Blobulator logo: Brannigan Lab - Rutgers University - Camden

Warning: the blobulator is best viewed on a computer or tablet, not a smart phone.



New here? Welcome! For more information about the blobulator, visit the About and FAQ tabs above. When you're ready to blobulate a protein, select an input method below.

Select an input method:


Enter an ID for your protein.

Note: only human proteins will display disease-associated mutations, and will take longer to load.

Welcome to the Blobulator

Blobulation is an approach for detecting hydrophobic modularity in protein sequences based on contiguous hydrophobicity, originally developed by the Brannigan Lab for aiding in analyzing residue contacts in molecular dynamics (MD) simulations of a long intrinsically disordered protein (the BDNF prodomain). The blobulator allows the user to blobulate any sequence, and visualize the results while adjusting the two tunable parameters to detect blobs found at varying resolutions.

The figure above shows an overview of the blobulation algorithm. It consists of two steps - digitization and clustering. In the digitization step, residues are classified as either hydrophobic (blue) or non-hydrophobic (orange) by comparing their hydropathy to the user-selected threshold, H*. Next, the sequence is segmented: all segments containing only hydrophobic residues longer than Lmin are h-blobs (blue), other segments longer than Lmin are p-blobs (orange), and segments shorter than Lmin and non-hydrophobic are s-blobs (green). Figure adapted from Lohia et al. 2022.

In addition to outputting a visualization of the blobulated sequence, the blobulator also outputs several tracks showing blobs overlaid with additional information including: 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 known 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, or post an issue on our GitHub.


Citing the Blobulator

When citing the Blobulator, please reference: Connor Pitman, Ezry Santiago-McRae, Ruchi Lohia, Kaitlin Bassi, Thomas T. Joseph, Matthew E.B. Hansen, Grace Brannigan, “The blobulator: a webtool for identification and visual exploration of hydrophobic modularity in protein sequences.” JCIM. 2026.

Sequence Input

The first thing needed to use 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.

Tunable Items on the Results Page

The default scale used for the initial blobulation is the Kyte Doolittle hydropathy scale, but other scales can be selected from the dropdown menu. Changing the scale will update the clickable amino acid letters above the hydropathy cutoff slider.

The first step of blobulation is digitization. The algorithm first calculates each residue's hydrophobicity on the selected scale and then smooths this over the hydrophobicity of the adjacent residues. Residues are then digitized to hydrophobic or non-hydrophobic based on their smoothed hydropathy's relation to the hydropathy cutoff (shown as grey bars in the first track). This cutoff (shown as a blue line in the first track) can be adjusted by manual entry into the text box to the left, by adjusting the slider to the desired value, or by clicking a residue letter (found above the slider) to set the cutoff to a given amino acid's hydrophobicity on the selected scale.

This setting establishes a threshold for how many residues constitute blob. If a group of contiguous residues over the minimum blob size individually have smoothed hydrophobicities above the value for hydrophobicity cutoff, the cluster will be considered a ‘h’ (hydrophobic) blob. If not, a group will be considered a ‘p’ (non-hydrophobic) blob if the length is above the minimum blob size, or an 's' (short) blob if the length is below the minimum blob size. 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 option is used to change a residue within the sequence, and see what potential effects it would have on the blobulation output. To mutate a residue, select which residue you would like to mutate, choose the amino acid you would like to mutate the residue into, and click the checkbox. Additionally, known disease-associated mutations are shown by black triangles below all tracks if ID Entry is used. Hovering over these mutations will display the amino acid change caused by them, as well as a clickable reference SNP cluster ID.

Parameters

To view blobs in 3D on the blobulator webtool, use either ID entry (for the alpha fold structure) or upload a PDB using PDB entry when selecting an input method. Additionally, a VMD plugin is available to download via the bloblator github repository to blobulate and view blobs on a structure in VMD.



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 being a hydropathy threshold. This threshold is shown by the blue line on the “mean hydropathy” axis. This line shows the hydropathy threshold (shown by a blue line), which determines the boundaries of the h and p blobs. Note that 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 blue line. If a group of contiguous residues over the minimum blob size individually have smoothed hydrophobicities above the value for hydrophobicity cutoff, the cluster will be considered a ‘h’ (hydrophobic) blob. If not, a group will be considered a ‘p’ (non-hydrophobic) blob if the length is above the minimum blob size, or an 's' (short) blob if the length is below the minimum blob size.

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 negatively charged residues, or a low fraction of any charged residues results in a grey color.

This fourth outputted visualization shows the blobs colored according to their globular tendency based on their Das-Pappu classification. The Das-Pappu phase diagram was originally used 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 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 in our recent publication, from which the figure below is presented (Lohia, et al 2022).

This sixth 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 more ordered and positive values (shown in blue) are more disordered.

This seventh and final outputted visualization shows the blobs according to their predicted fraction of disordered residues, 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 used to generate the tracks will be downloaded in the form of a csv file. The columns correspond to:

  • Residue_Position: Position of the residue in the protein sequence (1-based indexing).
  • Residue: One-letter amino acid code for the residue.
  • Window_Length: Length of the rolling window used to smooth hydropathy values (currently fixed at 3).
  • Hydropathy_Cutoff: Normalized hydropathy threshold (0–1) used to categorize residues as hydrophobic or non-hydrophobic.
  • Minimum_Blob_Length: Minimum number of residues required to be classified as an h- or p-blob.
  • Blob_Length: Length (in residues) of the blob to which this residue belongs.
  • Normalized_Mean_Blob_Hydropathy: Mean hydropathy of the blob, normalized to the selected hydropathy scale.
  • Minimum_Blob_Hydropathy: The lowest smoothed hydropathy value observed within a given blob.
  • Blob_Type: The type of blob containing this residue (h = hydrophobic, p = polar/hydrophilic, s = short hydrophilic).
  • Blob_Name: Name of the blob containing this residue. Consists of the blob type (h, s, or p), the group number (1, 2, 3, etc.), and a letter showing the order of the blob in that group (a, b, c, etc.).
  • Blob_Das-Pappu_Class: Das–Pappu Phase for the containing blob. 1 = Globular, 2 = Janus/boundary, 3 = Polar, 4 = Polycation, 5 = Polyanion. See https://www.pnas.org/doi/10.1073/pnas.1304749110.
  • Blob_NCPR: Net charge per residue of the blob. Equal to the total number of positively charged residues minus the total number of negatively charged residues, divided by the length of the blob.
  • Fraction_of_Positively_Charged_Residues: The ratio of the number of positively charged residues to the length of the blob.
  • Fraction_of_Negatively_Charged_Residues: The ratio of the number of negatively charged residues to the length of the blob.
  • Fraction_of_Charged_Residues: Equal to the total number of positively charged residues plus the total number of negatively charged residues, divided by the length of the blob.
  • Uversky_Diagram_Score: Distance from the Uversky–Gillespie–Fink order/disorder boundary line. See https://pubmed.ncbi.nlm.nih.gov/11025552/.
  • dSNP_Enrichment: Predicted enrichment of disease-causing SNPs. See https://www.pnas.org/doi/10.1073/pnas.2116267119.
  • Blob_Disorder_Score: Mean expected disorder score as provided by D2P2. See https://doi.org/10.1093/nar/gks1226.
  • Normalized_Hydropathy: Hydropathy value of the residue on the selected scale.
  • Smoothed_Hydropathy: Normalized hydropathy smoothed over the window length.

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 clusters of contiguously hydrophobic residues, and the non-hydrophobic residues that span between them. A blob is a contiguous stretch of either hydrophobic or non-hydrophobic residues greater than (or below) a certain length.

While many analyses 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, our recent publication has demonstrated other contexts in which the blobulator has proven useful, particularly with regard to disease-associated SNPs.

The blobulator outputs 6 tracks showing blobs overlaid with additional information. 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.

Yes! We have two ways: either via the ID entry (alphafold) or PDB entry (provided PDB file), or using the VMD plugin (source code found in the blobulator github repository).

We strongly recommend using the ID entry 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. If there's a specific structure you'd like to view in the molecular viewer, use the PDB entry option.

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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