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How to draw protein topology diagram

Ribbon diagrams , also known as Richardson diagrams , are 3D schematic representations of protein structure and are one of the most common methods of protein depiction used today. The ribbon shows the overall path and organization of the protein backbone in 3D, and serves as a visual framework on which to hang details of the full atomic structure Proteins are large biomolecules and macromolecules that comprise one or more long chains of amino acid residues. Proteins perform a vast array of functions within organisms, including catalysing metabolic reactions, DNA replication, responding to stimuli, providing structure to cells and organisms, and transporting molecules from one location to another. EzEditor is a java-based sequence alignment editor for rRNA and protein coding genes.


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Metrics details. In protein design, correct use of topology is among the initial and most critical feature. Meticulous selection of backbone topology aids in drastically reducing the structure search space.

With ProLego, we present a server application to explore the component aspect of protein structures and provide an intuitive and efficient way to scan the protein topology space. Using the topology string, ProLego, compares topology against a non-redundant extensive topology database ProLegoDB as well as extracts constituent topological modules.

The platform offers interactive topology visualization graphs. ProLego, provides an alternative but comprehensive way to scan and visualize protein topology along with an extensive database of protein topology.

Understanding of protein fold universe remains one of the major goal in post genomic era. Topology based approach has been recently exploited to examine the structure space of proteins and provide insights into fold designing and evolution [ 4 , 5 , 6 , 7 ]. Topology has been used extensively to address the nature of folding profile by both experimental and computational approaches [ 8 ].

Rockline et al. The use of topology in the context of protein designing, folding and stability studies has been widely used. Structural modularity is crucial in conferring functional and structural diversity of proteins [ 6 , 10 ]. Protein topology has been studied using several graph-based techniques to understand domain arrangement [ 12 , 13 ], protein folding pathways [ 8 ], analysis of different biochemical activities and structural comparison [ 14 ]. With the emergence of computer graphics, protein topology representation evolved from manual drawing [ 15 ] to scalable graphics representation [ 16 , 17 ].

However, only handful of methods are available that provide automatic generation of the protein topology diagram Additional file 1 section 1.

PTGL is a continuously developing topology library with the aim to provide protein folding graphs [ 18 , 19 ]. However, the issue of module identification and visualisation could be addressed in much efficient way as proposed by protein lego server, as reported here. With ProLego, we propose a platform that can be used to analyse protein topology and its modular architecture. ProLego, along with generating improved topology cartoon diagrams, provide tools for searching proteins with similar topology and extracting constituent structural modules.

Briefly, in the background, user provided protein chain examined for secondary structure SS contacts and relative orientation.

The SS-contact definition is considered based on the presence of corresponding residual contacts as in [ 14 , 20 ]. The architecture of the server is discussed in Additional file 1 : Figure S1. ProLego leverages the component approach of protein topology space to extract inherent modules, similar topology and assigns topology frequency class Preferred, Non-preferred. Representing protein topology as a graph of secondary structure, ProLego provides visualization focusing on different representation Fig.

ProLegoDB is an extensive database of protein topology generated by analysis of representative datasets Additional file 1 section 1. The proposed web platform provides an intuitive approach to explore the protein structure topology space. In the following section, some of the key finding in nature of topology space by analysis of different representative non-redundant datasets have been discussed.

Some of the salient features of the server application has been presented along with a comparative study with current state-of-the-arts topology servers. The chain an anit-parallel beta sheet at the N-terminal followed by seven alpha-helices. Fig a. In linear topology a.

The length of helical rectangles scaled as per number of residues in corresponding helix. The protein chain is represented as red to green to blue as passes from N to C terminal. The linear lines, connecting secondary structure SS blocks shows chain connectivity, whereas the arc lines represent spatial connectivity and type of SS contact colour coded as labelled in Additional file 1 : Table S4.

The secondary structure contact map a. A 3D carton representation VMD generated a. The 2D ProLego cartoon shows contact between two SS blocks by red dotted lines and chain connectivity by black continuous line. Helices are represented as circles and stands as rectangles.

PTGL considers, 3 10 helices also in total helix, hence the addition of 1st and 7th helix, giving total number of helix to 9 instead of 7 alpha-helix as per ProLego in this protein. PTGL misses the N-terminal sheet, which is represented as up-down triangle for anti-parallel orientation in case of ProLego. Using secondary structures SS as building blocks of protein structure, we have defined topology as the arrangement, spatial contacts and organisation of SS in a protein chain.

Applying this simple but efficient definition, we have scanned representative protein structure databases and extracted underlying topological space. The representative data sets have been curated for sequence redundancy with state-of-the-art methods to mitigate the effect of structural bias in current protein structure space. A brief description of dataset statistics can be read from Table 1 and from Additional file 1 section 1.

The significance is further examined with restricting false discovery rate to less than 0. Figure 2 , describes the distribution of proteins in statistically significant topologies.

For each case, the density of distribution is represented by the width of the violin plot and the spread of the inter-quartile region describes the variation. For each case, maximum density of the data can be found around their respective mean and interquartile regions, whose values varies for topology and proteins in both cases.

Similar analysis has been performed for different datasets and among structural classes Additional file 1 : Figure S5. Among all studied cases, we have observed the consistent distribution of topology space, with tolerable variance in protein distribution across structure classes.

Description of dataset has been provided in the text and supplementary. The shape of violin plot describes the kernel density estimation of the distribution of data in different topologies and proteins. A summary of statistics can be drawn from the inner boxplot. Using the topology string, it is possible to draw a distribution and study the variation in topology in protein structure space.

As shown by the Fig. The secondary structure contact map illustrates the presence of contact and their relative orientation with different colour codes.

Spatial contacts between SS have been shown as arcs. The cartoon view, illustrates the protein topology graph where solid lines show the sequential SSE contact whereas, the dashed red line shows the presence of tertiary contact between corresponding secondary structures. This protocol extracts sub-structures or modules from a protein by analysing topology string. The topology database, ProLegoDB, are then used to map the protein chains and domains with each resultant topology modules.

A working example of extracted topological modules for photoreaction centre protein 1JB0:L has been discussed in Additional file 1 : Table S3.

ProLegoDB is an extensive database for protein topology. This database has 58, protein chains and 14, protein domains topology analysed and grouped into statistically significant topology groups Table 1. As the topologies are defined as per their secondary structure construct, its relatively easy to divide the whole space into all-alpha A , all-beta B and alpha-beta AB , structure classes.

Each topology has been reported with observed occurrence frequency and statistical significance score Additional file 1 : Table S5. A search in ProLegoDB can be performed from three levels i. Topology, Protein and Domains. The query result lists all possible topologies with requested SS-composition along with their significant scores.

Each row of the result has the corresponding link describing topology. This is a subsequent upgrade and development over protein topology graph library [ 18 , 19 ]. The most recent addition include ligand information in protein secondary structure contact and decomposes protein chain into alpha, beta and alpha-beta and receptor—ligand graphs [ 17 ].

The approach is shown to be used for searching sub-graphs, which is a crucial aspect of protein graph analysis, as also reported by Pro-Origami [ 16 ] and Tableaux [ 26 ]. With ProLego, we illustrate the usability of string based topological representation.

ProLego, provides more detailed and modular view to protein topology landscape. Our primary focus is to describe the variation in protein topology space, hence have not considered the ligand interactions.

The extensive topology database, with different search modules, is advantageous to tailor search for topology. Identification of topological modules remains one of the most significant development in ProLego as compare to other topology databases. In protein designing, managing and filtering designed templates is one of the major challenges.

In recent development in the field, Rocklin et al. In different rounds of optimisation, authors have generated de-novo decoys which provides an ideal synthetic dataset for investigating the occurrence of ProLego topology.

Detail of experimental setup and dataset used has been discussed in Additional file 1 section 1. With ProLego, we aim to provide an alternative approach to study protein structure topology. The component approach is found to be efficiently scanning the structure space and explore the nature of topology space.

To understand the secondary structure based architecture in proteins, ProLego have compiled an extensive topology database analyzing different sets of non-redundant representative protein datasets.

The server application provides an easy access to the database as well as enables users to investigate their protein of interest. With the integration of state-of-the-art framework and libraries, improved topology visualization approaches have been implemented and compared with other open source topology servers.

Nucleic Acids Res. The history of the CATH structural classification of protein domains. Classification of proteins with shared motifs and internal repeats in the ECOD database. Bolon D, baker D, Tawfik D, editors. Protein Sci. Biochem Biophys Res Commun. Protein structures, folds and fold spaces. J Phys Condens Matter. Article Google Scholar.

Biochemical functional predictions for protein structures of unknown or uncertain function. Computational and Structural Biotechnology Journal. Modules identification in protein structures: the topological and geometrical solutions.


Science’s ‘Mother of Ribbon Diagrams’ celebrates 50 years at Duke

Essays Biochem 8 October ; 64 4 : — Structural biology is the study of the molecular arrangement and dynamics of biological macromolecules, particularly proteins. The resulting structures are then used to help explain how proteins function. This article gives the reader an insight into protein structure and the underlying chemistry and physics that is used to uncover protein structure. We start with the chemistry of amino acids and how they interact within, and between proteins, we also explore the four levels of protein structure and how proteins fold into discrete domains.

However, topology cartoons or what are often called schematic diagrams, have not until now been generated automatically for all classes of protein structure.

Protein topology


Biological network figures are ubiquitous in the biology and medical literature. On the one hand, a good network figure can quickly provide information about the nature and degree of interactions between items and enable inferences about the reason for those interactions. On the other hand, good network figures are difficult to create. In this paper, we outline 10 simple rules for creating biological network figures for communication, from choosing layouts, to applying color or other channels to show attributes, to the use of layering and separation. These rules are accompanied by illustrative examples. We also provide a concise set of references and additional resources for each rule. PLoS Comput Biol 15 9 : e This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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how to draw protein topology diagram

Hope they will release the source codes or compiled files for people who want to generate the topology diagrams of their fresh, before-submitting PDBs. Comment by im confused — February 4, am Reply. Choose one PDB e. It should work fine for any other PDBs.

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Metrics details. In protein design, correct use of topology is among the initial and most critical feature. Meticulous selection of backbone topology aids in drastically reducing the structure search space. With ProLego, we present a server application to explore the component aspect of protein structures and provide an intuitive and efficient way to scan the protein topology space. Using the topology string, ProLego, compares topology against a non-redundant extensive topology database ProLegoDB as well as extracts constituent topological modules. The platform offers interactive topology visualization graphs.

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So far we have discussed predominantly globular proteins that are soluble in water. Proteins are also found associated with membranes. Two major classes of membrane proteins are found in nature. In some of these integral membrane proteins, large extracellullar and intracellular domains of the protein are present, connected by the intramembrane regions. The intramembrane spanning region often consists of either a single alpha helix, or 7 different helical regions which zig-zag through the membrane.

There will be a central beta sheet surrounded by alpha helices. To decide which one of these proteins is related, draw a topology diagram for each one of them.

Scientific Calculator. Celsius Farenheit. Protein Analysis A. Symbols A.

In the following we will focus on the general aspects of protein secondary structure. The prediction was confirmed when the first three-dimensional structure of a protein, myoglobin by Max Perutz and John Kendrew was determined by X-ray crystallography. To get a better impression of how a helix looks like, only the main chain of the polypeptide is shown, no side chains. There are 3. Each residue is translated 1. Together these groups form a hydrogen bond, one of the main forces in the stabilization of secondary structure in proteins.

PTGLweb is a web server and database of protein structure topologies [Wolf et al. The graphs can be automated computed, visualized and used for further analysis.

Scientific visualization relies heavily on visual jargon. Symbols can carry highly specific information within a specific context, and allow the illustrator to efficiently communicate complex information with others that are fluent in that language. Flip through any science textbook, and you'll see these symbols rolling out along with new concepts. For example, students learn to interpret and use electron orbital diagrams in chemistry, Feynman diagrams in physics, and cladograms in paleontology. But other than perhaps Feynman diagrams likely due to the fact that they are named after the person that popularized them , I'm embarrassed to admit that I know very few origin stories of these visual languages. I read or use many of these symbols nearly every day in my job, and yet I don't know the authors. Last week—thanks to a tweet by Sonya Tadrowksi —I was virtually introduced to another author.

Biomolecular structures are complex, consisting of hundreds or thousands of atoms. Over the years, researchers have developed a variety of molecular graphics methods to display protein structures to make it easier to study and explore their properties. These molecular graphics programs allow you to upload a PDB file, display the structure on your computer, and create custom pictures of it. In addition, they often include analysis tools that allow you to measure distances and bond angles, and identify interesting structural features.




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  1. Kassi

    It is remarkable, very valuable information