- Research article
- Open Access
Structural disorder promotes assembly of protein complexes
© Hegyi et al.; licensee BioMed Central Ltd. 2007
- Received: 28 March 2007
- Accepted: 08 October 2007
- Published: 08 October 2007
The idea that the assembly of protein complexes is linked with protein disorder has been inferred from a few large complexes, such as the viral capsid or bacterial flagellar system, only. The relationship, which suggests that larger complexes have more disorder, has never been systematically tested. The recent high-throughput analyses of protein-protein interactions and protein complexes in the cell generated data that enable to address this issue by bioinformatic means.
In this work we predicted structural disorder for both E. coli and S. cerevisiae, and correlated it with the size of complexes. Using IUPred to predict the disorder for each complex, we found a statistically significant correlation between disorder and the number of proteins assembled into complexes. The distribution of disorder has a median value of 10% in yeast for complexes of 2–4 components (6% in E. coli), but 18% for complexes in the size range of 11–100 proteins (12% in E. coli). The level of disorder as assessed for regions longer than 30 consecutive disordered residues shows an even stronger division between small and large complexes (median values about 4% for complexes of 2–4 components, but 12% for complexes of 11–100 components in yeast). The predicted correlation is also supported by experimental evidence, by observing the structural disorder in protein components of complexes that can be found in the Protein Data Bank (median values 1. 5% for complexes of 2–4 components, and 9.6% for complexes of 11–100 components in yeast). Further analysis shows that this correlation is not directly linked with the increased disorder in hub proteins, but reflects a genuine systemic property of the proteins that make up the complexes.
Overall, it is suggested and discussed that the assembly of protein-protein complexes is enabled and probably promoted by protein disorder.
- Structural Disorder
- Large Complex
- Small Complex
- Protein Disorder
- Complex Size
Intrinsically unstructured/disordered proteins or protein domains (IUPs) lack a well-defined structure, yet they carry out important functions [1–4]. IUPs often function by molecular recognition, when they bind partner molecules and undergo binding-induced folding transitions [5, 6]. In these, the presence of protein disorder is thought to confer many functional advantages, such as the increased speed of interaction, specificity without excessive binding strength, and the adaptability to different partners, i.e. binding promiscuity or moonlighting . These advantages may explain the recent observation that hub proteins, i.e. proteins involved in multiple interactions, tend to have a higher level of structural disorder than other proteins in the interactome [8–11], although the difference is small, and was not observed in one study .
Extending beyond these advantages is the suggestion that due to their open and exposed structure, IUPs might be able to simultaneously bind multiple partners , which enables the assembly of large complexes. Whereas disorder in such "assembler" functions [3, 14] apparently has a significant advantage, its validity relies on a few isolated observations only. The high level and/or observed mechanistic role of disorder in the assembly process of the bacterial flagellum and viral capsid , the cytoskeleton, ribosome and clathrin coat [16, 17], or some scaffolding proteins, such as BRCA1 and Ste5 [18, 19], serve as focal points for the suggestion that structural disorder enables the assembly of large complexes. Whereas physical logic for such an assembly process implies large-scale structural rearrangements enabled by excessive flexibility, this inference has never been systematically tested. Recent high-throughput TAP-tag/MS studies of the full complement of protein-protein interactions (the interactome) of E. coli and S. cerevisiae [20–22] enabled us to probe into the general validity of the role of protein disorder in complexes and the assembly process.
Since the assembly of larger complexes may be conceived to process from smaller complexes at the expense of the burial of an increasing surface with increasing complex size, the foregoing considerations suggest that protein disorder should increase with increasing numbers of complexed proteins. We checked this inference by protein disorder prediction and also by looking for disorder in protein components of complexes in PDB. By applying IUPred [23, 24], we found a statistically significant correlation between disorder and the number of proteins assembled into complexes for both E. coli and S. cerevisiae. The predicted correlation is also seen for a limited set of proteins for which experimental evidence of disorder can be found in the PDB. Our observations provide comprehensive evidence that the fraction of protein disorder increases with increasing complex size, which corroborates and extends previous suggestions that protein disorder is directly advantageous in protein-protein interactions [3, 6, 14].
The population of the different size groups in E. coli and yeast complexes
Number of complexes in the different data sets
E. coli (Arifuzzaman06)
E. coli (Butland05)
E. coli (Gully06)
2 – 4 proteins
5 – 10 proteins
11 – 20 proteins
21 – 30 proteins
31 – 100 proteins
Number of singular proteins and proteins in complexes of different sizes in the different data sets
E. coli (Arifuzzaman06)
E. coli (Butland05)
E. coli (Gully06)
2 – 4 proteins
5 – 10 proteins
11 – 20 proteins
21 – 30 proteins
31 – 100 proteins
Distribution of the predicted disorder of the complexes of different sizes
Disorder calculated from segments of more than 30 residues
Distribution of the disorder of the protein components in the different complex size groups
Distribution of the observed disorder of E. coli complexes derived from the PDB homologues of the protein components
The results presented thus far rely on disorder prediction by IUPred, which, at a false positive rate of 5% predicts disordered residues at a true positive rate of 76% . To support these findings by actual data on disorder, we also compared the experimentally observed disorder of proteins in complexes of various sizes. To this end, we selected E. coli proteins in complexes that appear in PDB, using Blastp (yeast homologues were not numerous enough for a thorough statistical analysis). We used only those protein matches in PDB that had at least 90% sequence identity with a complex component. We considered almost full matches only where the lengths of the query proteins and that of the best match in PDB did not differ by more than 50 amino acids.
We used both single-chain and multi-chain PDB matches. Although in the latter set there might be significant disorder-to-order transition known to occur when a protein binds to its partner(s), still there is a linear relationship between the observed disorder (calculated as the average disorder of the PDB homologues of the complex components for each complex and the predicted one (additional file 2), which shows the relevance of disorder thus extracted from PDB.
Comparing complexes and hub proteins
The greater disorder of hub proteins (defined as such if they interact with more than 10 proteins in pair-wise interactions) observed by several groups independently [8–11]) raises the question of a relationship between hubs and complexes. The question is justified as there is a positive correlation between hub proteins and those that appear in a large number of complexes (additional file 3).
It is traditionally held that a major advantage of protein disorder is that it facilitates protein-protein interactions, which may explain the increased level of disorder in hub proteins [8–11], and in some large protein complexes [15–17]. Since a large body of data on the identity of complexes of various sizes in E. coli and yeast has been generated in recent high-throughput TAP-tag/MS studies [20–22], we have been able to test if, as expected, larger complexes have more average disorder than smaller ones.
Our findings validate the expected correlation. For both E. coli and yeast, there is a statistically significant increase in average predicted disorder with the number of components of complexes. This increase is even more pronounced if only long (more than 30 consecutive residues) disordered regions are taken into consideration, which suggest that these regions are particularly relevant in protein-protein interactions, and in particular in the assembly of large complexes. The major source of the observed correlation is that larger complexes are assembled from proteins that tend to be more disordered, underlined by the observation that proteins unique to large complexes in yeast show the highest level of disorder. The observed correlation is also corroborated by experimentally observed disorder of individual proteins, selected from the PDB, even though traditional structure-solution and deposition in PDB is biased against long disordered regions .
The observed correlation points to important functional implications of protein disorder in the organisation and evolution of the interactome, and it also raises interesting experimental ideas and provide important functional insight. These points will be discussed next. First, our report relies mostly on the prediction of disorder, and requires further corroboration by experimental data. Undoubtedly, as the interactome research advances and more complexes are identified, these studies may be further refined. Also, because PDB is highly biased against disorder, alternative data sources providing data on the disorder of individual proteins will give a boost to these ideas. Such data are deposited into the DisProt database , which is expected to grow rapidly as protein disorder is gaining general recognition. Second, the observed correlation between disorder and complex size provides a mechanistic insight into the roles disorder plays in the assembly of complexes. One possibility is that disordered regions are involved in the binding process directly, as suggested already by the fact that local disorder serves recognition functions in the form of molecular recognition features (MoRFs ) or short linear motifs (SLMs ). Alternatively, disorder might provide flexible linkers of well-folded interaction domains, which might enable their productive interactions. These alternatives might be experimentally tested as the structures of more and more large complexes are solved. By the same token, as longer disordered segments appear to correlate better with complex size, this feature might also be experimentally tested.
The third ramification of our observations is in the evolution of protein complexes. If we consider the formation of large complexes in evolutionary terms, they must have come about by the addition of new components to smaller pre-existing complexes. The predicted increase in disorder with complex size is only compatible with this model if we assume that the newer proteins attached to complexes are more disordered, thus increasing the average disorder as observed. Whereas this inference will also become testable as actual structures of large complexes become available, it is already in agreement with the observed advance of protein disorder with evolution, i.e. the increase of observed disorder with evolutionary complexity of organisms, which suggests that newer proteins tend to be more disordered [17, 25, 26].
A further key point to address is the relationship of increasing disorder with complex size and an increased level of disorder in hub proteins [8–11]. Hubs in general organize the interactome, and "party" hubs  are involved in binding several partners at the same time, i.e. scaffolding (large) complexes. Our analysis, however, shows that the number of interacting partners is in no correlation with the number of components of complexes the protein is in, which suggests that increasing disorder with complex size is independent of the presence of hubs, and is probably a genuine property of the entire complex. This finding is in line with several previous observations. First, a significant fraction of hubs termed "date" hubs  are involved in binding multiple partners on distinct occasions, i.e. they increase the level of disorder of small complexes, but not that of large ones. The other point is that the level of disorder in hub(s) is not much larger than that in non-hubs ([8–10], and cf. a counterexample, ), and the presence of one such organizing protein does not necessarily increase the average level of the disorder of a complex. A final point is that it was suggested that often hubs are not disordered, but instead interact with disordered partners . Incorporation of such a hub in a complex would decrease average disorder, and thus an increased level of disorder of the complex would rather reflect the disorder of interacting partners. In all, it appears our observation on complexes is a novel manifestation of the role of disorder in protein-protein interactions.
In conclusion, our studies provide evidence for the intimate link between protein disorder and the assembly of complexes. Larger complexes appear to have more average disorder and more of long segments of disorder, which are in perfect agreement with prior suggestions that a major evolutionary and functional asset of protein disorder is its involvement in protein-protein interactions [6, 13]. Whereas our observations provide evidence for these previous suggestions, they also raise new and testable hypotheses, which will lead to novel experiments in future studies on protein disorder and protein-protein interactions.
E. coli and yeast datasets
We analyzed several datasets in the IntAct database  containing data about protein complexes in E. coli and S. cerevisiae, generated by TAP-tag/MS analysis. However, data obtained by yeast two-hybrid analysis have not been considered because complex size cannot be adequately inferred from pair-wise interaction studies. For E. coli we focused on three data sets, each containing experimental TAP-tag data on a large scale [22, 36, 37]. For yeast, we analyzed only one data set  present in IntAct, as this was the only data set that contained a reasonable number of large complexes determined from a single proteome-wide experiment. Unless otherwise noted, we refer to this experiment when we talk about yeast complexes throughout the paper.
Prediction of disorder
We used the IUPred server  to predict the disorder of the E. coli and yeast proteins in the study. We determined the percentage disorder for each protein in the complexes by counting the number of disordered amino acids as predicted by IUPred, divided it by the length of the protein in question and multiplied the result with 100. We determined the average percentage disorder for each complex by averaging the percentage disorder of the component proteins of the complexes. These primary data can be found in additional files 4 and 5. For all these and the following steps we used in-house Perl scripts.
Percentage distribution of percentage disorder
After determining the average percentage disorder for each complex we grouped them into different categories according to their size (i.e. the number of component proteins). For each category we determined the distribution of their disorder by counting the number of complexes in each disorder range (usually in increments of 5% of disorder) and normalizing each distribution curve in a way that the total number of values for each curve would add up to 100.
where Oi and Ei are the observed and expected frequencies, respectively, for a series of data.
PDB homologs of the complex components
We used Blastp  to compare the sequences of the E. coli and yeast proteins to those in PDB . We took into account only those proteins in PDB that matched one of the protein components of the complexes or any of the non-complexed proteins in question with at least 90% sequence identity. If several proteins satisfied these criteria, only the best match was taken into consideration. We considered almost full matches only, where the lengths of the query proteins and that of the best match in PDB did not differ by more than 50 amino acids. This resulted in insufficient number of proteins for yeast, and thus we only carried out the subsequent analysis in the case of E. coli proteins. We assigned the disorder of each matching protein in the PDB by adding up the number of amino acids in the header of each PDB entry whose structure the authors could not determine, marked as "missing residues". However, we did not consider undetermined side chains as disordered.
Selecting single proteins in yeast and E. coli
The list of single proteins in yeast was kindly provided by AC Gavin, defined as such as those proteins that were found not to be complexed with any other in the TAP-tag experiments by . They found 241 such proteins. For E. coli we selected those proteins in SwissProt that did not have any evidence to be part of a complex according to either the IntAct database or Swissprot. We identified 1922 such proteins of the 4933 E. coli proteins present in SwissProt.
This research was supported by grants OTKA K60694 from the Hungarian Scientific Research Fund, ETT 245/2006 from the Hungarian Ministry of Health, International Senior Research Fellowship ISRF 067595 from the Wellcome Trust to P.T. and a Marie Curie reintegration grant IRG-046572 form the European Commission to H.H.
- Dyson HJ, Wright PE: Intrinsically unstructured proteins and their functions. Nat Rev Mol Cell Biol 2005, 6: 197–208. 10.1038/nrm1589View ArticlePubMedGoogle Scholar
- Fink AL: Natively unfolded proteins. Curr Opin Struct Biol 2005, 15: 35–41. 10.1016/j.sbi.2005.01.002View ArticlePubMedGoogle Scholar
- Tompa P: The interplay between structure and function in intrinsically unstructured proteins. FEBS Lett 2005, 579: 3346–3354. 10.1016/j.febslet.2005.03.072View ArticlePubMedGoogle Scholar
- Uversky VN, Oldfield CJ, Dunker AK: Showing your ID: intrinsic disorder as an ID for recognition, regulation and cell signaling. J Mol Recognit 2005, 18: 343–384. 10.1002/jmr.747View ArticlePubMedGoogle Scholar
- Demchenko AP: Recognition between flexible protein molecules: induced and assisted folding. J Mol Recognit 2001, 14: 42–61. 10.1002/1099-1352(200101/02)14:1<42::AID-JMR518>3.0.CO;2-8View ArticlePubMedGoogle Scholar
- Dyson HJ, Wright PE: Coupling of folding and binding for unstructured proteins. Curr Opin Struct Biol 2002, 12: 54–60. 10.1016/S0959-440X(02)00289-0View ArticlePubMedGoogle Scholar
- Tompa P, Szasz C, Buday L: Structural disorder throws new light on moonlighting. Trends Biochem Sci 2005, 30: 484–489. 10.1016/j.tibs.2005.07.008View ArticlePubMedGoogle Scholar
- Haynes C, Oldfield CJ, Ji F, Klitgord N, Cusick ME, Radivojac P, Uversky VN, Vidal M, Iakoucheva LM: Intrinsic disorder is a common feature of hub proteins from four eukaryotic interactomes. PLoS Comput Biol 2006, 2: e100. 10.1371/journal.pcbi.0020100PubMed CentralView ArticlePubMedGoogle Scholar
- Patil A, Nakamura H: Disordered domains and high surface charge confer hubs with the ability to interact with multiple proteins in interaction networks. FEBS Lett 2006, 580: 2041–2045. 10.1016/j.febslet.2006.03.003View ArticlePubMedGoogle Scholar
- Dosztanyi Z, Chen J, Dunker AK, Simon I, Tompa P: Disorder and sequence repeats in hub proteins and their implications for network evolution. J Proteome Res 2006, 5: 2985–2995. 10.1021/pr060171oView ArticlePubMedGoogle Scholar
- Ekman D, Light S, Bjorklund AK, Elofsson A: What properties characterize the hub proteins of the protein-protein interaction network of Saccharomyces cerevisiae? Genome Biol 2006, 7: R45. 10.1186/gb-2006-7-6-r45PubMed CentralView ArticlePubMedGoogle Scholar
- Schnell S, Fortunato S, Roy S: Is the intrinsic disorder of proteins the cause of the scale-free architecture of protein-protein interaction networks? Proteomics 2007, 7: 961–964. 10.1002/pmic.200600455View ArticlePubMedGoogle Scholar
- Gunasekaran K, Tsai CJ, Kumar S, Zanuy D, Nussinov R: Extended disordered proteins: targeting function with less scaffold. Trends Biochem Sci 2003, 28: 81–85. 10.1016/S0968-0004(03)00003-3View ArticlePubMedGoogle Scholar
- Tompa P: Intrinsically unstructured proteins. Trends Biochem Sci 2002, 27: 527–533. 10.1016/S0968-0004(02)02169-2View ArticlePubMedGoogle Scholar
- Namba K: Roles of partly unfolded conformations in macromolecular self-assembly. Genes Cells 2001, 6: 1–12. 10.1046/j.1365-2443.2001.00384.xView ArticlePubMedGoogle Scholar
- Dafforn TR, Smith CJ: Natively unfolded domains in endocytosis: hooks, lines and linkers. EMBO Rep 2004, 5: 1046–1052. 10.1038/sj.embor.7400276PubMed CentralView ArticlePubMedGoogle Scholar
- Ward JJ, Sodhi JS, McGuffin LJ, Buxton BF, Jones DT: Prediction and functional analysis of native disorder in proteins from the three kingdoms of life. J Mol Biol 2004, 337: 635–645. 10.1016/j.jmb.2004.02.002View ArticlePubMedGoogle Scholar
- Mark WY, Liao JC, Lu Y, Ayed A, Laister R, Szymczyna B, Chakrabartty A, Arrowsmith CH: Characterization of segments from the central region of BRCA1: an intrinsically disordered scaffold for multiple protein-protein and protein-DNA interactions? J Mol Biol 2005, 345: 275–287. 10.1016/j.jmb.2004.10.045View ArticlePubMedGoogle Scholar
- Bhattacharyya RP, Remenyi A, Good MC, Bashor CJ, Falick AM, Lim WA: The Ste5 scaffold allosterically modulates signaling output of the yeast mating pathway. Science 2006, 311: 822–826. 10.1126/science.1120941View ArticlePubMedGoogle Scholar
- Gavin AC, Bosche M, Krause R, Grandi P, Marzioch M, Bauer A, Schultz J, Rick JM, Michon AM, Cruciat CM, Remor M, Hofert C, Schelder M, Brajenovic M, Ruffner H, Merino A, Klein K, Hudak M, Dickson D, Rudi T, Gnau V, Bauch A, Bastuck S, Huhse B, Leutwein C, Heurtier MA, Copley RR, Edelmann A, Querfurth E, Rybin V, Drewes G, Raida M, Bouwmeester T, Bork P, Seraphin B, Kuster B, Neubauer G, Superti-Furga G: Functional organization of the yeast proteome by systematic analysis of protein complexes. Nature 2002, 415: 141–147. 10.1038/415141aView ArticlePubMedGoogle Scholar
- Gavin AC, Aloy P, Grandi P, Krause R, Boesche M, Marzioch M, Rau C, Jensen LJ, Bastuck S, Dumpelfeld B, Edelmann A, Heurtier MA, Hoffman V, Hoefert C, Klein K, Hudak M, Michon AM, Schelder M, Schirle M, Remor M, Rudi T, Hooper S, Bauer A, Bouwmeester T, Casari G, Drewes G, Neubauer G, Rick JM, Kuster B, Bork P, Russell RB, Superti-Furga G: Proteome survey reveals modularity of the yeast cell machinery. Nature 2006, 440: 631–636. 10.1038/nature04532View ArticlePubMedGoogle Scholar
- Arifuzzaman M, Maeda M, Itoh A, Nishikata K, Takita C, Saito R, Ara T, Nakahigashi K, Huang HC, Hirai A, Tsuzuki K, Nakamura S, Altaf-Ul-Amin M, Oshima T, Baba T, Yamamoto N, Kawamura T, Ioka-Nakamichi T, Kitagawa M, Tomita M, Kanaya S, Wada C, Mori H: Large-scale identification of protein-protein interaction of Escherichia coli K-12. Genome Res 2006, 16: 686–691. 10.1101/gr.4527806PubMed CentralView ArticlePubMedGoogle Scholar
- Dosztanyi Z, Csizmok V, Tompa P, Simon I: IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content. Bioinformatics 2005, 21: 3433–3434. 10.1093/bioinformatics/bti541View ArticlePubMedGoogle Scholar
- Dosztányi Z, Csizmok V, Tompa P, Simon I: The pairwise energy content estimated from amino acid composition discriminates between folded and instrinsically unstructured proteins. J Mol Biol 2005, 347: 827–839. 10.1016/j.jmb.2005.01.071View ArticlePubMedGoogle Scholar
- Dunker AK, Obradovic Z, Romero P, Garner EC, Brown CJ: Intrinsic protein disorder in complete genomes. Genome Inform Ser Workshop Genome Inform 2000, 11: 161–171.PubMedGoogle Scholar
- Tompa P, Dosztanyi Z, Simon I: Prevalent structural disorder in E. coli and S. cerevisiae proteomes. J Proteome Res 2006, 5: 1996–2000. 10.1021/pr0600881View ArticlePubMedGoogle Scholar
- Puntervoll P, Linding R, Gemund C, Chabanis-Davidson S, Mattingsdal M, Cameron S, Martin DM, Ausiello G, Brannetti B, Costantini A, Ferre F, Maselli V, Via A, Cesareni G, Diella F, Superti-Furga G, Wyrwicz L, Ramu C, McGuigan C, Gudavalli R, Letunic I, Bork P, Rychlewski L, Kuster B, Helmer-Citterich M, Hunter WN, Aasland R, Gibson TJ: ELM server: A new resource for investigating short functional sites in modular eukaryotic proteins. Nucleic Acids Res 2003, 31: 3625–3630. 10.1093/nar/gkg545PubMed CentralView ArticlePubMedGoogle Scholar
- Peng K, Radivojac P, Vucetic S, Dunker AK, Obradovic Z: Length-dependent prediction of protein intrinsic disorder. BMC Bioinformatics 2006, 7: 208. 10.1186/1471-2105-7-208PubMed CentralView ArticlePubMedGoogle Scholar
- Fuxreiter M, Tompa P, Simon I: Structural disorder imparts plasticity on linear motifs. Bioinformatics 2007, 23: 950–956. 10.1093/bioinformatics/btm035View ArticlePubMedGoogle Scholar
- Le Gall T, Romero PR, Cortese MS, Uversky VN, Dunker AK: Intrinsic disorder in the protein data bank. J Biomol Struct Dyn 2007, 24: 325–342.View ArticlePubMedGoogle Scholar
- Sickmeier M, Hamilton JA, LeGall T, Vacic V, Cortese MS, Tantos A, Szabo B, Tompa P, Chen J, Uversky VN, Obradovic Z, Dunker AK: DisProt: the Database of Disordered Proteins. Nucleic Acids Res 2007, 35: D786–93. 10.1093/nar/gkl893PubMed CentralView ArticlePubMedGoogle Scholar
- Mohan A, Oldfield CJ, Radivojac P, Vacic V, Cortese MS, Dunker AK, Uversky VN: Analysis of Molecular Recognition Features (MoRFs). J Mol Biol 2006, 362: 1043–1059. 10.1016/j.jmb.2006.07.087View ArticlePubMedGoogle Scholar
- Han JD, Bertin N, Hao T, Goldberg DS, Berriz GF, Zhang LV, Dupuy D, Walhout AJ, Cusick ME, Roth FP, Vidal M: Evidence for dynamically organized modularity in the yeast protein-protein interaction network. Nature 2004, 430: 88–93. 10.1038/nature02555View ArticlePubMedGoogle Scholar
- Dunker AK, Cortese MS, Romero P, Iakoucheva LM, Uversky VN: Flexible nets. The roles of intrinsic disorder in protein interaction networks. Febs J 2005, 272: 5129–5148. 10.1111/j.1742-4658.2005.04948.xView ArticlePubMedGoogle Scholar
- Kerrien S, Alam-Faruque Y, Aranda B, Bancarz I, Bridge A, Derow C, Dimmer E, Feuermann M, Friedrichsen A, Huntley R, Kohler C, Khadake J, Leroy C, Liban A, Lieftink C, Montecchi-Palazzi L, Orchard S, Risse J, Robbe K, Roechert B, Thorneycroft D, Zhang Y, Apweiler R, Hermjakob H: IntAct--open source resource for molecular interaction data. Nucleic Acids Res 2007, 35: D561–5. 10.1093/nar/gkl958PubMed CentralView ArticlePubMedGoogle Scholar
- Butland G, Peregrin-Alvarez JM, Li J, Yang W, Yang X, Canadien V, Starostine A, Richards D, Beattie B, Krogan N, Davey M, Parkinson J, Greenblatt J, Emili A: Interaction network containing conserved and essential protein complexes in Escherichia coli. Nature 2005, 433: 531–537. 10.1038/nature03239View ArticlePubMedGoogle Scholar
- Gully D, Bouveret E: A protein network for phospholipid synthesis uncovered by a variant of the tandem affinity purification method in Escherichia coli. Proteomics 2006, 6: 282–293. 10.1002/pmic.200500115View ArticlePubMedGoogle Scholar
- Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25: 3389–3402. 10.1093/nar/25.17.3389PubMed CentralView ArticlePubMedGoogle Scholar
- Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE: The Protein Data Bank. Nucleic Acids Res 2000, 28: 235–242. 10.1093/nar/28.1.235PubMed CentralView ArticlePubMedGoogle Scholar
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