Discovery of promiscuous HLA-II-restricted T cell epitopes with TEPITOPE

TEPITOPE is a prediction model that has been successfully applied to the in silico identification of T cell epitopes in the context of oncology, allergy, infectious diseases, and autoimmune diseases. Like most epitope prediction models, TEPITOPE's underlying algorithm is based on the prediction of HLA-II peptide binding, which constitutes a major bottleneck in the natural selection of epitopes. An important step in the design of subunit vaccines is the identification of promiscuous HLA-II ligands in sets of disease-specific gene products. TEPITOPE's user interface enables the systematic prediction of promiscuous peptide ligands for a broad range of HLA-binding specificity. We show how to apply the TEPITOPE prediction model to identify T cell epitopes, and provide both a road map and examples of its successful application.     

植物长链非编码RNA的生物信息学预测与分析研究进展

长链非编码RNA(Long non-coding RNAs,lncRNAs)是一类广泛存在于真核生物中,长度大于200个核苷酸、无蛋白编码功能,具有调控基因转录后表达的RNA转录本。新近研究表明,lncRNA在多种生物途径中起着重要调节作用。生物信息学由生物、数学、计算机科学,统计学等多学科交叉产生,能从全局和系统水平对大数据信息进行深入挖掘与分析。采用生物信息学方法预测与分析lncRNA是当前发现和鉴定植物lncRNA的重要策略之一。本文梳理和总结了近年来采用生物信息学预测植物lncRNA及其靶基因的方法策略,以期为今后深入认知植物lncRNA在植物的生长发育过程、抗逆境胁迫及系统进化等过程中的作用研究提供一定参考。     

生物信息学在蛋白质组学研究中的应用进展

生物信息学是运用数学和信息学方法阐明和解释海量生物学数据所蕴含的生物学意义的重要手段和工具.随着蛋白质组学研究的不断发展和深入,大量的蛋白序列、结构、功能以及互作数据不断产生.面对海量蛋白质组数据的获取、处理、存储以及蛋白质组数据信息的挖掘,生物信息学已成为蛋白组学研究中不可或缺的组成部分.本文结合蛋白质组学的发展历程...     

基于生物信息学的胃癌早期诊断预测模型研究

利用The Cancer Genome Atlas和Genotype-Tissue Expression公共数据检索收集胃癌(Gastric cancer, GC)基因表达数据集,筛选与早期胃癌密切相关的基因并构建胃癌早期诊断预测模型。运用Deseq2软件包筛选早期胃癌差异基因,并对差异基因进行GO和KEGG富集分析。通过STRING数据库建立其蛋白质相互作用网络并利用Cytoscape软件提取关键子网得到候选关键基因,进一步利用MedCalc软件确认胃癌早期诊断关键基因。根据筛选得到的10个关键基因构建基于支持向量机、随机森林、朴素贝叶斯、K-近邻、极限梯度提升和自适应提升等六种算法的胃癌早期诊断预测模型,依据ROC曲线和准确率等评价指标对各个分类器模型进行评估,通过独立测试集验证得到极致梯度提升诊断预测模型为最优模型。本研究成果为提高结胃癌早期诊断的研究提供了新的思路和方法。     

Capabilities of bioinformatics tools for optimizing physicochemical features of proteins used in Nano biosensors: A short overview of the tools related to bioinformatics

Protein-protein ligand is one of the most detection methods used in Nano biosensors. Based on the advantage of specific docking between two special 3D structures, they have become a potent candidate in bioanalysis and Nanodiagnostic tools. These tools lease users to do a simple, fast, cost-effective, sensitive, and specific detection of molecular biomarkers in real samples. Recent advantages of using protein-protein ligand Nano-biosensors application is remarkable due to its special docking that refers to each protein unique 3D conformation. However, it challenges different problems such as low rate of docking and hard process for fixation on the basic layer. These challenges make developers to optimize the structure and functions of proteins. The process has different Nano scale calculation that could be done with algorithms and solutions are available as bioinformatics tools. This article aimed to have a short overview of the abilities of bioinformatics tools for modeling and optimization of physiochemical features of proteins in Nano scale.     

细胞外基质蛋白质预测工具研究进展

细胞外基质蛋白质在细胞的一系列生物过程中发挥着重要作用,它的异常调节会导致很多重大疾病。理论细胞外基质蛋白质参考数据是实现细胞外基质蛋白质高效鉴定的基础,研究者们已经基于机器学习的方法开发出一系列的细胞外基质蛋白质预测工具。文中首先阐述了基于机器学习模型构建细胞外基质蛋白质预测工具的基本流程,之后以工具为单位总结了已有细胞外基质蛋白质预测工具的研究成果,最后提出了细胞外基质蛋白质预测工具目前面临的问题和可能的优化方法。     

T and B-cell epitopes prediction of Iranian saffron (Crocus sativus) profilin by bioinformatics tools

Plant profilins form a well-known panallergen family responsible for cross-sensitization between plant foods and pollens. We sought to map T and B-cell epitopes on the Iranian Crocus sativus profilin by bioinformatics tools. The predicted peptides are useful for further vaccine development.     

A whole-genome bioinformatics approach to selection of antigens for systematic antibody generation

Here, we present an antigen selection strategy based on a whole-genome bioinformatics approach, which is facilitated by an interactive visualization tool displaying protein features from both public resources and in-house generated data. The web-based bioinformatics platform has been designed for selection of multiple, non-overlapping recombinant protein epitope signature tags by display of predicted information relevant for antigens, including domain- and epitope sized sequence similarities to other proteins, transmembrane regions and signal peptides. The visualization tool also displays shared and exclusive protein regions for genes with multiple splice variants. A genome-wide analysis demonstrates that antigens for approximately 80% of the human protein-coding genes can be selected with this strategy.     

In silico analysis of squalene synthase in Fabaceae family using bioinformatics tools

Triterpenoid saponins are a diverse group of bioactive compounds, which are used for possessing of many biomedical and pharmaceutical products. Generally, squalene synthase (SQS) is defined as an emerging and essential branch point enzyme far from the major pathway of isoprenoids biosynthetic and a latent adjusting point, which manages carbon flux into triterpenes biosynthesis and sterols. The present study deals with the detailed characterization of SQS by bioinformatics approaches to evaluate physicochemical properties, structural characteristics including secondary and 3D structure prediction and functional analysis from eight plants related to Fabaceae family and Arabidopsis thaliana. Bioinformatics analysis revealed that SQS proteins have two transmembrane regions in the C-terminal. The predicted motifs were used to design universal degenerate primers for PCR analysis and other molecular applications. Phylogenetic analysis showed conserved regions at different stretches with maximum homology in amino acid residues within all SQSs. The secondary structure prediction results showed that the amino acid sequence of all squalene synthases had α helix and random coil as the main components. The reliability of the received model was confirmed using the ProSA and RAMPAGE programs. Determining of active site by CASTp proposes the possibility of using this protein as probable medication target. The findings of the present study may be useful for further assessments on characterization and cloning of squalene synthase.     

乙型肝炎病毒S蛋白的序列特征分析

乙肝病毒S蛋白是病毒的包膜蛋白,与病毒进入细胞有关,它存在逆转录过程并且具有极强的潜伏性。本论文应用生物信息学分析乙肝病毒S蛋白的序列特征,利用在线分析软件预测乙肝病毒S蛋白的理化性质和亲疏水性、跨膜区域、信号肽特征、磷酸化位点、二级结构以及乙肝病毒S蛋白的最佳抗原表位形成位置等。结果显示了乙肝病毒S蛋白由226个氨基酸组成,理论等电点是8.21,为不稳定蛋白,总平均亲水性为0.649,是疏水蛋白质,并且该蛋白存在信号肽,有4个跨膜区,有30个潜在的磷酸化位点,主要二级结构为α螺旋和无规则卷曲,同时,结合乙型肝炎病毒S蛋白的序列可及性、线性表位、β转角、柔性、抗原性的预测结果,可以找到潜在的抗原表位区域,为乙型肝炎的表位疫苗研制提供重要的参考依据,有利于进一步对乙型肝炎S蛋白的抗原性进行研究。     

甘蔗细胞色素P450还原酶基因的电子克隆与分析

旨在为甘蔗细胞色素P450还原酶基因的实验克隆、功能鉴定及其应用提供参考。本研究以甘蔗类似细胞色素P450还原酶基因的EST序列CF576130.1为探针,在甘蔗EST数据库中进行检索,并基于电子克隆技术获得了甘蔗细胞色素P450还原酶基因（Cytochrome P450 reductase）的一条cDNA全长序列,命名为ScCYP450。采用生物信息学方法,对该基因编码蛋白从氨基酸组成、理化性质、亚细胞定位、跨膜结构域、疏水性/亲水性、高级结构及功能域等方面进行预测和分析。结果表明该基因全长1 821 bp,包含一个744 bp的开放阅读框,编码247个氨基酸,该基因编码蛋白定位于细胞内质网（膜）,为可溶性碱性蛋白,不存在信号肽,二级结构原件多为无规卷曲,含有多个保守功能域,主要功能为辅酶因子生物合成和翻译功能。     

甘蔗天冬氨酰半醛脱氢酶基因的电子克隆与分析

应用电子克隆技术,以水稻EF576477序列为探针,获得了甘蔗天冬氨酰半醛脱氢酶基因（aspartate．semialdehydedehy—drogenase,ASADH）的一条cDNA全长序列,命名为ScASADH。采用生物信息学方法,对该基因编码蛋白从氨基酸组成、理化性质、亚细胞定位、跨膜结构域、疏水性／亲水性、高级结构及功能域等方面进行预测和分析。结果表明：该基因全长1711bp,包含一个1128bp的开放阅读框,编码375个氨基酸,该基因编码蛋白定位于细胞核,为可溶性蛋白,存在信号肽,二级结构原件多为无规卷曲,含有多个保守功能域,主要功能为翻译。电子表达分析结果显示,该基因在甘蔗根尖、幼苗、花序、叶片和茎中组成型表达,其中在茎中的表达量比其他组织类型中表达量高。该基因的表达受葡萄糖杆菌和赤腐病菌的调控。     

甘蔗过氧化氢酶基因的电子克隆及生物信息学分析

应用电子克隆技术,获得甘蔗中一个过氧化氢酶基因的cDNA序列全长,命名为S-CAT。该基因全长2160bp,包含一个1479bp的开放阅读框,编码492个氨基酸。通过PSORT工具,预测甘蔗S-CAT蛋白存在于过氧化物酶体中。同源比对分析显示,S-CAT基因编码的氨基酸序列与水稻、玉米、高粱、朝鲜碱茅、葡萄等植物中过氧化氢酶基因所编码的氨基酸序列高度同源,同源性分别为97%,97%,95%,91%和92%。研究结果为该基因的实验克隆奠定基础。     

甘蔗细胞色素C基因的电子克隆与分析

以甘蔗类似细胞色素C的EST序列CF576943.1为探针,通过电子克隆技术获得了甘蔗细胞色素C基因（Cytochrome C,Cyt C）的一条cDNA全长序列,命名为ScCyt C.用生物信息学方法对该基因氨基酸序列与组成、亚细胞定位、跨膜区与信号肽、疏水性/亲水性、蛋白质二、三级结构以及功能等进行分析与预测.结果表明：Cyt C基因全长1 073 bp,编码112个氨基酸,该基因位于细胞质,为非分泌型蛋白,无规卷曲为主要二级结构原件,含有1个保守功能域,主要功能为翻译并且在不同植物中具有高度保守性.电子表达分析结果显示,该基因在甘蔗各个组织均有表达,其中在茎和根中的表达量比其他组织类型中表达量高,此外,该基因的表达可能受到低温的调控.为甘蔗细胞色素C基因的结构及其功能的研究奠定了一定的基础.     

甘蔗几丁质酶基因的电子克隆与生物信息学分析

用电子克隆方法获得甘蔗几丁质酶基因SCCHI1,采用生物信息学方法,对该基因编码蛋白从氨基酸组成、理化性质、跨膜结构域、疏水性/亲水性、亚细胞定位、高级结构及功能域等方面进行了预测和分析。结果表明:SCCHI1基因全长1236bp,包含一个完整的990bp的ORF,编码329个氨基酸。SCCHI1基因属于糖苷水解酶19家族,含有N-端信号肽、交连区、催化区,与高粱等其它植物的几丁质酶基因具有高度的相似性。为SCCHI1基因的分子克隆、功能鉴定和应用提供参考。     

Structural bioinformatics prediction of membrane-binding proteins

Membrane-binding peripheral proteins play important roles in many biological processes, including cell signaling and membrane trafficking. Unlike integral membrane proteins, these proteins bind the membrane mostly in a reversible manner. Since peripheral proteins do not have canonical transmembrane segments, it is difficult to identify them from their amino acid sequences. As a first step toward genome-scale identification of membrane-binding peripheral proteins, we built a kernel-based machine learning protocol. Key features of known membrane-binding proteins, including electrostatic properties and amino acid composition, were calculated from their amino acid sequences and tertiary structures, which were then incorporated into the support vector machine to perform the classification. A data set of 40 membrane-binding proteins and 230 non-membrane-binding proteins was used to construct and validate the protocol. Cross-validation and holdout evaluation of the protocol showed that the accuracy of the prediction reached up to 93.7% and 91.6%, respectively. The protocol was applied to the prediction of membrane-binding properties of four C2 domains from novel protein kinases C. Although these C2 domains have 50% sequence identity, only one of them was predicted to bind the membrane, which was verified experimentally with surface plasmon resonance analysis. These results suggest that our protocol can be used for predicting membrane-binding properties of a wide variety of modular domains and may be further extended to genome-scale identification of membrane-binding peripheral proteins.     

甘蔗MYB2转录因子的电子克隆和生物信息学分析

用电子克隆方法获得甘蔗MYB2基因,采用生物信息学方法,对该基因编码蛋白从氨基酸组成、理化性质、跨膜结构域、疏水性/亲水性、亚细胞定位、高级结构及功能域等方面进行了预测和分析。结果表明:甘蔗MYB2基因全长991bp,包含570bp的ORF,编码189个氨基酸。甘蔗MYB2基因包含有MYB功能域,在序列组成、高级结构及活性位点等方面,与玉米等其它植物的MYB2基因具有高度的相似性。研究结果为该基因的实验克隆奠定基础。     

Advances in omics and bioinformatics tools for systems analyses of plant functions

Omics and bioinformatics are essential to understanding the molecular systems that underlie various plant functions. Recent game-changing sequencing technologies have revitalized sequencing approaches in genomics and have produced opportunities for various emerging analytical applications. Driven by technological advances, several new omics layers such as the interactome, epigenome and hormonome have emerged. Furthermore, in several plant species, the development of omics resources has progressed to address particular biological properties of individual species. Integration of knowledge from omics-based research is an emerging issue as researchers seek to identify significance, gain biological insights and promote translational research. From these perspectives, we provide this review of the emerging aspects of plant systems research based on omics and bioinformatics analyses together with their associated resources and technological advances.     

Methods and protocols for prediction of immunogenic epitopes

T-cell recognition of peptide/major histocompatibility complex (MHC) is a prerequisite for cellular immunity. Recently, there has been an influx of bioinformatics tools to facilitate the identification of T-cell epitopes to specific MHC alleles. This article examines existing computational strategies for the study of peptide/MHC interactions. The most important bioinformatics tools and methods with relevance to the study of peptide/MHC interactions have been reviewed. We have also provided guidelines for predicting antigenic peptides based on the availability of existing experimental data.     

生物信息学及其在新药发现中的应用

人类基因组计划和蛋白质组计划的开展,为生物医药研究提供丰富的生物学信息。而在这纷繁复杂的生物信息中寻找合适的药物作用靶标是生物信息学的重要目的之一。目前,生物信息学已成为新药发现的重要工具和手段。