Article Synopsis
- Protein-protein interactions are essential for biological functions, yet many eukaryotic protein complex structures remain unknown, highlighting the need for better identification methods.
- Using advanced techniques like coevolution analysis and deep-learning models (RoseTTAFold and AlphaFold), researchers screened 8.3 million yeast protein pairs to predict interactions and construct structural models.
- They identified 1505 potential interacting pairs, characterized 106 previously unknown protein assemblies, and provided insights into 806 complexes not structurally documented, emphasizing their importance in key cellular processes.
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Article Abstract
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coevolution analysis and deep-learning–based structure modeling to systematically identify and build accurate models of core eukaryotic protein complexes within the proteome. We use a combination of RoseTTAFold and AlphaFold to screen through paired multiple sequence alignments for 8.3 million pairs of yeast proteins, identify 1505 likely to interact, and build structure models for 106 previously unidentified assemblies and 806 that have not been structurally characterized. These complexes, which have as many as five subunits, play roles in almost all key processes in eukaryotic cells and provide broad insights into biological function.
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Source |
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612107 | PMC |
| http://dx.doi.org/10.1126/science.abm4805 | DOI Listing |