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Help Section

This page provides help to the users to make them comfortable with the use of the webservices for predicting and designing Beta-turns.

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Beta Turn in proteins

Beta-turns are the most common type of non-repetitive structures, and constitute on average 25% of the residues in all protein chains. In a beta turn, a tight loop is formed when the carbonyl oxygen of one residue forms a hydrogen bond with the amide proton of an amino acid three residues down the chain. This hydrogen bond stabilizes the beta bend structure. A beta turn can reverse the direction of its peptide chain.

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Prediction of Beta Turn

In the past numerous methods were developed to predict the beta turns. But all of this method were trained to predict residue level prediction instead of four residue level. Since, a beta turn is composed of four consecutive amno acids. Using this simple approach we have achieved good prediction accuracy and realistic prediction of beta turns. To predict beta turns in your protein click »Submit »

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Propensity based Beta Turn prediction

In the past statistical methods were developed to predict the beta turns based upon propensity score of beta turn. The propensity score was calculated using few hundered PDBs. We have calculate new propensity score using ~18000 PDBs. Users can predict beta turns based upon various position based propensity score. Click here to »Submit »

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Designing of Beta Turn

For the first time, we have developed a module thats helps user in understanding the positional preference of pairs of amino acids. First, user sequence is mapped and various propensity score are shown for all possible tetrapeptide. Second, the module performs all possible mutation in a tetrapeptide, either to increase or decrease its beta turn formation probability. Click here to »Submit »

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Prediction of Beta Turn Type

In the past numerous methods were developed to predict the beta turn types. Using the turn level approach we have significantly improved the prediction accuracy of beta turn types. To predict beta turns types in your protein click »Submit »

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Algorithm

We have developed a algorithm that predcit complete beta turn, earlier algorithm predict the residue that are present in beta turn. They can predict a residue to be beta turn residue, even its neighbouring residue are non beta turn. Our algorithm has overcome all these limitation and can predict only four consecutive beta turn residues.

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Download dataset

To Download previously created dataset and the lastest dataset. We have created two dataset, one is 30% non-redunant and other is 90% non-redunant dataset.

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Help Section

This webpage is designed to help the users of the BetaTPred3 method. It provides the step wise instructions on how to use the BetaTPred3 webservice and its different modules. From sequence submission to the generation and visualization of results, everything is represented with graphical images.

The architecture of this help page is designed as per the different modules of BetaTPred3 as given below. You can click on the respective section to get the help of that module.

PredictionPropensityDesignTurn Type

Prediction


Prediction module is used to predict the BetaTurns in a protein sequence using random forest based models. User can enter peptide sequences in fasta format in the input box. The server also accepts multiple sequences in fasta format (max. 10 sequences at a time). User can also upload a file having multiple sequences in fasta format (max. 10 sequences at a time). An example sequence is also provided which can be filled in the input box by clicking on the 'Example Sequences' button. A threshold also needs to be selected for the prediction of betaturns in the protein. A score above the threshold will be predicted as betaturn and below that threshold will be predicted as non-turn. If email address is provided, the results will be mailed to the provided email address. (Figure 1).
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Figure 1. Graphical representation of the Prediction module of BetaTPred3 showing how to input the protein sequence and submitting it to the BetaTPred3 web-server.

The results of the Prediction module of BetaTPred3 is represented below in Figure 2. For each protein sequence, the first line represents the protein ID given by the user, the second line represents the sequence of the protein. The third line represents the prediction of turn/non-turn and fourth line represents the probability score of the prediction of turn/non-turn. The predicted betaturns are represented by color while non-turns are represented by black color. Start of a betaturn is represented by a red color and other turn residues are represented by a blue color. The probability score is scaled between 0-9. Results are also represented in graphical manner and while hovering the mouse over any residue, its status, its position and its probability is displayed in an interactive manner. The results can also be downloaded in a textual format.
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Figure 2. Graphical representation of the results of the Prediction module of BetaTPred3.

Propensity


Propensity module of BetaTPred3 is used to predict the BetaTurns in a protein sequence using the statistical based propensity method. In the figure 3 shown below, a graphical representation is provided on how to use the propensity based module of BetaTPred3. There are 5 different propensity based prediction methods which can be selected by the user. The explaination of these propensities are given in the propensity based prediction webpage. Briefly, Position wise propensities are calculated for all the four residues of a pattern of 4 residues with positions P1, P2, P3 and P4. In Pair wise propensity, the values (at position P1-2, P1-3, P1-4, P2-3, P2-4, P3-4) of all the residue pairs of a pattern is taken. Similarly, in Tri-peptide propensity, values (at position P1-2-3 and P2-3-4) of the pattern are taken. In tetra-peptide propensity, the propensity value of a whole tetrapeptide is taken. Finally, in hybrid method, all the above propensity values are averaged and used for the prediction of betaturns in the protein as explained in the figure 3 below.

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Figure 3. Graphical representaton of the Propensity module of BetaTPred3 showing how to input the protein sequence and submiting it to the BetaTPred3 web-server.

Further, the results of the propensity prediciton module is represented graphically in the figure 4 below. Each protein is represented in four lines. First line displays the ID of the protein. Second line displays the sequence of the protein. Third line displays the prediction result of the propensity module of BetaTPred3 where 'T' represents a turn and 'n' represents a non-turn. For better representation, start of a turn is represented in red color and rest residues of a turn are represented in blue color. Fourth line displays the probability score of the prediction which is scaled between 0 and 9.

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Figure 4. Graphical representation of the results of the propensity module of BetaTPred3.

Design


The Design module of the BetaTPred3 assists the users to induce or break a turn in the input protein sequence thereby designing of betaturns in a protein sequence. The graphical representation of this module is shown in figures given below. This module is divided into 2 parts, Basic method and Advanced method. Basic method provides basic functionality providing simple interface to the users for designing (inducing/breaking) a betaturn in the protein sequence. Figure 5 below shows the graphical image showing how to use this module. Figure 6 shows the results of the basic design module. Further, Figure 7 below shows the graphical image showing how to use Advanced Design module. Figure 8 below shows the results of the advanced design module.

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Figure 5. Graphical representation of the Basic Design module of the BetaTPred3 showing how to input the protein sequence and submitting it to the BetaTPred3 web-server.

The next figure 6 below shows the result of the basic design module. For each pattern of 4 residues, the scaled propensity values at each position (P1, P2, P3 and P4) are given along with their average in the respective columns in a tabular format. Next two columns shows the mutation and its position which is required to either induce a turn at that position or break a turn at that position. To make the visualization clear, red color is given to represent the turns while blue color is given to represent those turns which can be breaked by the mutation given in the 'Break a Betaturn' column.

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Figure 6. Graphical representation of the results of the Basic Design module of the BetaTPred3 showing the inducing and breaking betaturns in an input protein sequence.

The next figure 7 below shows the graphical representation of advanced design module of BetaTPred3 and showing how to use it effectively. A user needs to select Advanced option in the 'Select type of display output', and click on the 'Design Beta Turns' button to proceed further for the designing of betaturns in the protein sequence.

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Figure 7. Graphical representation of the Advanced Design module of the BetaTPred3 showing how to input the protein sequence and submitting it to the BetaTPred3 web-server.

The next figure 8 below shows the graphical representation of the result of the advanced design module of the BetaTPred3. The predicted turns are represented by the red color. The table is made interactively using javascript and provides to save and export the results in variety of file formats like excel, XML, CSV, TSV and HTML format. Further, each pattern can be clicked to further mutate all the residues in that pattern to select the mutation which can break or induce a betaturn in the input peptide sequence.

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Figure 8. Graphical representation of the results of the Advanced Design module of the BetaTPred3.

Turn Type


The turn type module of the BetaTPred3 helps the users to predict 9 different types of turns which are TypeI, TypeII, TypeI', TypeII', TypeIV, TypeVIa1, TypeVIa2, TypeVIb and TypeVIII. Users can select the threshold for each type of turn for the prediction. Optionally, users can give their email address and the results will be send to their e-mail. Figure 9 below shows the graphical representation of the turn type module of BetaTPred3 showing how to use this module.

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Figure 9. Graphical representation of the TurnType module of the BetaTPred3 showing how to input the sequence and submitting the sequence for prediction of different turn types.

The next figure 10 below shows the graphical representation of the result of the TurnType module of BetaTPred3. The starting residue of the turn is represented by red color and the other residues of the turn are represented by blue color.

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Figure 10. Graphical representation of the results of the TurnType module of the BetaTPred3