SUMMARY Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally-related proteins. Finally, BioPlex, in combination with other approaches can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial Amyotrophic Lateral Sclerosis perturb a defined community of interactors.

Fewer than half of all tandem mass spectrometry (MS/MS) spectra acquired in shotgun proteomics experiments are typically matched to a peptide with high confidence. Here we determine the identity of unassigned peptides using an ultra-tolerant Sequest database search that allows peptide matching even with modifications of unknown masses up to ±500 Da. In a proteome-wide dataset on HEK293 cells (9,513 proteins and 396,736 peptides), this approach matched an additional 184,000 modified peptides, which were linked to biological and chemical modifications representing 523 distinct mass bins, including phosphorylation, glycosylation, and methylation. We localized all unknown modification masses to specific regions within a peptide. Known modifications were assigned to the correct amino acids with frequencies often >90%. We conclude that at least one third of unassigned spectra arise from peptides with substoichiometric modifications.

We report a comprehensive and quantitative analysis of the mouse liver and plasma proteomes. The method used is based on extensive fractionation of intact proteins, further separation of proteins based on their abundance and size, and high-accuracy mass spectrometry. This analysis reached a depth in proteomic profiling not reported to date for a mammalian tissue or a biological fluid, with 7099 and 4727 proteins identified with high confidence in the liver and in the corresponding plasma, respectively. This method allowed for the identification in both compartments of low-abundance proteins such as cytokines, chemokines, and receptors and for the detection in plasma of proteins in the pg/mL concentration range. This method also allowed for semiquantitation of all identified proteins. The calculated abundance scores correlated with the abundance of the corresponding transcripts for the large majority of the proteins identified in the liver. Finally, comparison of the liver and plasma datasets demonstrated that a significant number of proteins identified in the liver can be detected in plasma. These included proteins involved in complement and coagulation, in fatty acid, purine and pyruvate metabolism, in gluconeogenesis and glycolysis, in protein ubiquitination, and in insulin, interleukin-4, epidermal growth factor, and platelet-derived growth factor signaling. Conclusion: This in-depth analysis of the mouse liver and corresponding plasma proteomes provides a strong basis for investigations of liver pathobiology and biology that employ mouse models of hepatic diseases in an effort to better understand, diagnose, treat, and prevent human hepatic diseases. (HEPATOLOGY 2008;47: 1043-1051.)

Physico-chemical properties of amino acids can be used to study protein sequence profiles, folding and function. We collated 242 properties for the 20 naturally occurring amino acids and created a dataset. The dataset is available as a database named APDbase( Amino acid Physico-chemical properties Data base). The database can be queried using either key words describing physico-chemical properties or pre-assigned database index number. The database contains corresponding references for each property value and facilitates deposition of new property values for processing and inclusion in the database.AvailabilityThe database is available for free at http://www.rfdn.org/bioinfo/APDbase.php