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The advent of AlphaFold2 presents a significant opportunity and also a challenge to predict PPIs in a straightforward way based on monomer structures while controlling bias from protein sequences. In this work, we established Structure and Graph-based Predictions of Protein Interactions (SGPPI), a structure-based DL framework for predicting PPIs, using the graph convolutional network. In particular, SGPPI focused on protein patches on the protein\u2013protein binding interfaces and extracted the structural, geometric and evolutionary features from the residue contact map to predict PPIs. We demonstrated that our model outperforms traditional machine learning methods and state-of-the-art DL-based methods using non-representation-bias benchmark datasets. Moreover, our model trained on human dataset can be reliably transferred to predict yeast PPIs, indicating that SGPPI can capture converging structural features of protein interactions across various species. The implementation of SGPPI is available at https:\/\/github.com\/emerson106\/SGPPI.<\/jats:p>","DOI":"10.1093\/bib\/bbad020","type":"journal-article","created":{"date-parts":[[2023,1,22]],"date-time":"2023-01-22T14:11:07Z","timestamp":1674396667000},"source":"Crossref","is-referenced-by-count":49,"title":["SGPPI: structure-aware prediction of protein\u2013protein interactions in rigorous conditions with graph convolutional network"],"prefix":"10.1093","volume":"24","author":[{"given":"Yan","family":"Huang","sequence":"first","affiliation":[{"name":"China Agricultural University State Key Laboratory of Livestock and Poultry Biotechnology Breeding, College of Biological Sciences, , Beijing 100193 , China"},{"name":"Peking University Department of Biomedical Informatics, Ministry of Education Key Laboratory of Molecular Cardiovascular Sciences, Center for Non-Coding RNA Medicine, School of Basic Medical Sciences, , Beijing 100191 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Wuchty","sequence":"additional","affiliation":[{"name":"University of Miami Department of Computer Science, , Coral Gables, FL 33146 , USA"},{"name":"University of Miami Department of Biology, , Coral Gables, FL 33146 , USA"},{"name":"University of Miami Sylvester Comprehensive Cancer Center, , Miami, FL 33136 , USA"},{"name":"Institute of Data Science and Computing, University of Miami , Coral Gables, FL 33146 , USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuan","family":"Zhou","sequence":"additional","affiliation":[{"name":"Peking University Department of Biomedical Informatics, Ministry of Education Key Laboratory of Molecular Cardiovascular Sciences, Center for Non-Coding RNA Medicine, School of Basic Medical Sciences, , Beijing 100191 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9296-571X","authenticated-orcid":false,"given":"Ziding","family":"Zhang","sequence":"additional","affiliation":[{"name":"China Agricultural University State Key Laboratory of Livestock and Poultry Biotechnology Breeding, College of Biological Sciences, , Beijing 100193 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,1,21]]},"reference":[{"key":"2023032004362275700_","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1038\/s41580-020-0231-2","article-title":"Proteomic and interactomic insights into the molecular basis of cell functional diversity","volume":"21","author":"Bludau","year":"2020","journal-title":"Nat Rev Mol Cell Biol"},{"key":"2023032004362275700_","doi-asserted-by":"crossref","first-page":"4884","DOI":"10.1021\/acs.chemrev.5b00683","article-title":"Predicting protein-protein interactions from 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