with plant multiomics analysis, we discovered four enzyme complexes and their organized pathways from kratom, an alkaloid-producing plant. The four pathway branches involved six enzymes, including a strictosidine synthase, a strictosidine β-D-glucosidase (MsSGD), and four medium-chain dehydrogenase/reductases (MsMDRs). PPI screening selected six MsMDRs interacting with MsSGD from 20 candidates predicted by multiomics analysis. Four of the six MsMDRs were then characterized as functional, indicating the high selectivity of the PPI screening method. This study highlights the opportunity of leveraging post-translational regulation features to discover novel plant natural product biosynthetic pathways.

Discovering Dynamic Plant Enzyme Complexes in Yeast for Kratom Alkaloid Pathway Identification**

AbstractDiscovering natural product biosynthetic pathways of medicinal plants is challenging and laborious. Capturing the coregulation patterns of pathway enzymes, particularly transcriptomic regulation, has proven an effective method to accelerate pathway identification. In this study, we developed a yeast‐based screening method to capture the protein‐protein interactions (PPI) between plant enzymes, which is another useful pattern to complement the prevalent approach. Combining this method with plant multiomics analysis, we discovered four enzyme complexes and their organized pathways from kratom, an alkaloid‐producing plant. The four pathway branches involved six enzymes, including a strictosidine synthase, a strictosidine β‐D‐glucosidase (MsSGD), and four medium‐chain dehydrogenase/reductases (MsMDRs). PPI screening selected six MsMDRs interacting with MsSGD from 20 candidates predicted by multiomics analysis. Four of the six MsMDRs were then characterized as functional, indicating the high selectivity of the PPI screening method. This study highlights the opportunity of leveraging post‐translational regulation features to discover novel plant natural product biosynthetic pathways.

Analysis of Communal Molecular Mechanism Between Chronic Obstructive Pulmonary Disease and Osteoporosis.

Chronic obstructive pulmonary disease (COPD) patients with osteoporosis (OP) usually experience more frequent exacerbations, worse quality of life, and heavier economic burden, however, few studies have investigated common molecular mechanisms of COPD and OP. To explore the relationship between COPD and OP through bioinformatics analysis. The miRNA microarray data of COPD and OP were retrieved from the Gene Expression Database (GEO), and the differentially expressed microRNAs (DEmiRNAs) were screened and the intersection was obtained. The Targetscan, miRDB, and miRWalk databases were used to predict the target genes of DEmiRNA, and the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the R package clusterProfiler, the STRING database was used to analyze the target protein-protein interaction network (PPI) and screens to determine the core modules and core genes. Two DEmiRNAs (miR-23a-5p, miR-194-3p) have been found in COPD and OP, which have predicted 76 and 114 target genes, respectively. GO functional annotations of miR-23a-5p were significantly enriched in CD40 signaling pathway, ubiquitin-conjugating enzyme activity, etc; KEGG pathways of miR-23a-5p were significantly enriched in ubiquitin-mediated proteolysis, folate biosynthesis, and regulation of actin cytoskeleton. GO function annotations of miR-194-3p were significantly enriched in T cell activation regulation, ubiquitin protein ligase activity, and DNA transcription factor binding; KEGG pathways of miR-194-3p were significantly enriched in cell adhesion molecules, intercellular tight junctions, and lysosomal pathway. PPI analysis found target coding proteins formed complex regulatory networks. Ten core genes (TP53, SRC, PXN, CHD4, SYK, TNRC6B, PML, KAT5, BRD1 and IGF2) were picked out among them, then we used the MCODE plugin found three core subnetworks. Two identical DEmiRNAs (miR-23a-5p, miR-194-3p) exist in the peripheral blood of COPD and OP patients, which are important biomarkers for COPD patients with OP and may represent novel targets for diagnosis and treatment of COPD patients with OP.

Investigate the genetic mechanisms of diabetic kidney disease complicated with inflammatory bowel disease through data mining and bioinformatic analysis.

Patients with diabetic kidney disease (DKD) often have gastrointestinal dysfunction such as inflammatory bowel disease (IBD). This study aims to investigate the genetic mechanism leading to IBD in DKD patients through data mining and bioinformatics analysis. The disease-related genes of DKD and IBD were searched from the five databases of OMIM, GeneCards, PharmGkb, TTD, and DrugBank, and the intersection part of the two diseases were taken to obtain the risk genes of DKD complicated with IBD. A protein-protein interaction (PPI) network analysis was performed on risk genes, and three topological parameters of degree, betweenness, and closeness of nodes in the network were used to identify key risk genes. Finally, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed on the risk genes to explore the related mechanism of DKD merging IBD. This study identified 495 risk genes for DKD complicated with IBD. After constructing a protein-protein interaction network and screening for three times, six key risk genes were obtained, including matrix metalloproteinase 2 (MMP2), hepatocyte growth factor (HGF), fibroblast growth factor 2 (FGF2), interleukin (IL)-18, IL-13, and C-C motif chemokine ligand 5 (CCL5). Based on GO enrichment analysis, we found that DKD genes complicated with IBD were associated with 3,646 biological processes such as inflammatory response regulation, 121 cellular components such as cytoplasmic vesicles, and 276 molecular functions such as G-protein-coupled receptor binding. Based on KEGG enrichment analysis, we found that the risk genes of DKD combined with IBD were associated with 181 pathways, such as the PI3K-Akt signaling pathway, advanced glycation end product-receptor for AGE (AGE-RAGE) signaling pathway and hypoxia-inducible factor (HIF)-1 signaling pathway. There is a genetic mechanism for the complication of IBD in patients with CKD. Oxidative stress, chronic inflammatory response, and immune dysfunction were possible mechanisms for DKD complicated with IBD.