遇见数据集

A Structure-Guided Kinase–Transcription Factor Interactome Atlas Reveals Docking Landscapes of the Kinome

收藏
Zenodo2025-10-12 更新2026-05-26 收录
官方服务:

资源简介:

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: Supplementary Data 1: The complete human Serine/Threonine kinase–transcription factor interactome, including iLIS scores and predicted residue-level interface data. Supplementary Data 2: The complete set of computationally derived Position Weight Matrices (PWMs) for the human S/T kinase screen. Supplementary Data 3: The complete Drosophila kinome–transcription factor interactome, including iLIS scores and predicted residue-level interface data. Supplementary Data 4: The complete set of computationally derived Position Weight Matrices (PWMs) for the Drosophila kinome screen. 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.

提供机构:
bioRxiv
创建时间:
2025-10-10
二维码
社区交流群
二维码
科研交流群
商业服务