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Structurally-informed human interactome reveals proteome-wide perturbations by disease mutations
Dapeng Xiong1,2,3, Yunguang Qiu4, Junfei Zhao5
1Department of Computational Biology, Cornell University, Ithaca, NY 14853, USA.
Biorxiv : the Preprint Server for Biology
|May 10, 2023
Summary
PIONEER, a deep learning tool, accurately predicts protein interaction interfaces and identifies disease-associated mutations. This framework aids in understanding complex diseases and advancing precision medicine by analyzing protein-protein interactions.
Area of Science:
- Genomics and Bioinformatics
- Computational Biology
- Systems Biology
Background:
- Translating human genetic findings to disease pathobiology and therapeutics is challenging.
- Understanding protein-protein interactions (PPIs) is crucial for disease mechanisms.
Conclusions:
- PIONEER provides a powerful deep learning tool for identifying functional consequences of disease-associated alleles.
- The framework facilitates precision medicine by analyzing PPIs at multiscale interactome network levels.
- Structurally-informed interactomes generated by PIONEER are valuable for therapeutic discovery.
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