GSDS: 基因结构显示系统

构建了一个用于绘制基因结构示意图的网站系统(http://gsds.cbi.pku.edu.cn/)。用户可提交核酸序列、NCBI核酸序列号或基因外显子位置信息, 得到基因结构示意图; 并可指定在基因结构图上标注某些特定区域。系统允许用户同时输入多个基因, 并指定输出次序和标注区域。结果可用位图和矢量图两种图形格式显示。点击位图格式结果, 可以查看相应序列。系统提供中英文两种用户界面。     

Sequence to Structure (S2S): display, manipulate and interconnect RNA data from sequence to structure

SUMMARY: Efficient RNA sequence manipulations (such as multiple alignments) need to be constrained by rules of RNA structure folding. The structural knowledge has increased dramatically in the last years with the accumulation of several large RNA structures similar to those of the bacterial ribosome subunits. However, no tool in the RNA community provides an easy way to link and integrate progress made at the sequence level using the available three-dimensional information. Sequence to Structure (S2S) proposes a framework in which an user can easily display, manipulate and interconnect heterogeneous RNA data, such as multiple sequence alignments, secondary and tertiary structures. S2S has been implemented using the Java language and has been developed and tested under UNIX systems, such as Linux and MacOSX. AVAILABILITY: S2S is available at http://bioinformatics.org/S2S/.     

Topological and sequence information predict that foldons organize a partially overlapped and hierarchical structure

It has been suggested that proteins have substructures, called foldons, which can cooperatively fold into the native structure. However, several prior investigations define foldons in various ways, citing different foldon characteristics, thereby making the concept of a foldon ambiguous. In this study, we perform a Gō model simulation and analyze the characteristics of substructures that cooperatively fold into the native‐like structure. Although some results do not agree well with the experimental evidence due to the simplicity of our coarse‐grained model, our results strongly suggest that cooperatively folding units sometimes organize a partially overlapped and hierarchical structure. This view makes us easy to interpret some different proposal about the foldon as a difference of the hierarchical structure. On the basis of this finding, we present a new method to assign foldons and their hierarchy, using structural and sequence information. The results show that the foldons assigned by our method correspond to the intermediate structures identified by some experimental techniques. The new method makes it easy to predict whether a protein folds sequentially into the native structure or whether some foldons fold into the native structure in parallel. Proteins 2015; 83:1900–1913. © 2015 Wiley Periodicals, Inc.     

Detecting DNA-binding helix-turn-helix structural motifs using sequence and structure information

In this work, we analyse the potential for using structural knowledge to improve the detection of the DNA-binding helix–turn–helix (HTH) motif from sequence. Starting from a set of DNA-binding protein structures that include a functional HTH motif and have no apparent sequence similarity to each other, two different libraries of hidden Markov models (HMMs) were built. One library included sequence models of whole DNA-binding domains, which incorporate the HTH motif, the second library included shorter models of ‘partial’ domains, representing only the fraction of the domain that corresponds to the functionally relevant HTH motif itself. The libraries were scanned against a dataset of protein sequences, some containing the HTH motifs, others not. HMM predictions were compared with the results obtained from a previously published structure-based method and subsequently combined with it. The combined method proved more effective than either of the single-featured approaches, showing that information carried by motif sequences and motif structures are to some extent complementary and can successfully be used together for the detection of DNA-binding HTHs in proteins of unknown function.     

AUGUR: a program to predict, display and analyze the tertiary structure of B-DNA

A UGUR is a program to predict, display and analyze the three-dimensionalstructure of B-DNA. The user can choose one of six models topredict the helical parameters of a given sequence. These parametersare then used to generate the coordinates of the DNA model inthree-dimensional space (trajectory). The trajectory can bedisplayed and rotated on a graphics terminal The trajectoryand helical parameters can also be searched for bends and structuralhomologues. Received on August 17, 1987; accepted on December 31, 1987     

VISSA: a program to visualize structural features from structure sequence alignment

MOTIVATION: Multiple sequence alignment is an important tool to understand and analyze functions of homologous proteins. However, the logic of residue conservation/variation is usually apparent only in three-dimensional (3D) space, not on a primary sequence level. Thus, in a traditional multiple alignment it is often difficult to directly visualize and analyze key residues because they are masked by other residues along the alignment. Here we present an integrated multiple alignment and 3D structure visualization program that can (1) map and highlight residues from a 1D alignment onto a 3D structure and vice versa and (2) display only the alignment of preselected, key residues. This program, called Visualize Structure Sequence Alignment, also has many other built-in tools that can help analyze multiple sequence alignments. AVAILABILITY: http://bioinformatics.burnham.org/liwz/vissa CONTACT: liwz@burnham.org.     

A homology identification method that combines protein sequence and structure information.

A new method is presented for identifying distantly related homologous proteins that are unrecognizable by conventional sequence comparison methods. The method combines information about functionally conserved sequence patterns with information about structure context. This information is encoded in stochastic discrete state-space models (DSMs) that comprise a new family of hidden Markov models. The new models are called sequence-pattern-embedded DSMs (pDSMs). This method can identify distantly related protein family members with a high sensitivity and specificity. The method is illustrated with trypsin-like serine proteases and globins. The strategy for building pDSMs is presented. The method has been validated using carefully constructed positive and negative control sets. In addition to the ability to recognize remote homologs, pDSM sequence analysis predicts secondary structures with higher sensitivity, specificity, and Q3 accuracy than DSM analysis, which omits information about conserved sequence patterns. The identification of trypsin-like serine proteases in new genomes is discussed.     

From sequence to structure to networks

A report on the 7th European Conference on Computational Biology (ECCB), Cagliari, Italy, 22-26 September 2008.     

MUSTER: Improving protein sequence profile-profile alignments by using multiple sources of structure information

We develop a new threading algorithm MUSTER by extending the previous sequence profile-profile alignment method, PPA. It combines various sequence and structure information into single-body terms which can be conveniently used in dynamic programming search: (1) sequence profiles; (2) secondary structures; (3) structure fragment profiles; (4) solvent accessibility; (5) dihedral torsion angles; (6) hydrophobic scoring matrix. The balance of the weighting parameters is optimized by a grading search based on the average TM-score of 111 training proteins which shows a better performance than using the conventional optimization methods based on the PROSUP database. The algorithm is tested on 500 nonhomologous proteins independent of the training sets. After removing the homologous templates with a sequence identity to the target >30%, in 224 cases, the first template alignment has the correct topology with a TM-score >0.5. Even with a more stringent cutoff by removing the templates with a sequence identity >20% or detectable by PSI-BLAST with an E-value <0.05, MUSTER is able to identify correct folds in 137 cases with the first model of TM-score >0.5. Dependent on the homology cutoffs, the average TM-score of the first threading alignments by MUSTER is 5.1-6.3% higher than that by PPA. This improvement is statistically significant by the Wilcoxon signed rank test with a P-value < 1.0 x 10(-13), which demonstrates the effect of additional structural information on the protein fold recognition. The MUSTER server is freely available to the academic community at http://zhang.bioinformatics.ku.edu/MUSTER.     

A workflow for mutation extraction and structure annotation

Rich information on point mutation studies is scattered across heterogeneous data sources. This paper presents an automated workflow for mining mutation annotations from full-text biomedical literature using natural language processing (NLP) techniques as well as for their subsequent reuse in protein structure annotation and visualization. This system, called mSTRAP (Mutation extraction and STRucture Annotation Pipeline), is designed for both information aggregation and subsequent brokerage of the mutation annotations. It facilitates the coordination of semantically related information from a series of text mining and sequence analysis steps into a formal OWL-DL ontology. The ontology is designed to support application-specific data management of sequence, structure, and literature annotations that are populated as instances of object and data type properties. mSTRAPviz is a subsystem that facilitates the brokerage of structure information and the associated mutations for visualization. For mutated sequences without any corresponding structure available in the Protein Data Bank (PDB), an automated pipeline for homology modeling is developed to generate the theoretical model. With mSTRAP, we demonstrate a workable system that can facilitate automation of the workflow for the retrieval, extraction, processing, and visualization of mutation annotations -- tasks which are well known to be tedious, time-consuming, complex, and error-prone. The ontology and visualization tool are available at (http://datam.i2r.a-star.edu.sg/mstrap).     

The peptaibol database: a sequence and structure resource.

The peptaibols are a large family of membrane-active peptides with considerable sequence homology, but with different biological properties and three-dimensional structures. They constitute a rich resource of naturally occurring 'mutants' which are potentially valuable for structure/function studies of ion channels. A searchable on-line database of sequences and structures of the peptaibols has been created at http://www.cryst.bbk.ac.uk/peptaibol, as a resource for the biological and structural community. In this paper, the contents and organization of the website are discussed as well as procedures for submission of new entries to the database. At present, more than 300 peptaibol sequences are stored in the database. Each sequence entry contains its full literature reference and information about its biological source. Tools are provided for searching for specific peptaibol sequences or groupings of sequences, and for locating peptaibols containing specified sequence motifs. In addition the website acts as a database for structural information. The coordinates of all currently available peptaibol x-ray and NMR structures are included and complemented, where appropriate. with molecular graphics illustrations. These include figures of model channel structures and comparisons between different peptaibol structures. The peptaibol database thus provides a tool for ready access to information and a means of investigating the sequences and structures of this class of polypeptides.     

SEAN: SNP prediction and display program utilizing EST sequence clusters

SEAN is an application that predicts single nucleotide polymorphisms (SNPs) using multiple sequence alignments produced from expressed sequence tag (EST) clusters. The algorithm uses rules of sequence identity and SNP abundance to determine the quality of the prediction. A Java viewer is provided to display the EST alignments and predicted SNPs.     

Band-shape analysis and display of fine structure in protein spectra: a new approach to perturbation spectroscopy

The shape of light absorption bands of proteins to about 250 nm can be described as the sum of two overlapping lognormal distribution curves. A plot of the differences between the mathematically smooth fitted curve and the experimental points provides a vivid display of vibronic fine structure. Band parameters and difference plots are provided for the N-acetyl-ethyl esters of the aromatic amino acids and are compared with those of glucagon, ribonuclease, chymotrypsinogen, lysozyme and apoaspartate aminotransferase. Changes in band parameters and fine structure are observed upon denaturation and in conversion of glucagon to fibril form.     

Live sequence charts to model medical information

Background

Consensus exists that several bariatric surgery procedures produce a rapid improvement of glucose homeostasis in obese diabetic patients, improvement apparently uncorrelated with the degree of eventual weight loss after surgery. Several hypotheses have been suggested to account for these results: among these, the anti-incretin, the ghrelin and the lower-intestinal dumping hypotheses have been discussed in the literature. Since no clear-cut experimental results are so far available to confirm or disprove any of these hypotheses, in the present work a mathematical model of the glucose-insulin-incretin system has been built, capable of expressing these three postulated mechanisms. The model has been populated with critically evaluated parameter values from the literature, and simulations under the three scenarios have been compared.

Results

The modeling results seem to indicate that the suppression of ghrelin release is unlikely to determine major changes in short-term glucose control. The possible existence of an anti-incretin hormone would be supported if an experimental increase of GIP concentrations were evident post-surgery. Given that, on the contrary, collected evidence suggests that GIP concentrations decrease post-surgery, the lower-intestinal dumping hypothesis would seem to describe the mechanism most likely to produce the observed normalization of Type 2 Diabetes Mellitus (T2DM) after bariatric surgery.

Conclusions

The proposed model can help discriminate among competing hypotheses in a context where definitive data are not available and mechanisms are still not clear.     

Live sequence charts to model medical information

ABSTRACT: BACKGROUND: Medical records accumulate data concerning patient health and the natural history of disease progression. However, methods to mine information systematically in a form other than an electronic health record are not yet available. The purpose of this study was to develop an object modeling technique as a first step towards a formal database of medical records. METHOD: Live Sequence Charts (LSC) were used to formalize the narrative text obtained during a patient interview. LSCs utilize a visual scenario-based programming language to build object models. LSC extends the classical language of UML message sequence charts (MSC), predominantly through addition of modalities and providing executable semantics. Interobject scenarios were defined to specify natural history event interactions and different scenarios in the narrative text. Result A simulated medical record was specified into LSC formalism by translating the text into an object model that comprised a set of entities and events. The entities described the participating components (i.e., doctor, patient and record) and the events described the interactions between elements. A conceptual model is presented to illustrate the approach. An object model was generated from data extracted from an actual new patient interview, where the individual was eventually diagnosed as suffering from Chronic Fatigue Syndrome (CFS). This yielded a preliminary formal designated vocabulary for CFS development that provided a basis for future formalism of these records. CONCLUSIONS: Translation of medical records into object models created the basis for a formal database of the patient narrative that temporally depicts the events preceding disease, the diagnosis and treatment approach. The LSCs object model of the medical narrative provided an intuitive, visual representation of the natural history of the patient's disease.     

Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information

Background  

Structural properties of proteins such as secondary structure and solvent accessibility contribute to three-dimensional structure prediction, not only in the ab initio case but also when homology information to known structures is available. Structural properties are also routinely used in protein analysis even when homology is available, largely because homology modelling is lower throughput than, say, secondary structure prediction. Nonetheless, predictors of secondary structure and solvent accessibility are virtually always ab initio.