Current Proteomics最新文献

{"title":"Curcumin Reverts the Protein Differential Expression in the Liver of the Diabetic Obese db/db mice","authors":"Oscar Gerardo Silva-Gaona, J. M. Guzmán-Flores, M. Hernández-Ortiz, K. Vargas-Ortiz, J. Ramírez-Emiliano, S. Encarnación-Guevara, V. Pérez-Vázquez","doi":"10.2174/1570164618666210114112642","DOIUrl":"https://doi.org/10.2174/1570164618666210114112642","url":null,"abstract":"\u0000\u0000 In type 2 diabetic mouse liver, hyperglycemia, and insulin modify gene expression. Curcumin is a\u0000powerful antioxidant and antidiabetic agent that regulates the gene expression of different signaling pathways through\u0000various transcription factors. Therefore, we hypothesized that curcumin modifies the protein expression profile in the liver\u0000of diabetic db/db mice.\u0000\u0000\u0000\u0000To determine the effects of curcumin on the liver protein profile of diabetic db/db mice.\u0000\u0000\u0000\u0000\u0000db/db and wild type (WT) male mice were allocated in four groups, and they were fed for eight weeks. Three WT\u0000and three diabetic db/db mice received a standard diet (SD; WT and db/db groups, respectively); three WT and three\u0000diabetic db/db mice received a SD supplemented with 0.75 % (w/w) curcumin (WT+C and db/db+C groups, respectively).\u0000Liver proteins were separated by 2D electrophoresis. Differential protein expression analysis was performed on\u0000ImageMaster 2D Platinum software, and selected proteins were identified by MALDI-TOF-MS and subjected to enrichment\u0000analysis using STRING and DAVID databases.\u0000\u0000\u0000\u0000Thirty-six proteins with differential expression due to the diabetic background and curcumin treatment were found;\u0000these proteins participate in the metabolism of amino acids, carbohydrates, and lipids. Interestingly, the altered expression of\u0000seven proteins was prevented in the liver of the diabetic mice that received curcumin.\u0000\u0000\u0000\u0000Among all differentially expressed proteins, curcumin reverted the altered expression of seven proteins. Thus,\u0000although it was observed that curcumin did not affect the biochemical parameters, it does modify the expression of some\u0000liver proteins in diabetic mice.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"40 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2021-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89033641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential Proteomic Identification and Bioinformatics Analysis of Femoral Neck in Elderly Female Patients with Hyperuricaemia","authors":"Yi-feng He, Guang-xin Zhang, Yuyang Huang, Qi Li, Cheng Luo","doi":"10.2174/1570164618999210112203816","DOIUrl":"https://doi.org/10.2174/1570164618999210112203816","url":null,"abstract":"\u0000\u0000Serum uric acid (UA) is positively correlated with bone mineral density (BMD). However, the mechanism by which serum UA affects BMD remains unclear.\u0000\u0000\u0000\u0000The aim was carried out to search for the functional proteins related to serum UA and femoral neck BMD to better understand the pathophysiological mechanism of osteoporosis.\u0000\u0000\u0000\u0000In this study, patients in the UA group (hyperuricaemia combined with femoral neck fracture) and the control group (normal uricaemia combined with femoral neck fracture) were selected according to the inclusion criteria. Total protein was extracted from the femoral neck of each patient. Fluorescence differential gel electrophoresis was used to separate the total proteins, and the differentially expressed protein spots were detected by image analysis. After enzyme digestion, peptide mass fingerprinting and database searches were performed to identify the differentially expressed proteins. DAVID software and Kyoto Encyclopedia of Genes and Genomes (KEGG) data were used for enrichment analysis of the screened differential proteins.\u0000\u0000\u0000\u0000After mass spectrometry and database searching, 66 differentially expressed protein spots were identified between the UA group and the control group. Most differentially expressed proteins functioned in cytoskeleton formation, energy metabolism, or signal transduction. They were mainly involved in 50 biological processes, including peroxisome proliferator-activated receptor (PPAR) signalling and fatty acid metabolism. PPARγ and PLIN1 were subject to Western blotting analysis detection; results were consistent with the Label-Free result.\u0000\u0000\u0000\u0000Based on an analysis of the biological information, these proteins may be associated with the incidence and progression of the femoral neck bone tissues of hyperuricaemia patients.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"132 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2021-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86816527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bioinformatics-based characterization of proteins related to SARS-CoV-2 using the Polarity Index Method® (PIM®) and Intrinsic Disorder Predisposition","authors":"C. Polanco, V. Uversky, Guy W. Dayhoff, A. Huberman, T. Buhse, M. Márquez, G. Vargas-Alarcón, J. Castañón-González, Leire Andrés, J. Dı́az-González, Karina González-Bañales","doi":"10.2174/1570164618666210106114606","DOIUrl":"https://doi.org/10.2174/1570164618666210106114606","url":null,"abstract":"\u0000\u0000The global outbreak of the 2019 novel Coronavirus Disease (COVID-19) caused by the infection with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which appeared in China at the end of\u00002019, signifies a major public health issue at the current time.\u0000\u0000\u0000\u0000 The objective of the present study is to characterize the physicochemical properties of the SARS-CoV-2 proteins at a residues level, and to generate a “bioinformatics fingerprint” in the form of a “PIM® profile” created for each\u0000sequence utilizing the Polarity Index Method® (PIM®), suitable for the identification of these proteins.\u0000\u0000\u0000\u0000Two different bioinformatics approaches were used to analyze sequence characteristics of these proteins at\u0000the residues level, an in-house bioinformatics system PIM®, and a set of the commonly used algorithms for the predic-tion of protein intrinsic disorder predisposition, such as PONDR® VLXT, PONDR® VL3, PONDR® VSL2, PONDR®\u0000FIT, IUPred_short and IUPred_long. The PIM® profile was generated for four SARS-CoV-2 structural proteins and\u0000compared with the corresponding profiles of the SARS-CoV-2 non-structural proteins, SARS-CoV-2 putative proteins,\u0000SARS-CoV proteins, MERS-CoV proteins, sets of bacterial, fungal, and viral proteins, cell-penetrating peptides, and a\u0000set of intrinsically disordered proteins. We also searched for the UniProt proteins with PIM® profiles similar to those of\u0000SARS-CoV-2 structural, non-structural, and putative proteins.\u0000\u0000\u0000\u0000We show that SARS-CoV-2 structural, non-structural, and putative proteins are characterized by a unique\u0000PIM® profile. A total of 1736 proteins were identified from the 562,253 “reviewed” proteins from the UniProt database,\u0000whose PIM® profile was similar to that of the SARS-CoV-2 structural, non-structural, and putative proteins.\u0000\u0000\u0000\u0000The PIM® profile represents an important characteristic that might be useful for the identification of proteins similar to SARS-CoV-2 proteins.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"7 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2021-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79974461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative Proteomic Analysis of Hydrogen Peroxide-induced Protein Expression in Streptococcus pneumoniae D39","authors":"Sungkyoung Lee, Myoung-Ro Lee, S. Bae, M. Kwak","doi":"10.2174/1570164618999210104223526","DOIUrl":"https://doi.org/10.2174/1570164618999210104223526","url":null,"abstract":"\u0000\u0000Streptococcus pneumoniae is a leading cause of human respiratory tract infection. Despite the lack\u0000of activities of antioxidative enzymes, including cytochromes, hemoproteins, and peroxidases/catalases, traits conferring the\u0000aerotolerant-anaerobic growth of this bacterium are conserved, with high efficacy of antioxidative actions, in an oxygen-rich\u0000environment.\u0000\u0000\u0000\u0000Through proteome analysis, this study’s intention was to evaluate differentially expressed proteins and/or gene\u0000products modeled in a highly virulent strain, S. pneumoniae D39, exogenously-treated with millimolar concentrations of\u0000H2O2.\u0000\u0000\u0000\u0000For two-dimensional gel electrophoresis (2-DE) analysis, following one dimensional isoelectric focusing with an\u0000immobilized pH gradient of pH 4-7, the most significantly mobilized proteins expressed were separated by SDS-PAGE in\u0000the second dimension. With a total of 431 protein spots detected, certain proteins were excised, in-gel trypsin digested, and\u0000analyzed by combination with MALDI-TOF and LC-ESI-MS/MS for mass spectrometric peptide mapping and protein\u0000identification. Utilizing mass spectrometry analysis of spots excised from 2-DE, the selected protein spots were identified\u0000with a variety of databases and MASCOT.\u0000\u0000\u0000\u0000With the aid of comparisons to proteome reference maps, the most differentially expressed 38 proteins, those with\u0000approximately 1.4-fold or more increase and/or decrease or with multiple isoforms exhibiting variable pI values, were\u0000induced by treatment of exogenous 2 mM H2O2. The identified proteins were seen to be involved in pneumococcal\u0000pathogenesis and primary metabolism, amongst others.\u0000\u0000\u0000\u0000This is the first study to convincingly document proteomic information associated with pathophysiological\u0000adaptation under the given oxidative conditions, and corresponding potential antioxidative mechanisms, in S. pneumoniae.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"125 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2021-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83830879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of Nitration Sites Based on FCBF Method and Stacking Ensemble Model","authors":"Min Liu, Lu Zhang, Xinyi Qin, Tao Huang, Ziwei Xu, Guangzhong Liu","doi":"10.2174/1570164618999210101222637","DOIUrl":"https://doi.org/10.2174/1570164618999210101222637","url":null,"abstract":"Nitration is one of the important Post-Translational Modification (PTM) occurring on the tyrosine residues of proteins. The occurrence of protein tyrosine nitration under disease conditions is inevitable and represents a shift from the signal transducing physiological actions of -NO to oxidative and potentially pathogenic pathways. Abnormal protein nitration modification can lead to serious human diseases, including neurodegenerative diseases, acute respiratory distress, organ transplant rejection and lung cancer. It is necessary and important to identify the nitration sites in protein sequences. Predicting that which tyrosine residues in the protein sequence are nitrated and which are not is of great significance for the study of nitration mechanism and related diseases. In this study, a prediction model of nitration sites based on the over-under sampling strategy and the FCBF method was proposed by stacking ensemble learning and fusing multiple features. Firstly, the protein sequence sample was encoded by 2701-dimensional fusion features (PseAAC, PSSM, AAIndex, CKSAAP, Disorder). Secondly, the ranked feature set was generated by the FCBF method according to the symmetric uncertainty metric. Thirdly, in the process of model training, use the over- and under- sampling technique was used to tackle the imbalanced dataset. Finally, the Incremental Feature Selection (IFS) method was adopted to extract an optimal classifier based on 10-fold cross-validation. Results show that the model has significant performance advantages in indicators such as MCC, Recall and F1-score, no matter in what way the comparison was conducted with other classifiers on the independent test set, or made by cross-validation with single-type feature or with fusion-features on the training set. By integrating the FCBF feature ranking methods, over- and under- sampling technique and a stacking model composed of multiple base classifiers, an effective prediction model for nitration PTM sites was build, which can achieve a better recall rate when the ratio of positive and negative samples is highly imbalanced.","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"29 1","pages":"1-11"},"PeriodicalIF":0.8,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76870640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning-based Virtual Screening Strategy Reveals Some Natural Compounds As Potential PAK4 Inhibitors In Triple Negative Breast Cancer","authors":"Opeyemi Iwaloye, O. Elekofehinti, Babatomiwa Kikiowo, E. Oluwarotimi, T. M. Fadipe","doi":"10.2174/1570164618999201223092209","DOIUrl":"https://doi.org/10.2174/1570164618999201223092209","url":null,"abstract":"\u0000\u0000 P-21 activating kinase 4 (PAK4) is implicated in poor prognosis of many cancers, especially in the\u0000progression of Triple Negative Breast Cancer (TNBC). The present study was aimed at designing some potential drug\u0000candidates as PAK4 inhibitors for breast cancer therapy.\u0000\u0000\u0000\u0000This study aimed to finding novel inhibitors of PAK4 from natural compounds using computational approach.\u0000\u0000\u0000\u0000\u0000An e-pharmacophore model was developed from docked PAK4-coligand complex and used to screen over a\u0000thousand natural compounds downloaded from BIOFACQUIM and NPASS databases to match a minimum of 5 sites for\u0000selected (ADDDHRR) hypothesis. The robustness of the virtual screening method was accessed by well-established\u0000methods including EF, ROC, BEDROC, AUAC, and the RIE. Compounds with fitness score greater than one were filtered\u0000by applying molecular docking (HTVS, SP, XP and Induced fit docking) and ADME prediction. Using Machine learningbased approach QSAR model was generated using Automated QSAR. The computed top model kpls_des_17 (R2= 0.8028,\u0000RMSE = 0.4884 and Q2 = 0.7661) was used to predict the pIC50 of the lead compounds. Internal and external validations\u0000were accessed to determine the predictive quality of the model. Finally the binding free energy calculation was computed.\u0000\u0000\u0000\u0000The robustness/predictive quality of the models were affirmed. The hits had better binding affinity than the\u0000reference drug and interacted with key amino acids for PAK4 inhibition. Overall, the present analysis yielded three potential\u0000inhibitors that are predicted to bind with PAK4 better than reference drug tamoxifen. The three potent novel inhibitors\u0000vitexin, emodin and ziganein recorded IFD score of -621.97 kcal/mol, -616.31 kcal/mol and -614.95 kcal/mol, respectively\u0000while showing moderation for ADME properties and inhibition constant.\u0000\u0000\u0000\u0000It is expected that the findings reported in this study may provide insight for designing effective and less toxic\u0000PAK4 inhibitors for triple negative breast cancer.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"33 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83944319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heteromerization As a Mechanism Modulating the Affinity of the ACE2 Receptor to the Receptor Binding Domain of SARS-CoV-2 Spike Protein","authors":"D. Guidolin, C. Tortorella, D. Anderlini, M. Marcoli, G. Maura","doi":"10.2174/1570164618999201216112244","DOIUrl":"https://doi.org/10.2174/1570164618999201216112244","url":null,"abstract":"\u0000\u0000 Angiotensin Converting Enzyme 2 (ACE2) is primarily involved in the maturation of angiotensin.\u0000It also represents the main receptor for the Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that caused\u0000the serious epidemics COVID-19. Available evidence indicates that at the cell membrane ACE2 can form heteromeric\u0000complexes with other membrane proteins, including the amino acid transporter B0AT1 and G Protein-Coupled Receptors\u0000(GPCR).\u0000\u0000\u0000\u0000It is well known that during the formation of quaternary structures, the configuration of each single monomer is\u0000re-shaped by its interaction pattern in the macromolecular complex. Therefore, it can be hypothesized that the affinity of\u0000ACE2 to the viral receptor binding domain (RBD), when in a heteromeric complex, may depend on the associated partner.\u0000\u0000\u0000\u0000By using established docking and molecular dynamics procedures, the reshaping of monomer was explored in\u0000silico to predict possible heterodimeric structures between ACE2 and GPCR, such as angiotensin and bradykinin receptors.\u0000The associated possible changes in binding affinity between the viral RBD and ACE2 when in the heteromeric complexes\u0000were also estimated.\u0000\u0000\u0000\u0000 The results provided support to the hypothesis that the heteromerization state of ACE2 may\u0000modulate its affinity to the viral RBD. If experimentally confirmed, ACE2 heteromerization may contribute to explain the\u0000observed differences in susceptibility to virus infection among individuals and to devise new therapeutic opportunities.\u0000\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"56 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2020-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86847460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic study of the mechanism of talin-C as an inhibitor of HIV infection","authors":"L. Yin, Yujiao Zhang, Huichun Shi, Ya-ru Xing, Hong Zhou Lu, Lijun Zhang","doi":"10.2174/1570164618999201214153239","DOIUrl":"https://doi.org/10.2174/1570164618999201214153239","url":null,"abstract":"\u0000\u0000 Talin-1 is involved in human immunodeficiency virus (HIV) invasion and synapse development.\u0000We found that talin-1 was cleaved into a 38 KDa fragment (talin-C) in the peripheral blood mononuclear cells (PBMCs) of\u0000HIV patients; however, the underlying mechanisms remain unknown.\u0000\u0000\u0000\u0000This study aimed to determine the relationship between talin-C and HIV infection and identify the mechanisms\u0000underlying the ability of this protein to influence HIV infection.\u0000\u0000\u0000\u0000 PBMCs were derived from HIV-infected patients enrolled in this study. N- and C-terminal peptides matching the\u0000potential sequence of talin-C were detected in PBMCs by multiple reaction monitoring (MRM) mass spectrometry. TZM-b1\u0000cells were infected with HIV-1 pseudotyped virus (HIVpp) for different durations to detect the talin-C product. Three stable\u0000cell lines overexpressing talin head (TLN1-H) or TLN1-C or with TLN1 knockdown (shTLN1) were created and infected by\u0000HIVpp. The HIV marker protein (P24) was then detected by enzyme-linked immunosorbent assay. Finally, an isobaric tag\u0000for relative and absolute quantification (iTRAQ)-based proteomic study was performed to detect the TLN1-C-regulated proteins with or without HIVpp infection in TZM-bl cells. The identified proteins were analyzed by R version 4.0.2, and\u0000STRING software (Version: 11.0) (https://string-db.org).\u0000\u0000\u0000\u0000N- and C-peptides of talin-C were detected to have higher expression in patients with lower HIV load. Talin-C was\u0000produced during HIVpp infection. TLN1-C significantly inhibited HIVpp infection in the TZM-b1 cells. Additionally, a proteomic study found that TLN1-C regulated the expression of 99 proteins in TZM-b1 cells without and with HIVpp infection,\u0000respectively. According to Gene Ontology (GO) annotation, proteins with cellular metabolic process and binding function\u0000were found to be enriched. Thirty four proteins have protein-protein interaction, including 19 down- and 15 up- regulated\u0000proteins, respectively.\u0000\u0000\u0000\u0000Talin-C was produced following HIV infection, and is inversely proportional to HIV load. A proteomic study\u0000indicated that TLN1-C might be involved in HIV infection through regulating metabolic processes.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"64 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80337495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic analysis of aqueous humor proteins associated with neovascular glaucoma secondary to proliferative diabetic retinopathy","authors":"Ying Wang, Shao-lin Xu, Junyi Li, Fujie Yuan, Yue Chen, Kelin Liu","doi":"10.2174/1570164618999201210224640","DOIUrl":"https://doi.org/10.2174/1570164618999201210224640","url":null,"abstract":"\u0000\u0000Extensive retinal ischemia caused by proliferative diabetic retinopathy (PDR) may develop into neo-vascular glaucoma (NVG). We searched for the proteins which might participate in neovascularization through the analysis of aqueous humor (AH) proteomics in patients with NVG secondary to PDR to increasing the understanding of the possible mechanism of neovascularization.\u0000\u0000\u0000\u0000We collected 12 samples (group A) of AH from patients with NVG secondary to PDR as the experimental group and 7 samples (group B) of AH from patients with primary acute angle-closure glaucoma (PAACG) & diabetes mellitus without diabetic retinopathy (NDR) as the control group. Differential quantitative proteome analysis of the aqueous humor samples was performed based on data-independent acquisition (DIA) method. The differentially expressed proteins were functionally annotated by Ingenuity Pathway Analysis (IPA). The important differentially expressed proteins were validated in another group (group A: 5 samples and group B: 5 samples) by parallel reaction monitor (PRM) approach .\u0000\u0000\u0000\u0000A total of 636 AH proteins were identified, and 82 proteins were differentially expressed between two groups. Functional annotation showed that the differentially expressed proteins were mainly associated with angiogenesis and cell migration. Signaling pathways analysis showed that the proteins up-regulated in group A were mainly related to Liver X re-ceptor/Retinoid X receptor (LXR/RXR) activation and acute reaction.\u0000\u0000\u0000\u0000This study presented a pilot work related to NVG secondary to PDR, which provided a better understanding of the mechanisms governing the pathophysiology of NVG.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"1 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90355930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Useful Tool for the Identification of DNA-binding Proteins Using Graph Convolutional Network","authors":"Dasheng Chen, Leyi Wei","doi":"10.2174/1570164618999201210225354","DOIUrl":"https://doi.org/10.2174/1570164618999201210225354","url":null,"abstract":"\u0000\u0000Both DNAs and proteins are important components of living organisms. DNA-binding proteins are\u0000a kind of helicase, which is a protein specifically responsible for binding to DNA single stranded regions. It plays a key role\u0000in the function of various biomolecules. Although there are some prediction methods for the DNA-binding proteins sequences,\u0000the use of graph neural networks in this research is still limited.\u0000\u0000\u0000\u0000In this article, using graph neural networks, we developed a novel predictor GCN-DBP for protein classification\u0000prediction.\u0000\u0000\u0000\u0000Each protein sequence is treated as a document in this study, and then document is segmented according to the\u0000concept of k-mer. This research aims to use document word relationships and word co-occurrence as a corpus to construct a\u0000text graph. Then, the predictor learns protein sequence information by two-layer graph convolutional networks.\u0000\u0000\u0000\u0000In order to compare the proposed method with other four existing methods, we have conducted more experiments.\u0000Finally, we tested GCN-DBP on the independent data set PDB2272. Its accuracy reached 64.17% and MCC reached\u000028.32%.\u0000\u0000\u0000\u0000The results show that the proposed method is superior to the other four methods and will be a useful tool for\u0000protein classification.\u0000","PeriodicalId":50601,"journal":{"name":"Current Proteomics","volume":"11 1","pages":""},"PeriodicalIF":0.8,"publicationDate":"2020-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89400245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}