Protein complex

A protein complex or multiprotein complex is a group of two or more associated polypeptide chains. Protein complexes are distinct from multienzyme complexes, in which multiple catalytic domains are found in a single polypeptide chain.[1]

Kinesin is a protein complex functioning as a molecular biological machine. It uses protein domain dynamics on nanoscales

Protein complexes are a form of quaternary structure. Proteins in a protein complex are linked by non-covalent protein–protein interactions. These complexes are a cornerstone of many (if not most) biological processes. The cell is seen to be composed of modular supramolecular complexes, each of which performs an independent, discrete biological function.[2]

Through proximity, the speed and selectivity of binding interactions between enzymatic complex and substrates can be vastly improved, leading to higher cellular efficiency. Many of the techniques used to enter cells and isolate proteins are inherently disruptive to such large complexes, complicating the task of determining the components of a complex.

Examples of protein complexes include the proteasome for molecular degradation and most RNA polymerases. In stable complexes, large hydrophobic interfaces between proteins typically bury surface areas larger than 2500 square Ås.[3]


The Bacillus amyloliquefaciens ribonuclease barnase (colored) and its inhibitor (blue) in a complex

Protein complex formation can activate or inhibit one or more of the complex members and in this way, protein complex formation can be similar to phosphorylation. Individual proteins can participate in a variety of protein complexes. Different complexes perform different functions, and the same complex can perform multiple functions depending on various factors. Factors include:

  • Cell compartment location
  • Cell cycle stage
  • Cell nutritional status

Many protein complexes are well understood, particularly in the model organism Saccharomyces cerevisiae (yeast). For this relatively simple organism, the study of protein complexes is now genome wide and the elucidation of most of its protein complexes is ongoing. In 2021, researchers used deep learning software RoseTTAFold along with AlphaFold to solve the structures of 712 eukaryote complexes. They compared 6000 yeast proteins to those from 2026 other fungi and 4325 other eukaryotes.[4]

Types of protein complexes

Obligate vs non-obligate protein complex

If a protein can form a stable well-folded structure on its own (without any other associated protein) in vivo, then the complexes formed by such proteins are termed "non-obligate protein complexes". However, some proteins can't be found to create a stable well-folded structure alone, but can be found as a part of a protein complex which stabilizes the constituent proteins. Such protein complexes are called "obligate protein complexes".[5]

Transient vs permanent/stable protein complex

Transient protein complexes form and break down transiently in vivo, whereas permanent complexes have a relatively long half-life. Typically, the obligate interactions (protein–protein interactions in an obligate complex) are permanent, whereas non-obligate interactions have been found to be either permanent or transient.[5] Note that there is no clear distinction between obligate and non-obligate interaction, rather there exist a continuum between them which depends on various conditions e.g. pH, protein concentration etc.[6] However, there are important distinctions between the properties of transient and permanent/stable interactions: stable interactions are highly conserved but transient interactions are far less conserved, interacting proteins on the two sides of a stable interaction have more tendency of being co-expressed than those of a transient interaction (in fact, co-expression probability between two transiently interacting proteins is not higher than two random proteins), and transient interactions are much less co-localized than stable interactions.[7] Though, transient by nature, transient interactions are very important for cell biology: the human interactome is enriched in such interactions, these interactions are the dominating players of gene regulation and signal transduction, and proteins with intrinsically disordered regions (IDR: regions in protein that show dynamic inter-converting structures in the native state) are found to be enriched in transient regulatory and signaling interactions.[5]

Fuzzy complex

Fuzzy protein complexes have more than one structural form or dynamic structural disorder in the bound state.[8] This means that proteins may not fold completely in either transient or permanent complexes. Consequently, specific complexes can have ambiguous interactions, which vary according to the environmental signals. Hence different ensemble of structures result in different (even opposite) biological functions.[9] Post-translational modifications, protein interactions or alternative splicing modulate the conformational ensembles of fuzzy complexes, to fine-tune affinity or specificity of interactions. These mechanisms are often used for regulation within the eukaryotic transcription machinery.[10]

Essential proteins in protein complexes

Essential proteins in yeast complexes occur much less randomly than expected by chance. Modified after Ryan et al. 2013[11]

Although some early studies[12] suggested a strong correlation between essentiality and protein interaction degree (the “centrality-lethality” rule) subsequent analyses have shown that this correlation is weak for binary or transient interactions (e.g., yeast two-hybrid).[13][14] However, the correlation is robust for networks of stable co-complex interactions. In fact, a disproportionate number of essential genes belong to protein complexes.[15] This led to the conclusion that essentiality is a property of molecular machines (i.e. complexes) rather than individual components.[15] Wang et al. (2009) noted that larger protein complexes are more likely to be essential, explaining why essential genes are more likely to have high co-complex interaction degree.[16] Ryan et al. (2013) referred to the observation that entire complexes appear essential as "modular essentiality".[11] These authors also showed that complexes tend to be composed of either essential or non-essential proteins rather than showing a random distribution (see Figure). However, this not an all or nothing phenomenon: only about 26% (105/401) of yeast complexes consist of solely essential or solely nonessential subunits.[11]

In humans, genes whose protein products belong to the same complex are more likely to result in the same disease phenotype.[17][18][19]

Homomultimeric and heteromultimeric proteins

The subunits of a multimeric protein may be identical as in a homomultimeric (homooligomeric) protein or different as in a heteromultimeric protein. Many soluble and membrane proteins form homomultimeric complexes in a cell, majority of proteins in the Protein Data Bank are homomultimeric.[20] Homooligomers are responsible for the diversity and specificity of many pathways, may mediate and regulate gene expression, activity of enzymes, ion channels, receptors, and cell adhesion processes.

The voltage-gated potassium channels in the plasma membrane of a neuron are heteromultimeric proteins composed of four of forty known alpha subunits. Subunits must be of the same subfamily to form the multimeric protein channel. The tertiary structure of the channel allows ions to flow through the hydrophobic plasma membrane. Connexons are an example of a homomultimeric protein composed of six identical connexins. A cluster of connexons forms the gap-junction in two neurons that transmit signals through an electrical synapse.

Intragenic complementation

When multiple copies of a polypeptide encoded by a gene form a complex, this protein structure is referred to as a multimer. When a multimer is formed from polypeptides produced by two different mutant alleles of a particular gene, the mixed multimer may exhibit greater functional activity than the unmixed multimers formed by each of the mutants alone. In such a case, the phenomenon is referred to as intragenic complementation (also called inter-allelic complementation). Intragenic complementation has been demonstrated in many different genes in a variety of organisms including the fungi Neurospora crassa, Saccharomyces cerevisiae and Schizosaccharomyces pombe; the bacterium Salmonella typhimurium; the virus bacteriophage T4,[21] an RNA virus[22] and humans.[23] In such studies, numerous mutations defective in the same gene were often isolated and mapped in a linear order on the basis of recombination frequencies to form a genetic map of the gene. Separately, the mutants were tested in pairwise combinations to measure complementation. An analysis of the results from such studies led to the conclusion that intragenic complementation, in general, arises from the interaction of differently defective polypeptide monomers to form a multimer.[24] Genes that encode multimer-forming polypeptides appear to be common. One interpretation of the data is that polypeptide monomers are often aligned in the multimer in such a way that mutant polypeptides defective at nearby sites in the genetic map tend to form a mixed multimer that functions poorly, whereas mutant polypeptides defective at distant sites tend to form a mixed multimer that functions more effectively. The intermolecular forces likely responsible for self-recognition and multimer formation were discussed by Jehle.[25]

Structure determination

The molecular structure of protein complexes can be determined by experimental techniques such as X-ray crystallography, Single particle analysis or nuclear magnetic resonance. Increasingly the theoretical option of protein–protein docking is also becoming available. One method that is commonly used for identifying the meomplexes is immunoprecipitation. Recently, Raicu and coworkers developed a method to determine the quaternary structure of protein complexes in living cells. This method is based on the determination of pixel-level Förster resonance energy transfer (FRET) efficiency in conjunction with spectrally resolved two-photon microscope. The distribution of FRET efficiencies are simulated against different models to get the geometry and stoichiometry of the complexes.[26]


Proper assembly of multiprotein complexes is important, since misassembly can lead to disastrous consequences.[27] In order to study pathway assembly, researchers look at intermediate steps in the pathway. One such technique that allows one to do that is electrospray mass spectrometry, which can identify different intermediate states simultaneously. This has led to the discovery that most complexes follow an ordered assembly pathway.[28] In the cases where disordered assembly is possible, the change from an ordered to a disordered state leads to a transition from function to dysfunction of the complex, since disordered assembly leads to aggregation.[29]

The structure of proteins play a role in how the multiprotein complex assembles. The interfaces between proteins can be used to predict assembly pathways.[28] The intrinsic flexibility of proteins also plays a role: more flexible proteins allow for a greater surface area available for interaction.[30]

While assembly is a different process from disassembly, the two are reversible in both homomeric and heteromeric complexes. Thus, the overall process can be referred to as (dis)assembly.

Evolutionary significance of multiprotein complex assembly

In homomultimeric complexes, the homomeric proteins assemble in a way that mimics evolution. That is, an intermediate in the assembly process is present in the complex's evolutionary history.[31] The opposite phenomenon is observed in heteromultimeric complexes, where gene fusion occurs in a manner that preserves the original assembly pathway.[28]

See also


  1. Price NC, Stevens L (1999). Fundamentals of Enzymology: The Cell and Molecular Biology of Catalytic Proteins (3rd ed.). Oxford: Oxford University Press. ISBN 0-19-850229-X.
  2. Hartwell LH, Hopfield JJ, Leibler S, Murray AW (December 1999). "From molecular to modular cell biology". Nature. 402 (6761 Suppl): C47–52. doi:10.1038/35011540. PMID 10591225.
  3. Pereira-Leal JB, Levy ED, Teichmann SA (March 2006). "The origins and evolution of functional modules: lessons from protein complexes". Philos. Trans. R. Soc. Lond. B Biol. Sci. 361 (1467): 507–17. doi:10.1098/rstb.2005.1807. PMC 1609335. PMID 16524839.
  4. "AI cracks the code of protein complexes—providing a road map for new drug targets". Retrieved 2021-11-14.
  5. Amoutzias G, Van de Peer Y (2010). "Single-Gene and Whole-Genome Duplications and the Evolution of Protein–Protein Interaction Networks. Evolutionary genomics and systems biology". In Caetano-Anolles G (ed.). Evolutionary Genomics. pp. 413–429. doi:10.1002/9780470570418.ch19.
  6. Nooren IM, Thornton JM (July 2003). "Diversity of protein interactions". EMBO J. 22 (14): 3486–92. doi:10.1093/emboj/cdg359. PMC 165629. PMID 12853464.
  7. Brown KR, Jurisica I (2007). "Unequal evolutionary conservation of human protein interactions in interologous networks". Genome Biol. 8 (5): R95. doi:10.1186/gb-2007-8-5-r95. PMC 1929159. PMID 17535438.
  8. Tompa P, Fuxreiter M (January 2008). "Fuzzy complexes: polymorphism and structural disorder in protein-protein interactions". Trends Biochem. Sci. 33 (1): 2–8. doi:10.1016/j.tibs.2007.10.003. PMID 18054235.
  9. Fuxreiter M (January 2012). "Fuzziness: linking regulation to protein dynamics". Mol Biosyst. 8 (1): 168–77. doi:10.1039/c1mb05234a. PMID 21927770.
  10. Fuxreiter M, Simon I, Bondos S (August 2011). "Dynamic protein-DNA recognition: beyond what can be seen". Trends Biochem. Sci. 36 (8): 415–23. doi:10.1016/j.tibs.2011.04.006. PMID 21620710.
  11. Ryan, C. J.; Krogan, N. J.; Cunningham, P; Cagney, G (2013). "All or nothing: Protein complexes flip essentiality between distantly related eukaryotes". Genome Biology and Evolution. 5 (6): 1049–59. doi:10.1093/gbe/evt074. PMC 3698920. PMID 23661563.
  12. Jeong, H; Mason, S. P.; Barabási, A. L.; Oltvai, Z. N. (2001). "Lethality and centrality in protein networks". Nature. 411 (6833): 41–2. arXiv:cond-mat/0105306. Bibcode:2001Natur.411...41J. doi:10.1038/35075138. PMID 11333967. S2CID 258942.
  13. Yu, H; Braun, P; Yildirim, M. A.; Lemmens, I; Venkatesan, K; Sahalie, J; Hirozane-Kishikawa, T; Gebreab, F; Li, N; Simonis, N; Hao, T; Rual, J. F.; Dricot, A; Vazquez, A; Murray, R. R.; Simon, C; Tardivo, L; Tam, S; Svrzikapa, N; Fan, C; De Smet, A. S.; Motyl, A; Hudson, M. E.; Park, J; Xin, X; Cusick, M. E.; Moore, T; Boone, C; Snyder, M; Roth, F. P. (2008). "High-quality binary protein interaction map of the yeast interactome network". Science. 322 (5898): 104–10. Bibcode:2008Sci...322..104Y. doi:10.1126/science.1158684. PMC 2746753. PMID 18719252.
  14. Zotenko, E; Mestre, J; O'Leary, D. P.; Przytycka, T. M. (2008). "Why do hubs in the yeast protein interaction network tend to be essential: Reexamining the connection between the network topology and essentiality". PLOS Computational Biology. 4 (8): e1000140. Bibcode:2008PLSCB...4E0140Z. doi:10.1371/journal.pcbi.1000140. PMC 2467474. PMID 18670624.
  15. Hart, G. T.; Lee, I; Marcotte, E. R. (2007). "A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality". BMC Bioinformatics. 8: 236. doi:10.1186/1471-2105-8-236. PMC 1940025. PMID 17605818.
  16. Wang, H; Kakaradov, B; Collins, S. R.; Karotki, L; Fiedler, D; Shales, M; Shokat, K. M.; Walther, T. C.; Krogan, N. J.; Koller, D (2009). "A complex-based reconstruction of the Saccharomyces cerevisiae interactome". Molecular & Cellular Proteomics. 8 (6): 1361–81. doi:10.1074/mcp.M800490-MCP200. PMC 2690481. PMID 19176519.
  17. Fraser, H. B.; Plotkin, J. B. (2007). "Using protein complexes to predict phenotypic effects of gene mutation". Genome Biology. 8 (11): R252. doi:10.1186/gb-2007-8-11-r252. PMC 2258176. PMID 18042286.
  18. Lage, K; Karlberg, E. O.; Størling, Z. M.; Olason, P. I.; Pedersen, A. G.; Rigina, O; Hinsby, A. M.; Tümer, Z; Pociot, F; Tommerup, N; Moreau, Y; Brunak, S (2007). "A human phenome-interactome network of protein complexes implicated in genetic disorders". Nature Biotechnology. 25 (3): 309–16. doi:10.1038/nbt1295. PMID 17344885. S2CID 5691546.
  19. Oti, M; Brunner, H. G. (2007). "The modular nature of genetic diseases". Clinical Genetics. 71 (1): 1–11. doi:10.1111/j.1399-0004.2006.00708.x. PMID 17204041. S2CID 24615025.
  20. Hashimoto K, Nishi H, Bryant S, Panchenko AR (June 2011). "Caught in self-interaction: evolutionary and functional mechanisms of protein homooligomerization". Phys Biol. 8 (3): 035007. Bibcode:2011PhBio...8c5007H. doi:10.1088/1478-3975/8/3/035007. PMC 3148176. PMID 21572178.
  21. Bernstein, H; Edgar, RS; Denhardt, GH (June 1965). "Intragenic Complementation among Temperature Sensitive Mutants of Bacteriophage T4D". Genetics. 51 (6): 987–1002. doi:10.1093/genetics/51.6.987. PMC 1210828. PMID 14337770.
  22. Smallwood S, Cevik B, Moyer SA. Intragenic complementation and oligomerization of the L subunit of the sendai virus RNA polymerase. Virology. 2002;304(2):235-245. doi:10.1006/viro.2002.1720
  23. Rodríguez-Pombo P, Pérez-Cerdá C, Pérez B, Desviat LR, Sánchez-Pulido L, Ugarte M. Towards a model to explain the intragenic complementation in the heteromultimeric protein propionyl-CoA carboxylase. Biochim Biophys Acta. 2005;1740(3):489-498. doi:10.1016/j.bbadis.2004.10.009
  24. Crick FH, Orgel LE. The theory of inter-allelic complementation. J Mol Biol. 1964 Jan;8:161-5. doi:10.1016/s0022-2836(64)80156-x. PMID 14149958
  25. Jehle H. Intermolecular forces and biological specificity. Proc Natl Acad Sci U S A. 1963;50(3):516-524. doi:10.1073/pnas.50.3.516
  26. Raicu V, Stoneman MR, Fung R, Melnichuk M, Jansma DB, Pisterzi LF, Rath S, Fox, M, Wells, JW, Saldin DK (2008). "Determination of supramolecular structure and spatial distribution of protein complexes in living cells". Nature Photonics. 3 (2): 107–113. doi:10.1038/nphoton.2008.291.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  27. Dobson, Christopher M (December 2003). "Protein folding and misfolding". Nature. 426 (6968): 884–90. Bibcode:2003Natur.426..884D. doi:10.1038/nature02261. PMID 14685248. S2CID 1036192.
  28. Marsh JA, Hernández H, Hall Z, Ahnert SE, Perica T, Robinson CV, Teichmann SA (Apr 2013). "Protein complexes are under evolutionary selection to assemble via ordered pathways". Cell. 153 (2): 461–470. doi:10.1016/j.cell.2013.02.044. PMC 4009401. PMID 23582331.
  29. Sudha, Govindarajan; Nussinov, Ruth; Srinivasan, Narayanaswamy (2014). "An overview of recent advances in structural bioinformatics of protein-protein interactions and a guide to their principles". Progress in Biophysics and Molecular Biology. 116 (2–3): 141–50. doi:10.1016/j.pbiomolbio.2014.07.004. PMID 25077409.
  30. Marsh, Joseph; Teichmann, Sarah A (May 2014). "Protein flexibility facilitates quaternary structure assembly and evolution". PLOS Biology. 12 (5): e1001870. doi:10.1371/journal.pbio.1001870. PMC 4035275. PMID 24866000.
  31. Levy, Emmanuel D; Boeri Erba, Elisabetta; Robinson, Carol V; Teichmann, Sarah A (July 2008). "Assembly reflects evolution of protein complexes". Nature. 453 (7199): 1262–5. Bibcode:2008Natur.453.1262L. doi:10.1038/nature06942. PMC 2658002. PMID 18563089.
This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.