Blobulator logo: Brannigan Lab - Rutgers University - Camden

Welcome to the Blobulator

Blobulation is an approach for edge-detection in protein sequences based on contiguous hydrophobicity, originally developed by the Brannigan Lab for a specific long intrinsically disordered protein (the prodomain of BDNF). The blobulator allows the user to blobulate any sequence, and visualize the results while adjusting the two blobulation parameters to detect more edges for higher-resolution ("zooming-in") or detect fewer edges for a more tractable visualization ("zooming-out").

A stretch of residues between two edges are called blobs, inspired by the terminology in polymer physics. The blobulator also characterizes each blob based on several collective properties of the blob residues, including hydrophobicity, net charge, globular tendency (Das-Pappu phase), distance from the Uversky boundary, and sensitivity to mutation. These properties are also dynamically adjusted as the user increases or decreases resolution of the sequence. For human proteins, users will also see the location of disease-associated single nucleotide polymorphisms (SNPs).

For bug reports, feature requests, or anything else please contact at connor.pitman@rutgers.edu or grace.brannigan@rutgers.edu.


Citing the Blobulator

A manuscript on the Blobulator is currently in preparation. For now, please cite analysis done with Blobulator using: Lohia R, Hansen M, Brannigan G, “Contiguously hydrophobic sequences are functionally significant throughout the human exome.” PNAS. 2022. doi: 10.1073

Sequence Input

The first thing needed for the blobulator is either a Uniprot ID for a protein of interest, or a manual sequence entry. Uniprot IDs are our recommended format for retrieving the sequence required for blobulation. Above each “compute button” there is a manual text entry box, in which the you insert either your sequence or ID. Then press the “Compute” button.

Visualization

On the blobulation output page, there are three adjustable parameters:

Blobulation considers the residues in turn and calculates the average hydrophobicity score of each group of residues. If a group of residues (under the minimum blob size) is above the value for hydrophobicity cutoff, it will be considered a ‘h’ (hydrophobic) blob. If it’s below it will be considered a ‘p’ (non-hydrophobic) blob. The hydropathy cutoff can be adjusted by manual entry into the text box to the left, or by adjusting the slider to the desired value.

This setting establishes a threshold for how many residues constitute blob. If there are groups of residues which average above or below the hydropathy cutoff, they must then meet this requirement to be considered either a h or p blob. If a residue in a h-blob is below this threshold and below the hydropathy cutoff, or if the residue is in a p-blob and above the hydropathy cutoff and below the minimum blob size, the residue (or group of residues) will be considered a ‘s’ (spacer or separator) blob.

This option is used to change a residue within the sequence, and see what potential affects it would have on the blobulation output. To mutate a residue, check the 'Mutate Residue' box on the left, then select which residue you would like to mutate, and then choose the amino acid they would like to mutate the residue into. The graphs will automatically update after the box is checked and the changes are made.



SNPs and Mutations

SNPs are shown by the black triangles below the relevant residues on many of the visualizations.



Interpreting Plots

After blobulation, multiple visualizations are produced.

This plot shows the smoothed hydropathy per residue. The core of blobulation consists of two parameters - the first of which being a hydropathy threshold. This threshold is shown by the blue line on the “mean hydropathy” axis. This line shows the threshold which determines the boundaries of the h and p blobs. This graph is the only one that shows the residues individually, and can be used as a reference to how the residues are grouped together based upon their position above or below the mean hydropathy line. Any stretch of 'minimum blob size' or more residues with mean hydropathy > 'hydropathy cutoff' is classified as a hydrophobic or “h” blob and any remaining stretch of four or more residues is classified as a non-hydrophobic linker or “p” blob. Beneath this first plot are several additional plots. Open the tooltip associated with each to get more information about the plots. In all cases, the height of the bars indicates h or p blobs established by the data presented here.

This second outputted visualizaton shows the blobs according to their globular tendency, considered based upon their Das-Pappu classification. The Das-Pappu phase diagram provides a means to estimate how a disordered sequence might behave based on the charge content. Each blob is colored according to the region they fall in Das-Pappu phase diagram. Specifically, these are: globular, janus/boundary, strong polyelectrolyte, strong polyanion, and strong polycation. The height of each bar corresponds to their identity of either a "p" "h" or "s" blob.

This third outputted visualization shows the blobs according to their residues’ collective average charge. Each blob is evaluated based on its fraction of both positively and negatively charged residues. The darker blue a blob is shown here, the higher the fraction of positively charged residues are present within the blob. Alternatively, the darker red a blob is shown here, the higher the fraction of negatively charged residues are present within the blob. An even fraction of positive or negative, or a low fraction of any charged residues, results in a grey color.

This fourth outputted visualization shows the blobs according to their positions on the Uversky diagram , where the line between ordered and disordered is plotted. Calculated negative values (represented in orange) are ordered and positive values (shown in blue) are disordered and plotted.

This fifth outputted visualization shows the blobs according to their enrichment in documented disease associated SNPs (dSNP). This idea was investigated in the context of aggregating and non-aggregating proteins at various blob lengths and hydrophobicity cutoffs a , from which the figure below is presented (Lohia, et al).

This sixth and final outputted visualization shows the blobs according to their fraction of disordered residue, which utilizes the Database of Disordered protein prediction . This disorder calculation is only available if the user uses the Uniprot ID.

Saving Data

After the “Download data!” button (located just below the three adjustable parameters) is pressed, the raw data will be downloaded in the form of a csv file. The data stored here is by residue. Each column corresponds to one of the following: residue name, residue number, window, hydropathy cutoff, minimum blob size, average hydrophobicity, blob type, blob index number, blob Das-Pappu classification, blob net charge per residue, fraction of positively charged residues, fraction of negatively charged residues, fraction of charged residues, uversky diagram score, blob dSNP enrichment, and blob disorder score.

Frequently Asked Questions:

The nomenclature used here comes from polymer physics (Pincus, 1976; de Gennes, 1979): a blob is a group of sequential monomers in a polymer chain that "clump" with a characteristic length. For more information see Scaling Concepts in Polymer Physics by Pierre-Gilles de Gennes.

Blobs here are determined by defining regions of contiguously hydrophobic residues, and the regions of non-hydrophobic residues that span between. A blob is a contiguous stretch of either hydrophobic or non-hydrophobic residues greater than a certain length.

While many softwares exist that consider charge, disorder, or conformational states of proteins, the blobulator considers hydrophobicity and its role in the determination of regions of a protein. This has been shown already to be a powerful tool for analysis of different domains of the BDNF protein , the research within which this tool was developed. Additionally, a recent publication has demonstrated other contexts in which the blobulator has proven useful, particularly with regard to disease associated snps.

The blobulator outputs 6 graphs showing categorizations of its subdomains. Each graph shows the sequence of the protein displayed in one of the following ways: smoothed hydropathy per residue, colored according to globular tendency, colored according to net charge per residue, colored according to the Uversky diagram, colored according to dSNP enrichment, colored according to fraction of disordered residue.

We strongly recommend using the Uniprot ID option when available. There will be more graphs outputted, as well as SNP data available if you blobulate the protein using its Uniprot ID. If you are interested in a specific variant of the protein, such as one containing a SNP, there is a mutate residue option at the top of the output page.

For smaller proteins, we expect blobulation to take seconds. For very large proteins, the blobulator may take over a minute to produce a result.

To zoom in, hover your mouse over the plot you're interested in and click and drag around the area you wish to zoom in on. To revert the plot back to it's original zoomed-out state, double click on the plot.

These letters represent amino acids. Clicking a letter will set the hydropathy cutoff to the hydrophobicity of the selected amino acid for the chosen scale.

Yes! We recommend saving the page as a .pdf file using the “print” function in your browser.

The data can be downloaded using the “Download data!” button at the top of the blobulator output page. The downloaded data will be in the form of the csv file with labeled columns, which can be used to generate custom graphs or retrieve specific values.

Yes. Any adjustments made after blobulation but before the “Download data!” button is clicked will be reflected in the csv file.

It is possible that you chose the manual sequence entry option, for which there will be no SNP data, or that there is no data in EMBL-EBI for your protein of interest. It is also possible that you are not blobulating a human protein. In any of these cases, it doesn’t necessarily mean that no SNP data exists for the protein you are blobulating.

Check and make sure you chose the Uniprot ID input option.

Please contact us and let us know what you’re thinking. Our goal is to maximize the blobulator’s usefulness, and any suggestions are greatly appreciated. In the meantime, the local version of the blobulator, which can be found on our github, can be modified to your liking.

Yes! It can be found on our github.

We recommend using our back end code found on our github. If you think a specific feature would be generally useful, please email us at connor.pitman@rutgers.edu or grace.brannigan@rutgers.edu.

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