Skip to content
This repository has been archived by the owner. It is now read-only.
Generates a single figure that combines ConSurf, PSIPRED, DISOPRED and PFAM data.
Branch: master
Clone or download
Pull request Compare This branch is 1 commit ahead of avibpatel:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.


Generates a single figure that combines ConSurf, PSIPRED, DISOPRED and PFAM data.

This code is associated with the paper from Patel et al., "Architecture of the chromatin remodeler RSC and insights into its nucleosome engagement". eLife, 2019.

An example of files needed and resulting outputs are provided in the TBP directory.

Image of Demo


Example for human TBP (TATA-box binding protein)

Step 1:

  • Make a folder on your computer to compile and run
  • Download and copy it into your new folder

Step 2:

Step 3:

Use the downloaded fasta sequence run:

  • ConSurf (

    • [Select: Amino-Acids, NO, NO, automatically]
    • [Input: Protein seqence (MDQNN....), Job title (TBP), User E-Mail (]
    • Download: Amino Acid Conservation Scores, Confidence Intervals and Conservation Colors and save at TBP.grades
  • PSIPRED 4.0 and DISOPRED3 (

    • [Select: PSIPRED 4.0 and DISOPRED3]
    • [Input: Protein seqence (MDQNN....), Job title (TBP), User E-Mail (]
    • Download: SS2 Format Output and COMB NN Output files and rename as TBP.ss2 and TBP.comb respectively
  • PFAM (

    • [Input: Seqence (MDQNN....)}
    • Copy output table: Significant Pfam-A Matches and save as a text file called TBP.txt
    • Optional: Modify the PFAM file to custom define domains
      • First column defines domain name and columns 5 and 6 define the limits of that domain.

Step 4:

  • Fragments (Optional: If you want to mark modeled regions)

    • Create a file named TBP_fragements.txt
    • List regions you have modeled: 155-333 (from PDB 1CDW)
      • IF you have multiple fragment add other regions in another lines
  • Run

    • Open a terminal and navigate your directory that contains all of the downloaded files
      • You should have the following files: TBP.seq, TBP.grades, TBP.ss2, TBP.comb, TBP.txt, TBP_fragemnts.txt
      • All files should havre the same name. You will provide this name (TBP in this case) to
    • Run

C:\Users\Github_demo\TBP> py .\

What is the name of the protein: TBP

What color do you want the protein to be: red

  • The there should be 3 new files in your directory: TBP.pdf, TBP.svg and TBP_seq.svg
    • All files are editable in illustrator or vector art programs.
    • TBP.pdf is the smallest and easiiest file to work with if you do not plan on editing the figure
    • TBP.svg is more easily editable version of TBP.pdf
    • TBP_seq.svg contains the sequence of TBP embeded into the figure. This can be useful for model building... or showing a zoomed in view of a specific part of your protein.


You can’t perform that action at this time.