Neurological and neuropsychiatric disorders are one of the leading causes of disability worldwide and affect the health of billions of people.Nitric oxide(NO),a free gas with multitudinous bioactivities,is mainly prod...Neurological and neuropsychiatric disorders are one of the leading causes of disability worldwide and affect the health of billions of people.Nitric oxide(NO),a free gas with multitudinous bioactivities,is mainly produced from the oxidation of L-arginine by neuronal nitric oxide synthase(nNOS)in the brain.Inhibiting nNOS benefits a variety of neurological and neuropsychiatric disorders,including stroke,depression and anxiety disorders,posttraumatic stress disorder,Parkinson’s disease,Alzheimer’s disease,chronic pain,and drug addiction.Due to critical roles of nNOS in learning and memory and synaptic plasticity,direct inhibition of nNOS may cause severe side effects.Importantly,interactions of several proteins,including post-synaptic density 95(PSD-95),carboxyterminal PDZ ligand of nNOS(CAPON)and serotonin transporter(SERT),with the PSD/Disc-large/ZO-1 homologous(PDZ)domain of nNOS have been demonstrated to influence the subcellular distribution and activity of the enzyme in the brain.Therefore,it will be a preferable means to interfere with nNOS-mediated proteinprotein interactions(PPIs),which do not lead to undesirable effects.Herein,we summarize the current literatures on nNOS-mediated PPIs involved in neurological and neuropsychiatric disorders,and the discovery of drugs targeting the PPIs,which is expected to provide potential targets for developing novel drugs and new strategy for the treatment of neurological and neuropsychiatric disorders.展开更多
Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes...Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes.Even,a viral infection is often initiated through virus-host protein interactions.Protein-protein interactions(PPIs)are the physical contacts between two or more proteins and they represent complex biological functions.Nowadays,PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins.Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets.In this review,we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies.Here,we present a short but comprehensive review on PPIs,including the experimental and computational methods of finding PPIs,the databases dedicated to virus-host PPIs,and the associated various applications in protein interaction networks of some lethal viruses with their hosts.展开更多
Systems biology has become an effective approach for understanding the molecular mechanisms underlying the development of lung cancer.In this study,sequences of 100 non-small cell lung cancer (NSCLC)-related proteins ...Systems biology has become an effective approach for understanding the molecular mechanisms underlying the development of lung cancer.In this study,sequences of 100 non-small cell lung cancer (NSCLC)-related proteins were downloaded from the National Center for Biotechnology Information (NCBI) databases.The Theory of Coevolution was then used to build a protein-protein interaction (PPI) network of NSCLC.Adopting the reverse thinking approach,we analyzed the NSCLC proteins one at a time.Fifteen key proteins were identified and categorized into a special protein family F(K),which included Cyclin D1 (CCND1),E-cadherin (CDH1),Cyclin-dependent kinase inhibitor 2A (CDKN2A),chemokine (C-X-C motif) ligand 12 (CXCL12),epidermal growth factor (EGF),epidermal growth factor receptor (EGFR),TNF receptor superfamily,member 6(FAS),FK506 binding protein 12-rapamycin associated protein 1 (FRAP1),O-6-methylguanine-DNA methyltransferase (MGMT),parkinson protein 2,E3 ubiquitin protein ligase (PARK2),phosphatase and tensin homolog (PTEN),calcium channel voltage-dependent alpha 2/delta subunit 2 (CACNA2D2),tubulin beta class I (TUBB),SWI/SNF-related,matrix-associated,actin-dependent regulator of chromatin,subfamily a,member 2 (SMARCA2),and wingless-type MMTV integration site family,member 7A (WNT7A).Seven key nodes of the sub-network were identified,which included PARK2,WNT7A,SMARCA2,FRAP1,CDKN2A,CCND1,and EGFR.The PPI predictions of EGFR-EGF,PARK2-FAS,PTEN-FAS,and CACNA2D2-CDH1 were confirmed experimentally by retrieving the Biological General Repository for Interaction Datasets (BioGRID) and PubMed databases.We proposed that the 7 proteins could serve as potential diagnostic molecular markers for NSCLC.In accordance with the developmental mode of lung cancer established by Sekine et al.,we assumed that the occurrence and development of lung cancer were linked not only to gene loss in the 3p region (WNT7A,3p25) and genetic mutations in the 9p region but also to similar events in the regions of 1p36.2 (FRAP1),6q25.2-q27 (PARK2),and 11q13 (CCND1).Lastly,the invasion or metastasis of lung cancer happened.展开更多
Cotton provides the most abundant natural fiber for the textile industry.The mature cotton fiber largely consists of secondary cell walls with the highest proportion of cellulose and a small amount of hemicellulose an...Cotton provides the most abundant natural fiber for the textile industry.The mature cotton fiber largely consists of secondary cell walls with the highest proportion of cellulose and a small amount of hemicellulose and lignin.To dissect the roles of hemicellulosic polysaccharides during fiber development,four IRREGULAR XYLEM 15(IRX15)genes,GhIRX15-1/-2/-3/-4,were functionally characterized in cotton.These genes encode DUF579 domain-containing proteins,which are homologs of AtIRX15 involved in xylan biosynthesis.The four GhIRX15 genes were predominantly expressed during fiber secondary wall thickening,and the encoded proteins were localized to the Golgi apparatus.Each GhIRX15 gene could restore the xylan deficient phenotype in the Arabidopsis irx15irx15l double mutant.Silencing of GhIRX15s in cotton resulted in shorter mature fibers with a thinner cell wall and reduced cellulose content as compared to the wild type.Intriguingly,GhIRX15-2 and GhIRX15-4 formed homodimers and heterodimers.In addition,the GhIRX15s showed physical interaction with glycosyltransferases GhGT43C,GhGT47A and GhGT47B,which are responsible for synthesis of the xylan backbone and reducing end sequence.Moreover,the GhIRX15s can form heterocomplexes with enzymes involved in xylan modification and side chain synthesis,such as GhGUX1/2,GhGXM1/2 and GhTBL1.These findings suggest that GhIRX15s participate in fiber xylan biosynthesis and modulate fiber development via forming large multiprotein complexes.展开更多
Clubroot disease is a severe threat to Brassica crops globally,particularly in western Canada.Genetic resistance,achieved through pyramiding clubroot resistance(CR)genes with different modes of action,is the most impo...Clubroot disease is a severe threat to Brassica crops globally,particularly in western Canada.Genetic resistance,achieved through pyramiding clubroot resistance(CR)genes with different modes of action,is the most important strategy for managing the disease.However,studies on the CR gene functions are quite limited.In this study,we have conducted investigations into the temporal,structural,and interacting features of a newly cloned CR gene,Rcr1,using CRISPR/Cas9 technology.For temporal functionality,we developed a novel CRISPR/Cas9-based binary vector,pHHIGR-Hsp18.2,to deliver Rcr1 into a susceptible canola line(DH12075)and observed that early expression of Rcr1 is critical for conferring resistance.For structural functionality,several independent mutations in specific domains of Rcr1 resulted in loss-offunction,highlighting their importance for CR phenotype.In the study of the interacting features of Rcr1,a cysteine protease gene and its homologous allele in canola were successfully disrupted via CRISPR/Cas9 as an interacting component with Rcr1 protein,resulting in the conversion from clubroot resistant to susceptible in plants carrying intact Rcr1.These results indicated an indispensable role of these two cysteine proteases in Rcr1-mediated resistance response.This study,the first of its kind,provides valuable insights into the functionality of Rcr1.Further,the new vector p HHIGR-Hsp18.2 demonstrated an inducible feature on the removal of add-on traits,which should be useful for functional genomics and other similar research in brassica crops.展开更多
Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understan...Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understanding the underlying disease-causing mechanisms and building solutions that have implications for a broad spectrum of patients. One potential solution is to develop personalized medicine approaches based on strategies that target the most prevalent cellular events that are perturbed in patients. Especially in patients with a known genetic mutation, it may be possible to understand how these mutations contribute to problems that lead to neurodegeneration. Protein–protein interaction analyses offer great advantages for revealing how proteins interact, which cellular events are primarily involved in these interactions, and how they become affected when key genes are mutated in patients. This line of investigation also suggests novel druggable targets for patients with different mutations. Here, we focus on alsin and spastin, two proteins that are identified as “causative” for amyotrophic lateral sclerosis and hereditary spastic paraplegia, respectively, when mutated. Our review analyzes the protein interactome for alsin and spastin, the canonical pathways that are primarily important for each protein domain, as well as compounds that are either Food and Drug Administration–approved or are in active clinical trials concerning the affected cellular pathways. This line of research begins to pave the way for personalized medicine approaches that are desperately needed for rare neurodegenerative diseases that are complex and heterogeneous.展开更多
Domain-based protein-protein interactions( PPIs) is a problem that has drawn the attentions of many researchers in recent years and it has been studied using lots of computational approaches from many different perspe...Domain-based protein-protein interactions( PPIs) is a problem that has drawn the attentions of many researchers in recent years and it has been studied using lots of computational approaches from many different perspectives. Existing domain-based methods to predict PPIs typically infer domain interactions from known interacting sets of proteins. However,these methods are costly and complex to implement. In this paper, a simple and effective prediction model is proposed. In this model,an improved multiinstance learning( MIL) algorithm( MilCaA) is designed that doesn't need to take the domain interactions into consideration to construct MIL bags. Then, the pseudo-amino acid composition( PseAAC) transformation method is used to encode the instances in a multi-instance bag and the principal components analysis( PCA) is also used to reduce the feature dimension. Finally, several traditional machine learning and MIL methods are used to verify the proposed model. Experimental results demonstrate that MilCaA performs better than state-of-the-art techniques including the traditional machine learning methods which are widely used in PPIs prediction.展开更多
Dynamic protein-protein interactions are essential for proper cell functioning.Homointeraction events—physical interactions between the same type of proteins—represent a pivotal subset of protein-protein interaction...Dynamic protein-protein interactions are essential for proper cell functioning.Homointeraction events—physical interactions between the same type of proteins—represent a pivotal subset of protein-protein interactions that are widely exploited in activating intracellular signaling pathways.Capacities of modulating protein-protein interactions with spatial and temporal resolution are greatly desired to decipher the dynamic nature of signal transduction mechanisms.The emerging optogenetic technology,based on genetically encoded light-sensitive proteins,provides promising opportunities to dissect the highly complex signaling networks with unmatched specificity and spatiotemporal precision.Here we review recent achievements in the development of optogenetic tools enabling light-inducible protein-protein homo-interactions and their applications in optical activation of signaling pathways.展开更多
Domain-domain interactions are important clues to inferring protein-protein interactions. Although about 8 000 domain-domain interactions are discovered so far,they are just the tip of the iceberg. Because domains are...Domain-domain interactions are important clues to inferring protein-protein interactions. Although about 8 000 domain-domain interactions are discovered so far,they are just the tip of the iceberg. Because domains are conservative and commonplace in proteins,domain-domain interactions are discovered based on pairs of domains which significantly co-exist in proteins. Meanwhile,it is realized that:( 1) domain-domain interactions may exist within the same proteins or across different proteins;( 2) only the domain-domain interactions across different proteins can mediate interactions between proteins;( 3) domains have biases to interact with other domains. And then,a novel method is put forward to construct protein-protein interaction network by using domain-domain interactions. The method is validated by experiments and compared with the state- of-art methods in the field. The experimental results suggest that the method is reasonable and effectiveness on constructing Protein-protein interactions network.展开更多
Detailed knowledge of interfacial region between interacting proteins is not only helpful in annotating function for proteins, but also very important for structure-based drug design and disease treatment. However, th...Detailed knowledge of interfacial region between interacting proteins is not only helpful in annotating function for proteins, but also very important for structure-based drug design and disease treatment. However, this is one of the most difficult tasks and current methods are constrained by some factors. In this study, we developed a new method to predict residue-residue contacts of two interacting protein domains by integrating information about evolutionary couplings andamino acid pairwise contact potentials, as well as domain-domain interaction interfaces. The experimental results showed that our proposed method outperformed the previous method with the same datasets. Moreover, the method promises an improvement in the source of template-based protein docking.展开更多
BACKGROUND Studies show that the antifibrotic mechanism of taurine may involve its inhibition of the activation and proliferation of hepatic stellate cells(HSCs). Since the molecular mechanism of taurine-mediated anti...BACKGROUND Studies show that the antifibrotic mechanism of taurine may involve its inhibition of the activation and proliferation of hepatic stellate cells(HSCs). Since the molecular mechanism of taurine-mediated antifibrotic activity has not been fully unveiled and is little studied, it is imperative to use "omics" methods to systematically investigate the molecular mechanism by which taurine inhibits liver fibrosis.AIM To establish a network including transcriptomic and protein-protein interaction data to elucidate the molecular mechanism of taurine-induced HSC apoptosis.METHODS We used microarrays, bioinformatics, protein-protein interaction(PPI) network,and sub-modules to investigate taurine-induced changes in gene expression in human HSCs(LX-2). Subsequently, all of the differentially expressed genes(DEGs) were subjected to gene ontology function and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. Furthermore, the interactions of DEGs were explored in a human PPI network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software.RESULTS A total of 635 DEGs were identified in taurine-treated HSCs when compared with the controls. Of these, 304 genes were statistically significantly up-regulated, and 331 down-regulated. Most of these DEGs were mainly located on the membrane and extracellular region, and are involved in the biological processes of signal transduction, cell proliferation, positive regulation of extracellular regulated protein kinases 1(ERK1) and ERK2 cascade, extrinsic apoptotic signaling pathway and so on. Fifteen significantly enriched pathways with DEGs were identified, including mitogen-activated protein kinase(MAPK) signaling pathway, peroxisome proliferators-activated receptor signaling pathway,estrogen signaling pathway, Th1 and Th2 cell differentiation, cyclic adenosine monophosphate signaling pathway and so on. By integrating the transcriptomics and human PPI data, nine critical genes, including MMP2, MMP9, MMP21,TIMP3, KLF10, CX3CR1, TGFB1, VEGFB, and EGF, were identified in the PPI network analysis.CONCLUSION Taurine promotes the apoptosis of HSCs via up-regulating TGFB1 and then activating the p38 MAPK-JNK-Caspase9/8/3 pathway. These findings enhance the understanding of the molecular mechanism of taurine-induced HSC apoptosis and provide references for liver disorder therapy.展开更多
Recent studies indicate that the process of liver regeneration involves multiple signaling pathways and a variety of genes,cytokines and growth factors. Protein-protein interactions(PPIs)play a role in nearly all even...Recent studies indicate that the process of liver regeneration involves multiple signaling pathways and a variety of genes,cytokines and growth factors. Protein-protein interactions(PPIs)play a role in nearly all events that take place within the cell and PPI maps should be helpful in further understanding the process of liver regeneration.In this review,we discuss recent progress in understanding the PPIs that occur during liver regeneration especially those in the transforming growth factorβsignaling pathways.We believe the use of large-scale PPI maps for integrating the information already known about the liver regeneration is a useful approach in understanding liver regeneration from the standpoint of systems biology.展开更多
Two DNA fragments encoding PDZ domain (21-110 residues) and BAR domain ( 150-360 residues) from PICK1 (1-416 residues) were amplified by PCR and then introduced into vectors, pET-32M and pMAL-e2X respectively to...Two DNA fragments encoding PDZ domain (21-110 residues) and BAR domain ( 150-360 residues) from PICK1 (1-416 residues) were amplified by PCR and then introduced into vectors, pET-32M and pMAL-e2X respectively to generate recombinant plasmids, pE-pdz and pM-bar. Having been separately transferred into the hosts E. coli BL21 and E. coli JM109, these two strains can express fusion proteins: His-tagged PDZ(PDZ domain) and maltose binding protein-BAR( MBP-BAR domain) respectively, as confirmed by both SDS-PAGE and Wostem blotting. The interaction between these two domains is dose-dependence, as identified by a pull-down test. Moreover, it has been shown from the ELISA analysis that the actual amount of PDZ bound to MBP-BAR-amylose beads reaches ( 16 ± 0. 5)%, as calculated by the molar ratio of PDZ to MBP-BAR. In addition, the interaction between BAR(bait) and PDZ(prey) in vivo was also examined with a yeast two-hybrid system.展开更多
Protein-protein interactions are of great significance for human to understand the functional mechanisms of proteins.With the rapid development of high-throughput genomic technologies,massive protein-protein interacti...Protein-protein interactions are of great significance for human to understand the functional mechanisms of proteins.With the rapid development of high-throughput genomic technologies,massive protein-protein interaction(PPI)data have been generated,making it very difficult to analyze them efficiently.To address this problem,this paper presents a distributed framework by reimplementing one of state-of-the-art algorithms,i.e.,CoFex,using MapReduce.To do so,an in-depth analysis of its limitations is conducted from the perspectives of efficiency and memory consumption when applying it for large-scale PPI data analysis and prediction.Respective solutions are then devised to overcome these limitations.In particular,we adopt a novel tree-based data structure to reduce the heavy memory consumption caused by the huge sequence information of proteins.After that,its procedure is modified by following the MapReduce framework to take the prediction task distributively.A series of extensive experiments have been conducted to evaluate the performance of our framework in terms of both efficiency and accuracy.Experimental results well demonstrate that the proposed framework can considerably improve its computational efficiency by more than two orders of magnitude while retaining the same high accuracy.展开更多
Smoking is the primary cause of lung cancer and is linked to 85% of lung cancer cases.However,how lung cancer develops in patients with smoking history remains unclear.Systems approaches that combine human protein-pro...Smoking is the primary cause of lung cancer and is linked to 85% of lung cancer cases.However,how lung cancer develops in patients with smoking history remains unclear.Systems approaches that combine human protein-protein interaction (PPI) networks and gene expression data are superior to traditional methods.We performed these systems to determine the role that smoking plays in lung cancer development and used the support vector machine (SVM) model to predict PPIs.By defining expression variance (EV),we found 520 dynamic proteins (EV>0.4) using data from the Human Protein Reference Database and Gene Expression Omnibus Database,and built 7 dynamic PPI subnetworks of lung cancer in patients with smoking history.We also determined the primary functions of each subnetwork:signal transduction,apoptosis,and cell migration and adhesion for subnetwork A;cell-sustained angiogenesis for subnetwork B;apoptosis for subnetwork C;and,finally,signal transduction and cell replication and proliferation for subnetworks D-G.The probability distribution of the degree of dynamic protein and static protein differed,clearly showing that the dynamic proteins were not the core proteins which widely connected with their neighbor proteins.There were high correlations among the dynamic proteins,suggesting that the dynamic proteins tend to form specific dynamic modules.We also found that the dynamic proteins were only correlated with the expression of selected proteins but not all neighbor proteins when cancer occurred.展开更多
AIM:To understand the interaction of human IQGAP1 and CDC42,especially the effects of phosphorylation and a cancer-associated mutation. METHODS:Recombinant CDC42 and a novel C-termi- nal fragment of IQGAP1 were expres...AIM:To understand the interaction of human IQGAP1 and CDC42,especially the effects of phosphorylation and a cancer-associated mutation. METHODS:Recombinant CDC42 and a novel C-termi- nal fragment of IQGAP1 were expressed in,and puri- fied from,Escherichia coli.Site directed mutagenesis was used to create coding sequences for three phos- phomimicking variants(S1441E,S1443D and S1441E/ S1443D)and to recapitulate a cancer-associated mu- tation(M1231I).These variant proteins were also ex- pressed and purified.Protein-protein crosslinking using 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide was used to investigate interactions between the C-terminal fragment and CDC42.These interactions were quanti- fied using surface plasmon resonance measurements.Molecular modelling was employed to make predictions about changes to the structure and flexibility of the protein which occur in the cancer-associated variant. RESULTS:The novel,C-terminal region of human IQGAP1 (residues 877-1558)is soluble following expression and purification.It is also capable of binding to CDC42,as judged by crosslinking experiments.Interaction appears to be strongest in the presence of added GTP.The three phosphomimicking mutants had different affini- ties for CDC42.S1441E had an approximately 200-fold reduction in affinity compared to wild type.This was caused largely by a dramatic reduction in the associa- tion rate constant.In contrast,both S1443D and the double variant S1441E/S1443D had similar affinities to the wild type.The cancer-associated variant,M1231I, also had a similar affinity to wild type.However,in the case of this variant,both the association and dis- sociation rate constants were reduced approximately 10-fold.Molecular modelling of the M1231I variant, based on the published crystal structure of part of the C-terminal region,revealed no gross structural changes compared to wild type(root mean square deviation of 0.564over 5556 equivalent atoms).However,pre- dictions of the flexibility of the polypeptide backbone suggested that some regions of the variant protein had greatly increased rigidity compared to wild type.One such region is a loop linking the proposed CDC42 bind- ing site with the helix containing the altered residue.It is suggested that this increase in rigidity is responsible for the observed changes in association and dissocia- tion rate constants. CONCLUSION:The consequences of introducing nega- tive charge at Ser-1441 or Ser-1443 in IQGAP1 are dif- ferent.The cancer-associated variant M1231I exerts its effects partly by rigidifying the protein.展开更多
Owing to the effect of classified models was different in Protein-Protein Interaction(PPI) extraction, which was made by different single kernel functions, and only using single kernel function hardly trained the opti...Owing to the effect of classified models was different in Protein-Protein Interaction(PPI) extraction, which was made by different single kernel functions, and only using single kernel function hardly trained the optimal classified model to extract PPI, this paper presents a strategy to find the optimal kernel function from a kernel function set. The strategy is that in the kernel function set which consists of different single kernel functions, endlessly finding the last two kernel functions on the performance in PPI extraction, using their optimal kernel function to replace them, until there is only one kernel function and it’s the final optimal kernel function. Finally, extracting PPI using the classified model made by this kernel function. This paper conducted the PPI extraction experiment on AIMed corpus, the experimental result shows that the optimal convex combination kernel function this paper presents can effectively improve the extraction performance than single kernel function, and it gets the best precision which reaches 65.0 among the similar PPI extraction systems.展开更多
Plant cellulose synthases (CesAs) are the key enzymes necessary for cellulose biosynthesis. In Arabidopsis, two distinct groups of three CesAs each are necessary for cellulose synthesis during primary and secondary ce...Plant cellulose synthases (CesAs) are the key enzymes necessary for cellulose biosynthesis. In Arabidopsis, two distinct groups of three CesAs each are necessary for cellulose synthesis during primary and secondary cell wall formation. It has also been suggested that such three CesAs interact with each other to form plasma-membrane bound rosette complexes that are functional during cellulose production. However, in vivo demonstration of such assemblies of three CesAs into rosettes has not been possible. We used yeast two-hybrid assays to demonstrate the possible interactions among several CesAs from Arabidopsis and aspen via their N-terminal zinc-binding domains (ZnBDs). While strong positive interactions were detected among ZnBDs from secondary wall associated CesAs of both Arabidopsis and aspen, the intergeneric interactions between Arabidopsis and aspen CesAs were weak. Moreover, in aspen, three primary wall associated CesA ZnBDs positively interacted with each other as well as with secondary CesAs. These results suggest that ZnBDs from either primary or secondary CesAs, and even from different plant species could interact but are perhaps insufficient for specificities of such interactions among CesAs. These observations suggest that some other more specific interacting regions might exist within CesAs. It is also possible that some hitherto unknown mechanism exists in plants for assembling the rosette complexes with different compositions of CesAs. Understanding how cellulose is synthesized will have a direct impact on utilization of lignocellulosic biomass for bioenergy production.展开更多
Duplication and divergence have been widely recognized as the two domi- nant evolutionary forces in shaping biological networks, e.g., gene regulatory networks and protein-protein interaction (PPI) networks. It has ...Duplication and divergence have been widely recognized as the two domi- nant evolutionary forces in shaping biological networks, e.g., gene regulatory networks and protein-protein interaction (PPI) networks. It has been shown that the network growth models constructed on the principle of duplication and divergence can recapture the topo- logical properties of real PPI networks. However, such network models only consider the evolution processes. How to select the model parameters with the real biological experi- mental data has not been presented. Therefore, based on the real PPI network statistical data, a yeast PPI network model is constructed. The simulation results indicate that the topological characteristics of the constructed network model are well consistent with those of real PPI networks, especially on sparseness, scale-free, small-world, hierarchical modularity, and disassortativity.展开更多
基金supported by grants from National Natural Science Foundation of China (82090042, 31530091,81870912)National Key Research and Development Program of China (2016YFC1306703)。
文摘Neurological and neuropsychiatric disorders are one of the leading causes of disability worldwide and affect the health of billions of people.Nitric oxide(NO),a free gas with multitudinous bioactivities,is mainly produced from the oxidation of L-arginine by neuronal nitric oxide synthase(nNOS)in the brain.Inhibiting nNOS benefits a variety of neurological and neuropsychiatric disorders,including stroke,depression and anxiety disorders,posttraumatic stress disorder,Parkinson’s disease,Alzheimer’s disease,chronic pain,and drug addiction.Due to critical roles of nNOS in learning and memory and synaptic plasticity,direct inhibition of nNOS may cause severe side effects.Importantly,interactions of several proteins,including post-synaptic density 95(PSD-95),carboxyterminal PDZ ligand of nNOS(CAPON)and serotonin transporter(SERT),with the PSD/Disc-large/ZO-1 homologous(PDZ)domain of nNOS have been demonstrated to influence the subcellular distribution and activity of the enzyme in the brain.Therefore,it will be a preferable means to interfere with nNOS-mediated proteinprotein interactions(PPIs),which do not lead to undesirable effects.Herein,we summarize the current literatures on nNOS-mediated PPIs involved in neurological and neuropsychiatric disorders,and the discovery of drugs targeting the PPIs,which is expected to provide potential targets for developing novel drugs and new strategy for the treatment of neurological and neuropsychiatric disorders.
基金National Natural Science Foundation of China,No.31971180 and No.11474013.
文摘Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes.Even,a viral infection is often initiated through virus-host protein interactions.Protein-protein interactions(PPIs)are the physical contacts between two or more proteins and they represent complex biological functions.Nowadays,PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins.Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets.In this review,we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies.Here,we present a short but comprehensive review on PPIs,including the experimental and computational methods of finding PPIs,the databases dedicated to virus-host PPIs,and the associated various applications in protein interaction networks of some lethal viruses with their hosts.
基金supported by National Natural Science Foundation of China (No.91130009)Science and Technology Planning Project of Guangdong Province of China(No.2003A3080503)
文摘Systems biology has become an effective approach for understanding the molecular mechanisms underlying the development of lung cancer.In this study,sequences of 100 non-small cell lung cancer (NSCLC)-related proteins were downloaded from the National Center for Biotechnology Information (NCBI) databases.The Theory of Coevolution was then used to build a protein-protein interaction (PPI) network of NSCLC.Adopting the reverse thinking approach,we analyzed the NSCLC proteins one at a time.Fifteen key proteins were identified and categorized into a special protein family F(K),which included Cyclin D1 (CCND1),E-cadherin (CDH1),Cyclin-dependent kinase inhibitor 2A (CDKN2A),chemokine (C-X-C motif) ligand 12 (CXCL12),epidermal growth factor (EGF),epidermal growth factor receptor (EGFR),TNF receptor superfamily,member 6(FAS),FK506 binding protein 12-rapamycin associated protein 1 (FRAP1),O-6-methylguanine-DNA methyltransferase (MGMT),parkinson protein 2,E3 ubiquitin protein ligase (PARK2),phosphatase and tensin homolog (PTEN),calcium channel voltage-dependent alpha 2/delta subunit 2 (CACNA2D2),tubulin beta class I (TUBB),SWI/SNF-related,matrix-associated,actin-dependent regulator of chromatin,subfamily a,member 2 (SMARCA2),and wingless-type MMTV integration site family,member 7A (WNT7A).Seven key nodes of the sub-network were identified,which included PARK2,WNT7A,SMARCA2,FRAP1,CDKN2A,CCND1,and EGFR.The PPI predictions of EGFR-EGF,PARK2-FAS,PTEN-FAS,and CACNA2D2-CDH1 were confirmed experimentally by retrieving the Biological General Repository for Interaction Datasets (BioGRID) and PubMed databases.We proposed that the 7 proteins could serve as potential diagnostic molecular markers for NSCLC.In accordance with the developmental mode of lung cancer established by Sekine et al.,we assumed that the occurrence and development of lung cancer were linked not only to gene loss in the 3p region (WNT7A,3p25) and genetic mutations in the 9p region but also to similar events in the regions of 1p36.2 (FRAP1),6q25.2-q27 (PARK2),and 11q13 (CCND1).Lastly,the invasion or metastasis of lung cancer happened.
基金supported by the National Natural Science Foundation of China(31970516 and 32372104)the Foundation of Hubei Hongshan Laboratory(2021hszd014).
文摘Cotton provides the most abundant natural fiber for the textile industry.The mature cotton fiber largely consists of secondary cell walls with the highest proportion of cellulose and a small amount of hemicellulose and lignin.To dissect the roles of hemicellulosic polysaccharides during fiber development,four IRREGULAR XYLEM 15(IRX15)genes,GhIRX15-1/-2/-3/-4,were functionally characterized in cotton.These genes encode DUF579 domain-containing proteins,which are homologs of AtIRX15 involved in xylan biosynthesis.The four GhIRX15 genes were predominantly expressed during fiber secondary wall thickening,and the encoded proteins were localized to the Golgi apparatus.Each GhIRX15 gene could restore the xylan deficient phenotype in the Arabidopsis irx15irx15l double mutant.Silencing of GhIRX15s in cotton resulted in shorter mature fibers with a thinner cell wall and reduced cellulose content as compared to the wild type.Intriguingly,GhIRX15-2 and GhIRX15-4 formed homodimers and heterodimers.In addition,the GhIRX15s showed physical interaction with glycosyltransferases GhGT43C,GhGT47A and GhGT47B,which are responsible for synthesis of the xylan backbone and reducing end sequence.Moreover,the GhIRX15s can form heterocomplexes with enzymes involved in xylan modification and side chain synthesis,such as GhGUX1/2,GhGXM1/2 and GhTBL1.These findings suggest that GhIRX15s participate in fiber xylan biosynthesis and modulate fiber development via forming large multiprotein complexes.
基金supported by the Genomics Initiative of Agriculture and Agri-Food Canada。
文摘Clubroot disease is a severe threat to Brassica crops globally,particularly in western Canada.Genetic resistance,achieved through pyramiding clubroot resistance(CR)genes with different modes of action,is the most important strategy for managing the disease.However,studies on the CR gene functions are quite limited.In this study,we have conducted investigations into the temporal,structural,and interacting features of a newly cloned CR gene,Rcr1,using CRISPR/Cas9 technology.For temporal functionality,we developed a novel CRISPR/Cas9-based binary vector,pHHIGR-Hsp18.2,to deliver Rcr1 into a susceptible canola line(DH12075)and observed that early expression of Rcr1 is critical for conferring resistance.For structural functionality,several independent mutations in specific domains of Rcr1 resulted in loss-offunction,highlighting their importance for CR phenotype.In the study of the interacting features of Rcr1,a cysteine protease gene and its homologous allele in canola were successfully disrupted via CRISPR/Cas9 as an interacting component with Rcr1 protein,resulting in the conversion from clubroot resistant to susceptible in plants carrying intact Rcr1.These results indicated an indispensable role of these two cysteine proteases in Rcr1-mediated resistance response.This study,the first of its kind,provides valuable insights into the functionality of Rcr1.Further,the new vector p HHIGR-Hsp18.2 demonstrated an inducible feature on the removal of add-on traits,which should be useful for functional genomics and other similar research in brassica crops.
基金funded by NIH-NIA R01AG061708 (to PHO)Patrick Grange Memorial Foundation (to PHO)+1 种基金A Long Swim (to PHO)CureSPG4 Foundation (to PHO)。
文摘Developing effective and long-term treatment strategies for rare and complex neurodegenerative diseases is challenging. One of the major roadblocks is the extensive heterogeneity among patients. This hinders understanding the underlying disease-causing mechanisms and building solutions that have implications for a broad spectrum of patients. One potential solution is to develop personalized medicine approaches based on strategies that target the most prevalent cellular events that are perturbed in patients. Especially in patients with a known genetic mutation, it may be possible to understand how these mutations contribute to problems that lead to neurodegeneration. Protein–protein interaction analyses offer great advantages for revealing how proteins interact, which cellular events are primarily involved in these interactions, and how they become affected when key genes are mutated in patients. This line of investigation also suggests novel druggable targets for patients with different mutations. Here, we focus on alsin and spastin, two proteins that are identified as “causative” for amyotrophic lateral sclerosis and hereditary spastic paraplegia, respectively, when mutated. Our review analyzes the protein interactome for alsin and spastin, the canonical pathways that are primarily important for each protein domain, as well as compounds that are either Food and Drug Administration–approved or are in active clinical trials concerning the affected cellular pathways. This line of research begins to pave the way for personalized medicine approaches that are desperately needed for rare neurodegenerative diseases that are complex and heterogeneous.
基金National Natural Science Foundations of China(Nos.61503116,61402007)Foundation for Young Talents in the Colleges of Anhui Province Committee,China(No.2013SQRL097ZD)+1 种基金Natural Science Foundation of Anhui Educational Committee,China(No.KJ2014A198)Natural Science Foundation of Anhui Province,China(No.1408085QF108)
文摘Domain-based protein-protein interactions( PPIs) is a problem that has drawn the attentions of many researchers in recent years and it has been studied using lots of computational approaches from many different perspectives. Existing domain-based methods to predict PPIs typically infer domain interactions from known interacting sets of proteins. However,these methods are costly and complex to implement. In this paper, a simple and effective prediction model is proposed. In this model,an improved multiinstance learning( MIL) algorithm( MilCaA) is designed that doesn't need to take the domain interactions into consideration to construct MIL bags. Then, the pseudo-amino acid composition( PseAAC) transformation method is used to encode the instances in a multi-instance bag and the principal components analysis( PCA) is also used to reduce the feature dimension. Finally, several traditional machine learning and MIL methods are used to verify the proposed model. Experimental results demonstrate that MilCaA performs better than state-of-the-art techniques including the traditional machine learning methods which are widely used in PPIs prediction.
基金supported by a Shun Hing Institute of Advanced Engineering Grant(No.4720247)a General Research Fund/Early Career Scheme(No.24201919)from the Research Grants Council of Hong Kong Special Administrative Region(to LD)。
文摘Dynamic protein-protein interactions are essential for proper cell functioning.Homointeraction events—physical interactions between the same type of proteins—represent a pivotal subset of protein-protein interactions that are widely exploited in activating intracellular signaling pathways.Capacities of modulating protein-protein interactions with spatial and temporal resolution are greatly desired to decipher the dynamic nature of signal transduction mechanisms.The emerging optogenetic technology,based on genetically encoded light-sensitive proteins,provides promising opportunities to dissect the highly complex signaling networks with unmatched specificity and spatiotemporal precision.Here we review recent achievements in the development of optogenetic tools enabling light-inducible protein-protein homo-interactions and their applications in optical activation of signaling pathways.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61271346,61571163,61532014,91335112 and 61402132)the Fundamental Research Funds for the Central Universities(Grant No.DB13AB02)
文摘Domain-domain interactions are important clues to inferring protein-protein interactions. Although about 8 000 domain-domain interactions are discovered so far,they are just the tip of the iceberg. Because domains are conservative and commonplace in proteins,domain-domain interactions are discovered based on pairs of domains which significantly co-exist in proteins. Meanwhile,it is realized that:( 1) domain-domain interactions may exist within the same proteins or across different proteins;( 2) only the domain-domain interactions across different proteins can mediate interactions between proteins;( 3) domains have biases to interact with other domains. And then,a novel method is put forward to construct protein-protein interaction network by using domain-domain interactions. The method is validated by experiments and compared with the state- of-art methods in the field. The experimental results suggest that the method is reasonable and effectiveness on constructing Protein-protein interactions network.
文摘Detailed knowledge of interfacial region between interacting proteins is not only helpful in annotating function for proteins, but also very important for structure-based drug design and disease treatment. However, this is one of the most difficult tasks and current methods are constrained by some factors. In this study, we developed a new method to predict residue-residue contacts of two interacting protein domains by integrating information about evolutionary couplings andamino acid pairwise contact potentials, as well as domain-domain interaction interfaces. The experimental results showed that our proposed method outperformed the previous method with the same datasets. Moreover, the method promises an improvement in the source of template-based protein docking.
基金the National Natural Science Foundation of China,No.81360595 and No.81860790Guangxi Natural Science Foundation Program,No.KJT13066+2 种基金the Bagui Scholars Foundation Program of Guangxithe Special-term Experts Foundation Program of Guangxithe Project of Guangxi Young Teacher Fundamental Ability Promotion,No.2017KY0298
文摘BACKGROUND Studies show that the antifibrotic mechanism of taurine may involve its inhibition of the activation and proliferation of hepatic stellate cells(HSCs). Since the molecular mechanism of taurine-mediated antifibrotic activity has not been fully unveiled and is little studied, it is imperative to use "omics" methods to systematically investigate the molecular mechanism by which taurine inhibits liver fibrosis.AIM To establish a network including transcriptomic and protein-protein interaction data to elucidate the molecular mechanism of taurine-induced HSC apoptosis.METHODS We used microarrays, bioinformatics, protein-protein interaction(PPI) network,and sub-modules to investigate taurine-induced changes in gene expression in human HSCs(LX-2). Subsequently, all of the differentially expressed genes(DEGs) were subjected to gene ontology function and Kyoto encyclopedia of genes and genomes pathway enrichment analysis. Furthermore, the interactions of DEGs were explored in a human PPI network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software.RESULTS A total of 635 DEGs were identified in taurine-treated HSCs when compared with the controls. Of these, 304 genes were statistically significantly up-regulated, and 331 down-regulated. Most of these DEGs were mainly located on the membrane and extracellular region, and are involved in the biological processes of signal transduction, cell proliferation, positive regulation of extracellular regulated protein kinases 1(ERK1) and ERK2 cascade, extrinsic apoptotic signaling pathway and so on. Fifteen significantly enriched pathways with DEGs were identified, including mitogen-activated protein kinase(MAPK) signaling pathway, peroxisome proliferators-activated receptor signaling pathway,estrogen signaling pathway, Th1 and Th2 cell differentiation, cyclic adenosine monophosphate signaling pathway and so on. By integrating the transcriptomics and human PPI data, nine critical genes, including MMP2, MMP9, MMP21,TIMP3, KLF10, CX3CR1, TGFB1, VEGFB, and EGF, were identified in the PPI network analysis.CONCLUSION Taurine promotes the apoptosis of HSCs via up-regulating TGFB1 and then activating the p38 MAPK-JNK-Caspase9/8/3 pathway. These findings enhance the understanding of the molecular mechanism of taurine-induced HSC apoptosis and provide references for liver disorder therapy.
基金Supported by Chinese Human Liver Proteome Project,No.2004BA711A19-08National 863 Project,No.2007AA02Z100
文摘Recent studies indicate that the process of liver regeneration involves multiple signaling pathways and a variety of genes,cytokines and growth factors. Protein-protein interactions(PPIs)play a role in nearly all events that take place within the cell and PPI maps should be helpful in further understanding the process of liver regeneration.In this review,we discuss recent progress in understanding the PPIs that occur during liver regeneration especially those in the transforming growth factorβsignaling pathways.We believe the use of large-scale PPI maps for integrating the information already known about the liver regeneration is a useful approach in understanding liver regeneration from the standpoint of systems biology.
基金the National Natural Science Foundation of China(No 30400065)
文摘Two DNA fragments encoding PDZ domain (21-110 residues) and BAR domain ( 150-360 residues) from PICK1 (1-416 residues) were amplified by PCR and then introduced into vectors, pET-32M and pMAL-e2X respectively to generate recombinant plasmids, pE-pdz and pM-bar. Having been separately transferred into the hosts E. coli BL21 and E. coli JM109, these two strains can express fusion proteins: His-tagged PDZ(PDZ domain) and maltose binding protein-BAR( MBP-BAR domain) respectively, as confirmed by both SDS-PAGE and Wostem blotting. The interaction between these two domains is dose-dependence, as identified by a pull-down test. Moreover, it has been shown from the ELISA analysis that the actual amount of PDZ bound to MBP-BAR-amylose beads reaches ( 16 ± 0. 5)%, as calculated by the molar ratio of PDZ to MBP-BAR. In addition, the interaction between BAR(bait) and PDZ(prey) in vivo was also examined with a yeast two-hybrid system.
基金This work was supported in part by the National Natural Science Foundation of China(61772493)the CAAI-Huawei MindSpore Open Fund(CAAIXSJLJJ-2020-004B)+4 种基金the Natural Science Foundation of Chongqing(China)(cstc2019jcyjjqX0013)Chongqing Research Program of Technology Innovation and Application(cstc2019jscx-fxydX0024,cstc2019jscx-fxydX0027,cstc2018jszx-cyzdX0041)Guangdong Province Universities and College Pearl River Scholar Funded Scheme(2019)the Pioneer Hundred Talents Program of Chinese Academy of Sciencesthe Deanship of Scientific Research(DSR)at King Abdulaziz University(G-21-135-38).
文摘Protein-protein interactions are of great significance for human to understand the functional mechanisms of proteins.With the rapid development of high-throughput genomic technologies,massive protein-protein interaction(PPI)data have been generated,making it very difficult to analyze them efficiently.To address this problem,this paper presents a distributed framework by reimplementing one of state-of-the-art algorithms,i.e.,CoFex,using MapReduce.To do so,an in-depth analysis of its limitations is conducted from the perspectives of efficiency and memory consumption when applying it for large-scale PPI data analysis and prediction.Respective solutions are then devised to overcome these limitations.In particular,we adopt a novel tree-based data structure to reduce the heavy memory consumption caused by the huge sequence information of proteins.After that,its procedure is modified by following the MapReduce framework to take the prediction task distributively.A series of extensive experiments have been conducted to evaluate the performance of our framework in terms of both efficiency and accuracy.Experimental results well demonstrate that the proposed framework can considerably improve its computational efficiency by more than two orders of magnitude while retaining the same high accuracy.
基金supported by grants from the National Natural Science Foundation of China (No. 91130009)Science and Technology Planning Project of Guangdong Province of China (No. 2003A3080503)
文摘Smoking is the primary cause of lung cancer and is linked to 85% of lung cancer cases.However,how lung cancer develops in patients with smoking history remains unclear.Systems approaches that combine human protein-protein interaction (PPI) networks and gene expression data are superior to traditional methods.We performed these systems to determine the role that smoking plays in lung cancer development and used the support vector machine (SVM) model to predict PPIs.By defining expression variance (EV),we found 520 dynamic proteins (EV>0.4) using data from the Human Protein Reference Database and Gene Expression Omnibus Database,and built 7 dynamic PPI subnetworks of lung cancer in patients with smoking history.We also determined the primary functions of each subnetwork:signal transduction,apoptosis,and cell migration and adhesion for subnetwork A;cell-sustained angiogenesis for subnetwork B;apoptosis for subnetwork C;and,finally,signal transduction and cell replication and proliferation for subnetworks D-G.The probability distribution of the degree of dynamic protein and static protein differed,clearly showing that the dynamic proteins were not the core proteins which widely connected with their neighbor proteins.There were high correlations among the dynamic proteins,suggesting that the dynamic proteins tend to form specific dynamic modules.We also found that the dynamic proteins were only correlated with the expression of selected proteins but not all neighbor proteins when cancer occurred.
基金Supported by The Biotechnology and Biological Sciences Research Council(BBSRC),United Kingdom,No.BB/D000394/1Action Cancer,Northern Ireland,United Kingdom,No.PG2 2005
文摘AIM:To understand the interaction of human IQGAP1 and CDC42,especially the effects of phosphorylation and a cancer-associated mutation. METHODS:Recombinant CDC42 and a novel C-termi- nal fragment of IQGAP1 were expressed in,and puri- fied from,Escherichia coli.Site directed mutagenesis was used to create coding sequences for three phos- phomimicking variants(S1441E,S1443D and S1441E/ S1443D)and to recapitulate a cancer-associated mu- tation(M1231I).These variant proteins were also ex- pressed and purified.Protein-protein crosslinking using 1-Ethyl-3-(3-dimethylaminopropyl)carbodiimide was used to investigate interactions between the C-terminal fragment and CDC42.These interactions were quanti- fied using surface plasmon resonance measurements.Molecular modelling was employed to make predictions about changes to the structure and flexibility of the protein which occur in the cancer-associated variant. RESULTS:The novel,C-terminal region of human IQGAP1 (residues 877-1558)is soluble following expression and purification.It is also capable of binding to CDC42,as judged by crosslinking experiments.Interaction appears to be strongest in the presence of added GTP.The three phosphomimicking mutants had different affini- ties for CDC42.S1441E had an approximately 200-fold reduction in affinity compared to wild type.This was caused largely by a dramatic reduction in the associa- tion rate constant.In contrast,both S1443D and the double variant S1441E/S1443D had similar affinities to the wild type.The cancer-associated variant,M1231I, also had a similar affinity to wild type.However,in the case of this variant,both the association and dis- sociation rate constants were reduced approximately 10-fold.Molecular modelling of the M1231I variant, based on the published crystal structure of part of the C-terminal region,revealed no gross structural changes compared to wild type(root mean square deviation of 0.564over 5556 equivalent atoms).However,pre- dictions of the flexibility of the polypeptide backbone suggested that some regions of the variant protein had greatly increased rigidity compared to wild type.One such region is a loop linking the proposed CDC42 bind- ing site with the helix containing the altered residue.It is suggested that this increase in rigidity is responsible for the observed changes in association and dissocia- tion rate constants. CONCLUSION:The consequences of introducing nega- tive charge at Ser-1441 or Ser-1443 in IQGAP1 are dif- ferent.The cancer-associated variant M1231I exerts its effects partly by rigidifying the protein.
文摘Owing to the effect of classified models was different in Protein-Protein Interaction(PPI) extraction, which was made by different single kernel functions, and only using single kernel function hardly trained the optimal classified model to extract PPI, this paper presents a strategy to find the optimal kernel function from a kernel function set. The strategy is that in the kernel function set which consists of different single kernel functions, endlessly finding the last two kernel functions on the performance in PPI extraction, using their optimal kernel function to replace them, until there is only one kernel function and it’s the final optimal kernel function. Finally, extracting PPI using the classified model made by this kernel function. This paper conducted the PPI extraction experiment on AIMed corpus, the experimental result shows that the optimal convex combination kernel function this paper presents can effectively improve the extraction performance than single kernel function, and it gets the best precision which reaches 65.0 among the similar PPI extraction systems.
文摘Plant cellulose synthases (CesAs) are the key enzymes necessary for cellulose biosynthesis. In Arabidopsis, two distinct groups of three CesAs each are necessary for cellulose synthesis during primary and secondary cell wall formation. It has also been suggested that such three CesAs interact with each other to form plasma-membrane bound rosette complexes that are functional during cellulose production. However, in vivo demonstration of such assemblies of three CesAs into rosettes has not been possible. We used yeast two-hybrid assays to demonstrate the possible interactions among several CesAs from Arabidopsis and aspen via their N-terminal zinc-binding domains (ZnBDs). While strong positive interactions were detected among ZnBDs from secondary wall associated CesAs of both Arabidopsis and aspen, the intergeneric interactions between Arabidopsis and aspen CesAs were weak. Moreover, in aspen, three primary wall associated CesA ZnBDs positively interacted with each other as well as with secondary CesAs. These results suggest that ZnBDs from either primary or secondary CesAs, and even from different plant species could interact but are perhaps insufficient for specificities of such interactions among CesAs. These observations suggest that some other more specific interacting regions might exist within CesAs. It is also possible that some hitherto unknown mechanism exists in plants for assembling the rosette complexes with different compositions of CesAs. Understanding how cellulose is synthesized will have a direct impact on utilization of lignocellulosic biomass for bioenergy production.
基金Project supported by the National Natural Science Foundation of China(No.11172158)
文摘Duplication and divergence have been widely recognized as the two domi- nant evolutionary forces in shaping biological networks, e.g., gene regulatory networks and protein-protein interaction (PPI) networks. It has been shown that the network growth models constructed on the principle of duplication and divergence can recapture the topo- logical properties of real PPI networks. However, such network models only consider the evolution processes. How to select the model parameters with the real biological experi- mental data has not been presented. Therefore, based on the real PPI network statistical data, a yeast PPI network model is constructed. The simulation results indicate that the topological characteristics of the constructed network model are well consistent with those of real PPI networks, especially on sparseness, scale-free, small-world, hierarchical modularity, and disassortativity.