https://github.com/bartongroup/sack1g-analysis

This is a GitHub Repository containing the data and code used for an structural analysis of FAM83G and FAM83G-CK1A 3D models

https://github.com/bartongroup/sack1g-analysis

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Repository

This is a GitHub Repository containing the data and code used for an structural analysis of FAM83G and FAM83G-CK1A 3D models

Basic Info
  • Host: GitHub
  • Owner: bartongroup
  • Language: Jupyter Notebook
  • Default Branch: master
  • Size: 122 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created 11 months ago · Last pushed 8 months ago
Metadata Files
Readme

README.md

Mutations in fragment site of SACK1G abolish interaction with CK1α

This repository includes the code and results of the computational analysis of our pre-print "Mutations within the predicted fragment-binding region of FAM83G/SACK1G abolish its interaction with the Ser/Thr kinase CK1α", which can be found here.

DOI

Directories

Within the AFDB_FAM83B_model and AFDB_FAM83G_model directories, the AlphaFold DB models for human SACK1B (Q5T0W9) and SACK1G (A6ND36) can be found, respectively.

The FAM83B_FRAGSYS directory includes the necessary data from the FRAGSYS [1] analysis of FAM83B/SACK1B, which was employed to hightlight the most likely sites to affect SACK1B function as well as the individual residues within them.

The FAM83G_SS_prediction_JPRED directory include JPred [2] secondary structure predictions for FAM83G/SACK1G employed to complement secondary structure assignments from the AlphaFold [3]three-dimensional structure models.

The FAM83_dimers directory includes the 3D structure models obtained in this work using the Colabfold v1.5.2 [4] implementation of AlphaFold Multimer v3 [5].

Finally, the notebooks directory includes the two Jupyter notebooks employed to carry out the computational analysis described in our manuscript.

Dependencies

References

  1. Utgés, J.S., MacGowan, S.A., Ives, C.M. et al. Classification of likely functional class for ligand binding sites identified from fragment screening. Commun. Biol. 7, 320 (2024). https://doi.org/10.1038/s42003-024-05970-8
  2. Alexey Drozdetskiy, Christian Cole, James Procter, Geoffrey J. Barton, JPred4: a protein secondary structure prediction server, Nucleic Acids Res., Volume 43, Issue W1, 1 July 2015, Pages W389–W394, https://doi.org/10.1093/nar/gkv332
  3. Jumper, J., Evans, R., Pritzel, A. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021). https://doi.org/10.1038/s41586-021-03819-2
  4. Mirdita, M., Schütze, K., Moriwaki, Y. et al. ColabFold: making protein folding accessible to all. Nat. Methods 19, 679–682 (2022). https://doi.org/10.1038/s41592-022-01488-1
  5. Abramson, J., Adler, J., Dunger, J. et al. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493–500 (2024). https://doi.org/10.1038/s41586-024-07487-w

Owner

  • Name: Geoff Barton's Computational Biology Group
  • Login: bartongroup
  • Kind: organization
  • Location: Dundee, Scotland, UK

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