A Structure-Guided Kinase–Transcription Factor Interactome Atlas Reveals Docking Landscapes of the Kinome
Authors/Creators
Description
This repository contains the complete supplementary data tables associated with the manuscript, "A Structure-Guided Kinase–Transcription Factor Interactome Atlas Reveals Docking Landscapes of the Kinome" by Kim et al. 2025. The full preprint is available on bioRxiv (DOI: https://doi.org/10.1101/2025.10.10.681672).
The study presents a structure-guided atlas of the human and Drosophila kinome, built by applying a new interface-aware scoring framework (iLIS) to AlphaFold-Multimer predictions to map kinase-transcription factor interactions. This resource provides residue-level structural insight into partner recognition across the kinome.
This repository contains the following data files, along with a README.txt file that describes the content of each file and its columns:
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Supplementary Data 1: The complete human Serine/Threonine kinase–transcription factor interactome, including iLIS scores and predicted residue-level interface data.
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Supplementary Data 2: The complete set of computationally derived Position Weight Matrices (PWMs) for the human S/T kinase screen.
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Supplementary Data 3: The complete Drosophila kinome–transcription factor interactome, including iLIS scores and predicted residue-level interface data.
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Supplementary Data 4: The complete set of computationally derived Position Weight Matrices (PWMs) for the Drosophila kinome screen.
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Supplementary Data 5: A comprehensive catalog of all predicted interaction hotspots for the human and Drosophila kinomes.
- Supplementary Figure 8: Sequence logos displaying the computed position weight matrices (PWMs) for all high-confidence kinase clusters identified in the Drosophila kinome screen, showing enrichment patterns for all 20 amino acids across the ±10 residue window.
Code Availability The Python code for iLIS analysis and benchmarking is publicly available on GitHub: https://github.com/flyark/AFM-LIS
Please refer to the README.txt file for detailed descriptions and the associated manuscript for full methodological details.
Files
Supplementary Figure 8.pdf
Files
(283.6 MB)
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Additional details
Software
- Repository URL
- https://github.com/flyark/AFM-LIS
- Programming language
- Python , Jupyter Notebook