Predicting protein-protein interactions in the human proteome
Southwestern Medical Center · The University of Texas Southwestern Medical Center · +5 more institutions
Abstract
Protein-protein interactions (PPIs) are essential for biological function. Coevolutionary analysis and deep-learning (DL)-based protein structure prediction have enabled comprehensive PPI identification in bacteria and yeast, but these approaches have had limited success for the more complex human proteome. We overcame this challenge by enhancing the coevolutionary signals with sevenfold-deeper multiple sequence alignments harvested from 30 petabytes of unassembled genomic data and developing a new DL network trained on augmented datasets of domain-domain interactions from 200 million predicted protein structures. We systematically screened 200 million human protein pairs and predicted 17,849 interactions with…
Citation impact
- FWCI
- 32.04
- Percentile
- 100%
- References
- 100
Authors
12- JZJing ZhangCorresponding
Southwestern Medical Center, The University of Texas Southwestern Medical Center
- IRIan R. HumphreysCorresponding
University of Washington
- JPJimin PeiCorresponding
Southwestern Medical Center, The University of Texas Southwestern Medical Center
- JKJune‐Ki Kim
Seoul National University, Yonsei University
- CCChulwon Choi
Seoul National University
Topics & keywords
- Proteome
- Identification (biology)
- Protein function
- Function (biology)
- Human proteome project
- Protein–protein interaction
- Human proteins
- Petabyte