期刊
JOURNAL OF PROTEOME RESEARCH
卷 21, 期 2, 页码 349-359出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.1c00612
关键词
cell surface proteins; extracellular interactome; online database; computational modeling; systems biology
资金
- National Institutes of Health [R01GM120238, R01GM122804]
- Albert Einstein College of Medicine
- Albert Einstein College of Medicine High Performance Computing Center
The interactions between ectodomains of cell surface proteins play important roles in various cellular processes, but little progress has been made in studying these extracellular interactions. In this study, we present an online database called EXCESP, which is based on computational modeling and contains experimentally determined and computationally predicted interactions among type-I transmembrane proteins in humans. The database also includes additional information such as protein expression levels and signaling pathways.
The interactions between ectodomains of cell surface proteins are vital players in many important cellular processes, such as regulating immune responses, coordinating cell differentiation, and shaping neural plasticity. However, while the construction of a large-scale protein interactome has been greatly facilitated by the development of high-throughput experimental techniques, little progress has been made to support the discovery of extracellular interactome for cell surface proteins. Harnessed by the recent advances in computational modeling of protein-protein interactions, here we present a structure-based online database for the extracellular interactome of cell surface proteins in humans, called EXCESP. The database contains both experimentally determined and computationally predicted interactions among all type-I transmembrane proteins in humans. All structural models for these interactions and their binding affinities were further computationally modeled. Moreover, information such as expression levels of each protein in different cell types and its relation to various signaling pathways from other online resources has also been integrated into the database. In summary, the database serves as a valuable addition to the existing online resources for the study of cell surface proteins. It can contribute to the understanding of the functions of cell surface proteins in the era of systems biology.
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