基于全局角度网络策略的复杂疾病风险通路识别

复杂疾病的发生发展与机体内生物学通路的功能紊乱有密切联系,从高通量数据出发,利用计算机辅助方法来研究疾病与通路间的关系具有重要意义.本文提出了一个新的基于网络的全局性通路识别方法.该方法利用蛋白质互作信息和通路的基因集组成信息构建复杂的蛋白质-通路网.然后,基于表达谱数据,通过随机游走算法从全局层面优化疾病风险通路.最终,通过扰动方式识别统计学显著的风险通路.将该网络运用于结肠直肠癌风险通路识别,识别出15个与结肠直肠癌发生与发展过程显著相关的通路.通过与其他通路识别方法(超几何检验,SPIA)相比较,该方法能够更有效识别出疾病相关的风险通路.     

结构域相互作用数据库的产生、发展与应用

结构域是进化上的保守序列单元,是蛋白质的结构和功能的标准组件．典型的两个蛋白质间的相互作用涉及特殊结构域间的结合,而且识别相互作用结构域对于在结构域水平上彻底理解蛋白质的功能与进化、构建蛋白质相互作用网络、分析生物学通路等十分重要．目前,依赖于对实验数据的进一步挖掘和对各种不同输入数据的计算预测,已识别出了一些相互作用/功能连锁结构域对,并由此构建了内容丰富、日益更新的结构域相互作用数据库．综述了产生结构域相互作用的8种计算预测方法．介绍了5个结构域相互作用公共数据库3DID、iPfam、InterDom、DIMA和DOMINE的有关信息和最新动态．实例概述了结构域相互作用在蛋白质相互作用计算预测、可信度评估,蛋白质结构域注释,以及在生物学通路分析中的应用．     

结合亲和质谱与生物信息学分析构建TP53BP1的蛋白相互作用网络

蛋白质与蛋白质相互作用(PPIs)是两个或更多蛋白质分子之间通过静电作用、范德华力等建立的高度特异性的物理接触.细胞内的各种蛋白分子通过PPIs进行彼此之间的功能调节、信号通路的交互作用等,从而实现各种生物进程,而异常的PPIs也将导致疾病的发生、发展,其中就包括肿瘤.因此围绕某些和疾病密切相关的关键蛋白构建其相互作用生物网络(interactome)将有助于更好地分析该关键蛋白在疾病中的作用和可能的分子机制.本研究针对抑癌基因p53结合蛋白1(TP53BP1),利用亲和质谱分析鉴定了15个潜在的TP53BP1相互作用蛋白.同时,结合PPI数据库检索构建了与TP53BP1相互作用的蛋白质网络,并对该网络中的蛋白进行了功能富集分析、通路分析,结果显示,TP53BP1相互作用蛋白主要富集在细胞周期、同源重组、错配修复等重要通路,该研究为深入解析TP53BP1的生物学功能及其在肿瘤中的作用奠定了基础.     

基于蛋白质互作网络挖掘自闭症谱系障碍的功能模块与核心基因

自闭症谱系障碍(autism spectrum disorder, ASD)是一种具有高遗传性、临床异质性和生物复杂性的神经行为障碍类疾病。为挖掘ASD发生发展过程中的功能模块与核心基因,本文从自闭症谱系障碍疾病数据库获取ASD相关基因;利用STRING数据库构建ASD相关基因的蛋白质互作网络;通过MCODE算法对蛋白质互作网络进行模块分析并筛选核心基因;最后对各功能模块进行KEGG通路分析,根据富集到的通路类别评估功能模块之间的相互作用。结果显示, 3个疾病基因数据库筛选出182个共有基因,构建的蛋白质互作网络包含171个节点和1 041条边,其中NRXN1、GRIN2B、GRIN2A、DLG4、NLGN3、MECP2、CNTNAP2、BDNF、NLGN4X、FMR1等23个基因具有较高的连通度(degree)。从蛋白质互作网络中分析得到5个功能模块,包括68个核心基因。KEGG富集分析发现功能模块参与多个生物学通路,包括细胞黏附分子、钙离子通路、神经活性的配体-受体相互作用、多巴胺能神经突触等。分析结果提示,挖掘的ASD功能模块和核心基因大多集中在神经元活动、信号分子和信号传导等,且各模块相互作用共同影响ASD的发生发展。     

蛋白质组学在感染性疾病研究中的应用

蛋白质组学在人类疾病研究中的应用 ,主要是通过比较分析正常组织细胞与异常组织细胞、同一疾病在不同的发展时期细胞内整体蛋白质的表达差异 ,对差异表达的蛋白质进行鉴定、定量、表征 ,寻找与疾病相关的新的标志物 ,为人类疾病研究提供新的手段和依据 ,蛋白质组学在感染性疾病研究中的应用就是其中的一个方面。1 .蛋白质组学在感染性疾病研究中的应用蛋白质组学在人类感染性疾病研究中的应用主要是对引起感染性疾病的致病源的整体蛋白质进行研究 ,同时结合血清学 ,对其进行分析 ,鉴定出与疾病相关的新的标志物 ,为感染性疾病的诊断、治疗…     

中国人类蛋白质组计划全面启动

<正>中国人类蛋白质组计划(CNHPP)近日全面启动实施,主要目标是以我国重大疾病的防治需求为牵引,发展蛋白质组研究相关设备及关键技术,绘制人类蛋白质组生理和病理精细图谱、构建人类蛋白质组"百科全书",全景式揭示生命奥秘,为提高重大疾病防诊治水平提供有效手段,为我国生物医药产业发展提供原动力。     

人类蛋白质结构互作网络——结构域对网络拓扑与蛋白质功能的影响

高通量的蛋白质互作数据与结构域互作数据的出现,使得在蛋白质组学领域内研究人类蛋白质结构互作网络,进一步揭示蛋白质结构与功能间的潜在关系成为可能.蛋白质上广泛分布的结构域被认为是蛋白质结构、功能以及进化的基本功能单元.然而,结合蛋白质的结构信息(例如蛋白质结构域数目、长度和覆盖率等)来研究这些表象后的内部机制仍然面临着挑战.将蛋白质分为单结构域蛋白质与多结构域蛋白质,并进一步结合蛋白质互作信息与结构域互作信息构建了人类蛋白质结构互作网络;通过与人类蛋白质互作网络进行比较,研究了人类蛋白质结构互作网络的特殊结构特征;对于单结构域蛋白质与多结构域蛋白质,分别进行了功能富集分析、功能离散度分析以及功能一致性分析等.结果发现,将结构域互作信息综合考虑进来后,人类蛋白质结构互作网络可以提供更多的单纯的蛋白质互作网络无法提供的细节信息,揭示蛋白质互作网络的复杂性.     

基于二元网络异步重启随机游走算法预测肺癌风险致病基因

肺癌致病基因的发现及预测有助于认识肺癌的发生机理、诊断与防治,是人类基因组研究的重要目标。应用现有二元网络重启随机游走算法预测致病基因时,一般先在疾病表型网络、蛋白质作用网络及疾病-蛋白质二分图网络内随机游走一步,然后进行网络间跳转,这种策略不仅搜索效率较低,还可能遗漏蛋白质(或疾病)网络中的局部拓扑信息。鉴于此,作者提出一种二元网络异步重启游走(asynchronously random walk with restart,ARWRH)算法,构建疾病表型-蛋白质异构网络,深层次挖掘潜在肺癌风险致病基因。ARWRH算法首先在疾病表型网络、蛋白质作用网络及疾病表型-蛋白质二分图网络内随机游走不同步数,然后进行网络间跳转,迭代形成稳态概率向量,从而获得候选致病基因。仿真实验表明,ARWRH算法可有效预测肺癌潜在风险致病基因,多数预测结果获得了文献证据支持。     

进食障碍数据库的建立及其在识别与进食障碍相关的扩展脂肪细胞因子信号通路中的应用

进食障碍是一种生理和心理上的进食失调,影响了世界范围近1%的女性人群.尽管已广泛开展了针对此疾病遗传角度的流行病学研究,但其分子机制仍需进一步阐释.近期,高通量技术被广泛应用于发现复杂疾病中可能的致病基因以及其潜在的致病机理.本研究首次收集了大量文献报道的与进食障碍有关的基因,建立了进食障碍相关的数据库,以期对进食障碍的分子机制进行初步了解.EDdb数据库包括了从发表的文献中收集的有实验验证的与进食障碍有关的59个基因,并将这些基因作为核心数据集.根据核心数据集,利用蛋白-蛋白相互作用信息、基因共享的染色体条带信息及疾病相关信息扩展出其他4个数据集,这4个数据集包括了2824个潜在的进食障碍相关基因,这些基因分布在601个基因组区间.根据人的蛋白-蛋白相互作用数据,重建了可能的与进食障碍相关的分子相互作用网络.进一步,利用代谢通路富集性分析方法,识别出EDdb中的3个基因ADIPO,TNF和NR3C1可以将KEGG中的＂脂肪细胞因子信号通路＂和BioCarta中的＂内脏脂肪沉着和代谢综合征＂2个通路结合在一起,得到一个与进食障碍相关的扩展的脂肪细胞因子信号通路.在这个扩展通路中共包括43个基因,其中39个基因与进食障碍有关.本研究构建了第一个进食障碍相关的基因数据库,其中的各种数据信息将有助于对进食障碍的研究,揭示其中的基因和疾病关系.通过初步的统计分析,发现进食障碍引起的体重失调和肥胖可能与本研究发现的扩展通路的调节障碍有关,并且这个扩展通路也可能与不健康的生活习惯引起的体重失调等复杂疾病有关.     

用于GWAS结果后续研究的PBA方法简介

自提出全基因组关联研究(genome-wide association study,GWAS)设想以来,在人类复杂疾病和水稻农艺性状关联研究方面,GWAS已得到广泛运用。但作为一种典型的单标记研究方法,GWAS不能检测小效应的遗传变异,而稀有变异间的联合效应往往与表型密切相关,因此,需对GWAS结果进行深入的数据挖掘。基于通路的分析方法(pathway-based analysis,PBA)就是利用基因功能、生物代谢通路等相关信息建立的对GWAS结果进行二次挖掘的方法。该方法能从GWAS结果挖掘出与性状、疾病相关联的通路及具有相同功能的基因集等数据,从而获得更多的遗传信息。现对PBA的出现、计算方法和相关软件进行简要综述,以期为人们进行通路分析提供参考。     

TRMP: a database of therapeutically relevant multiple pathways

SUMMARY: Disease processes often involve crosstalks between proteins in different pathways. Different proteins have been used as separate therapeutic targets for the same disease. Synergetic targeting of multiple targets has been explored in combination therapy of a number of diseases. Potential harmful interactions of multiple targeting have also been closely studied. To facilitate mechanistic study of drug actions and a more comprehensive understanding the relationship between different targets of the same disease, it is useful to develop a database of known therapeutically relevant multiple pathways (TRMPs). Information about non-target proteins and natural small molecules involved in these pathways also provides useful hint for searching new therapeutic targets and facilitate the understanding of how therapeutic targets interact with other molecules in performing specific tasks. The TRMPs database is designed to provide information about such multiple pathways along with related therapeutic targets, corresponding drugs/ligands, targeted disease conditions, constituent individual pathways, structural and functional information about each protein in the pathways. Cross links to other databases are also introduced to facilitate the access of information about individual pathways and proteins. AVAILABILITY: This database can be accessed at http://bidd.nus.edu.sg/group/trmp/trmp.asp and it currently contains 11 entries of multiple pathways, 97 entries of individual pathways, 120 targets covering 72 disease conditions together with 120 sets of drugs directed at each of these targets. Each entry can be retrieved through multiple methods including multiple pathway name, individual pathway name and disease name. SUPPLEMENTARY INFORMATION: http://bidd.nus.edu.sg/group/trmp/sm.pdf     

The mechanics of base excision repair, and its relationship to aging and disease

Base excision repair (BER) is the major pathway responsible for averting the mutagenic and cytotoxic effects of spontaneous hydrolytic, oxidative, and non-enzymatic alkylation DNA damage. In particular, this pathway recognizes and repairs base modifications, such as uracil and 8-hydroxyguanine, as well as abasic sites and DNA single-strand breaks. In this review, we outline the basic mechanics of the BER process, and describe the potential association of this pathway with aging and age-related disease, namely cancer and neurodegeneration.     

Les isoformes neuronales des tyrosines kinases Src,Fyn et Lck : rôle particulier de la p56lckN dans la survie neuronale

The two main tyrosine kinases (TK) in the brain are p60Src and p59Fyn, expressed as specific isoforms (p60SrcNI, p60SrcNI + NII and p59fynB). They play a pivotal role in some major processes such as neuronal growth and myelinisation. Another member of this TK family was then reported in brain, the p56lck. Its name Lck (lymphocyte cell kinase) indicates its cellular specificity observed initially, so its presence in the brain was intriguing. But no further studies were performed to understand its role in brain until recent clinical studies on Alzheimer patients’ brains. One study reveals a decreased p56lck level in the brains of these patients while another study shows an association between one peculiar SNP (single nucleotide polymorphism) of the lck gene and some cases of the disease. These new data prompt us to reinvestigate the original biochemical data and to confront them with the present knowledge. This analysis suggests some hypothesis concerning both the Lck protein expressed in the brain (rather an isoform than the lymphocyte protein itself) and its role (to maintain the neuronal survival presumably by protecting them from inflammation, the main pathway that leads to neuron degeneracy).     

Nϵ-lysine acetylation in the lumen of the endoplasmic reticulum: A way to regulate autophagy and maintain protein homeostasis in the secretory pathway

The N?-lysine acetylation of cargo proteins in the lumen of the endoplasmic reticulum (ER) requires a membrane transporter (SLC33A1) and 2 acetyltransferases (NAT8B and NAT8). The ER acetylation machinery regulates the homeostatic balance between quality control/efficiency of the secretory pathway and autophagy-mediated disposal of toxic protein aggregates. We recently reported that the autophagy pathway that acts downstream of the ER acetylation machinery specifically targets protein aggregates that form within the secretory pathway. Genetic and biochemical manipulation of ER acetylation in a mouse model of Alzheimer disease is able to restore normal proteostasis and rescue the disease phenotype. Here we summarize these findings and offer an overview of the ER-acetylation machinery.     

Evolutionary couplings of amino acid residues reveal structure and function of bacterial signaling proteins

The genomic era along with major advances in high‐throughput sequencing technology has led to a rapid expansion of the genomic and consequently the protein sequence space. Bacterial extracytoplasmic function sigma factors have emerged as an important group of signaling proteins in bacteria involved in many regulatory decisions, most notably the adaptation to cell envelope stress. Their wide prevalence and amplification among bacterial genomes has led to sub‐group classification and the realization of diverse signaling mechanisms. Mathematical frameworks have been developed to utilize extensive protein sequence alignments to extract co‐evolutionary signals of interaction. This has proven useful in a number of different biological fields, including de novo structure prediction, protein–protein partner identification and the elucidation of alternative protein conformations for signal proteins, to name a few. The mathematical tools, commonly referred to under the name ‘Direct Coupling Analysis’ have now been applied to deduce molecular mechanisms of activation for sub‐groups of extracytoplasmic sigma factors adding to previous successes on bacterial two‐component signaling proteins. The amplification of signal transduction protein genes in bacterial genomes made them the first to be amenable to this approach but the sequences are available now to aid the molecular microbiologist, no matter their protein pathway of interest.     

The KCTD family of proteins: structure,function, disease relevance

The family of potassium channel tetramerizationdomain (KCTD) proteins consists of 26 members with mostly unknown functions. The name of the protein family is due to the sequence similarity between the conserved N-terminal region of KCTD proteins and the tetramerization domain in some voltage-gated potassium channels. Dozens of publications suggest that KCTD proteins have roles in various biological processes and diseases. In this review, we summarize the character of Bric-a-brack,Tram-track, Broad complex(BTB) of KCTD proteins, their roles in the ubiquitination pathway, and the roles of KCTD mutants in diseases. Furthermore, we review potential downstream signaling pathways and discuss future studies that should be performed.     

Protein secretion through autotransporter and two-partner pathways

Two distinct protein secretion pathways, the autotransporter (AT) and the two-partner secretion (TPS) pathways are characterized by their apparent simplicity. Both are devoted to the translocation across the outer membrane of mostly large proteins or protein domains. As implied by their name, AT proteins contain their own transporter domain, covalently attached to the C-terminal extremity of the secreted passenger domain, while TPS systems are composed of two separate proteins, with TpsA being the secreted protein and TpsB its specific transporter. In both pathways, the secreted proteins are exported in a Sec-dependent manner across the inner membrane, after which they cross the outer membrane with the help of their cognate transporters. The AT translocator domains and the TpsB proteins constitute distinct families of protein-translocating, outer membrane porins of Gram-negative bacteria. Both types of transporters insert into the outer membrane as beta-barrel proteins possibly forming oligomeric pores in the case of AT and serve as conduits for their cognate secreted proteins or domains across the outer membrane. Translocation appears to be folding-sensitive in both pathways, indicating that AT passenger domains and TpsA proteins cross the periplasm and the outer membrane in non-native conformations and fold progressively at the cell surface. A major difference between AT and TPS pathways arises from the manner by which specificity is established between the secreted protein and its transporter. In AT, the covalent link between the passenger and the translocator domains ensures the translocation of the former without the need for a specific molecular recognition between the two modules. In contrast, the TPS pathway has solved the question of specific recognition between the TpsA proteins and their transporters by the addition to the TpsA proteins of an N-proximal module, the conserved TPS domain, which represents a hallmark of the TPS pathway.     

Network pharmacology,molecular docking integrated surface plasmon resonance technology reveals the mechanism of Toujie Quwen Granules against coronavirus disease 2019 pneumonia

BackgroundThe Coronavirus disease 2019 pneumonia broke out in 2019 (COVID-19) and spread rapidly, which causes serious harm to the health of people and a huge economic burden around the world.PurposeIn this study, the network pharmacology, molecular docking and surface plasmon resonance technology (SPR) were used to explore the potential compounds and interaction mechanism in the Toujie Quwen Granules (TQG) for the treatment of coronavirus pneumonia 2019.Study designThe chemical constituents and compound targets of Lonicerae Japonicae Flos, Pseudostellariae Radix, Artemisia Annua L, Peucedani Radix, Forsythiae Fructus, Scutellariae Radix, Hedysarum Multijugum Maxim, Isatidis Folium, Radix Bupleuri, Fritiliariae Irrhosae Bulbus, Cicadae Periostracum, Poria Cocos Wolf, Pseudobulbus Cremastrae Seu Pleiones, Mume Fructus, Figwort Root and Fritillariae Thunbrgii Bulbus in TQG were searched. The target name was translated to gene name using the UniProt database and then the Chinese medicine-compound-target network was constructed. Protein-protein interaction network (PPI), Gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the core targets were performed in the Metascape to predict its mechanism. The top 34 compounds in the Chinese medicine-compound-target network were docked with SARS-CoV-2 3CL enzyme and SARS-­CoV­-2 RNA-dependent RNA polymerase (RdRp) and then the 13 compounds with lowest affinity score were docked with angiotensin-converting enzyme 2 (ACE2), SARS-CoV-2 Spike protein and interleukin 6 to explore its interaction mechanism. Lastly, SPR experiments were done using the quercetin, astragaloside IV, rutin and isoquercitrin, which were screened from the Chinese medicine-compound-target network and molecular docking.ResultsThe Chinese medicine-compound-target network includes 16 medicinal materials, 111 compounds and 298 targets, in which the degree of PTGS2, TNF and IL­6 is higher compared with other targets and which are the disease target exactly. The result of GO function enrichment analysis included the response to the molecule of bacterial origin, positive regulation of cell death, apoptotic signaling pathway, cytokine-mediated signaling pathway, cytokine receptor binding and so on. KEGG pathway analysis enrichment revealed two pathways: signaling pathway­ IL-17 and signaling pathway­ TNF. The result of molecular docking showed that the affinity score of compounds including quercetin, isoquercitrin, astragaloside IV and rutin is higher than other compounds. In addition, the SPR experiments revealed that the quercetin and isoquercitrin were combined with SARS-CoV-2 Spike protein rather than Angiotensin-converting enzyme 2, while astragaloside IV and rutin were combined with ACE2 rather than SARS-CoV-2 Spike protein.ConclusionTQG may have therapeutic effects on COVID-19 by regulating viral infection, immune and inflammation related targets and pathways, in the way of multi-component, multi-target and multi-pathway.