BioPlex (biophysical interactions of ORFeome-based complexes) is an open access resource for studying protein-protein interactions.[1][2][3] It is the result of collaborations between Harvard Medical School and Biogen. BioPlex 1.0 reported 23,744 interactions among 7,668 proteins.[4] BioPlex 2.0 extended those observations to detect over 29,000 new interactions.[5]
The basic technology is to express a "bait" protein in human cells. Those bait proteins interact with other proteins, and then the complexes of the bait and "prey" proteins are isolated by affinity purification. The interacting prey proteins are identified using mass spectrometry.
Use in research
editDetermining the interaction partners of poorly characterized proteins can provide clues to the function of those proteins, and knowing which "protein community" a disease gene resides in can give better context for its action.[5]
See also
editReferences
edit- ^ anon. "BioPlex". harvard.edu. harvard.edu. Retrieved 24 May 2017.
- ^ anon (2015-07-18). "Facebook for the Proteome". technology.org. technology.org. Retrieved 24 May 2017.
- ^ anon. "New study maps protein interactions for a quarter of the human genome". phys.org/. phys.org. Retrieved 24 May 2017.
- ^ Huttlin EL, Ting L, Bruckner RJ, Gebreab F, Gygi MP, Szpyt J, Tam S, Zarraga G, Colby G, Baltier K, Dong R, Guarani V, Vaites LP, Ordureau A, Rad R, Erickson BK, Wühr M, Chick J, Zhai B, Kolippakkam D, Mintseris J, Obar RA, Harris T, Artavanis-Tsakonas S, Sowa ME, De Camilli P, Paulo JA, Harper JW, Gygi SP (2015). "The BioPlex Network: A Systematic Exploration of the Human Interactome". Cell. 162 (2): 425–40. doi:10.1016/j.cell.2015.06.043. PMC 4617211. PMID 26186194.
- ^ a b Huttlin EL, Bruckner RJ, Paulo JA, Cannon JR, Ting L, Baltier K, Colby G, Gebreab F, Gygi MP, Parzen H, Szpyt J, Tam S, Zarraga G, Pontano-Vaites L, Swarup S, White AE, Schweppe DK, Rad R, Erickson BK, Obar RA, Guruharsha KG, Li K, Artavanis-Tsakonas S, Gygi SP, Harper JW (2017). "Architecture of the human interactome defines protein communities and disease networks". Nature. 545 (7655): 505–509. Bibcode:2017Natur.545..505H. doi:10.1038/nature22366. PMC 5531611. PMID 28514442.