Effects of Acetylation and Phosphorylation on Subunit Interactions in Three Large Eukaryotic Complexes
2018; Elsevier BV; Volume: 17; Issue: 12 Linguagem: Inglês
10.1074/mcp.ra118.000892
ISSN1535-9484
AutoresNikolina Šoštarić, Francis J. O’Reilly, Piero Giansanti, Albert J. R. Heck, Anne‐Claude Gavin, Vera van Noort,
Tópico(s)Enzyme Structure and Function
ResumoProtein post-translational modifications (PTMs) have an indispensable role in living cells as they expand chemical diversity of the proteome, providing a fine regulatory layer that can govern protein-protein interactions in changing environmental conditions. Here we investigated the effects of acetylation and phosphorylation on the stability of subunit interactions in purified Saccharomyces cerevisiae complexes, namely exosome, RNA polymerase II and proteasome. We propose a computational framework that consists of conformational sampling of the complexes by molecular dynamics simulations, followed by Gibbs energy calculation by MM/GBSA. After benchmarking against published tools such as FoldX and Mechismo, we could apply the framework for the first time on large protein assemblies with the aim of predicting the effects of PTMs located on interfaces of subunits on binding stability. We discovered that acetylation predominantly contributes to subunits' interactions in a locally stabilizing manner, while phosphorylation shows the opposite effect. Even though the local binding contributions of PTMs may be predictable to an extent, the long range effects and overall impact on subunits' binding were only captured because of our dynamical approach. Employing the developed, widely applicable workflow on other large systems will shed more light on the roles of PTMs in protein complex formation. Protein post-translational modifications (PTMs) have an indispensable role in living cells as they expand chemical diversity of the proteome, providing a fine regulatory layer that can govern protein-protein interactions in changing environmental conditions. Here we investigated the effects of acetylation and phosphorylation on the stability of subunit interactions in purified Saccharomyces cerevisiae complexes, namely exosome, RNA polymerase II and proteasome. We propose a computational framework that consists of conformational sampling of the complexes by molecular dynamics simulations, followed by Gibbs energy calculation by MM/GBSA. After benchmarking against published tools such as FoldX and Mechismo, we could apply the framework for the first time on large protein assemblies with the aim of predicting the effects of PTMs located on interfaces of subunits on binding stability. We discovered that acetylation predominantly contributes to subunits' interactions in a locally stabilizing manner, while phosphorylation shows the opposite effect. Even though the local binding contributions of PTMs may be predictable to an extent, the long range effects and overall impact on subunits' binding were only captured because of our dynamical approach. Employing the developed, widely applicable workflow on other large systems will shed more light on the roles of PTMs in protein complex formation. A protein's functional engagement with other molecules in the cell is finely regulated by an array of post-translational modifications (PTMs) 1The abbreviations used are:PTMpost-translational modificationCP20S yeast proteasome core particleCTDC-terminal domain of Rpb1 subunit of RNA polymerase IIMDmolecular dynamicsMM/GBSAmolecular mechanics energies combined with Generalized Born and surface area continuum solvationMM/PBSAmolecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvationRMSDroot mean square deviationRP19S yeast proteasome regulatory particleTAP-MStandem affinity purification followed by mass spectrometryY2Hyeast 2-hybrid. 1The abbreviations used are:PTMpost-translational modificationCP20S yeast proteasome core particleCTDC-terminal domain of Rpb1 subunit of RNA polymerase IIMDmolecular dynamicsMM/GBSAmolecular mechanics energies combined with Generalized Born and surface area continuum solvationMM/PBSAmolecular mechanics energies combined with Poisson-Boltzmann and surface area continuum solvationRMSDroot mean square deviationRP19S yeast proteasome regulatory particleTAP-MStandem affinity purification followed by mass spectrometryY2Hyeast 2-hybrid. 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Because of technological developments (7Olsen J.V. Blagoev B. Gnad F. Macek B. Kumar C. Mortensen P. Mann M. Global, in vivo, and site-specific phosphorylation dynamics in signaling networks.Cell. 2006; 127: 635-648Abstract Full Text Full Text PDF PubMed Scopus (2807) Google Scholar, 12Zhou H. Watts J.D. Aebersold R. A systematic approach to the analysis of protein phosphorylation.Nat. Biotechnol. 2001; 19: 375-378Crossref PubMed Scopus (674) Google Scholar), PTMs have been identified on a proteome-wide scale for several organisms, with the resulting data of more than 600,000 individual experimentally found modification sites stored in the freely available on-line database dbPTM (13Huang K.-Y. Su M.-G. Kao H.-J. Hsieh Y.-C. Jhong J.-H. Cheng K.-H. Huang H.-D. Lee T.-Y. dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins.Nucleic Acids Res. 2016; 44: D435-D446Crossref PubMed Scopus (131) Google Scholar). Availability of PTMs data enabled investigation of their functional roles on a large scale. For instance, the PTMfunc (14Beltrao P. Albanèse V. Kenner L.R. Swaney D.L. Burlingame A. Villén J. Lim W.A. Fraser J.S. Frydman J. Krogan N.J. Systematic functional prioritization of protein posttranslational modifications.Cell. 2012; 150: 413-425Abstract Full Text Full Text PDF PubMed Scopus (298) Google Scholar) resource was made, in which the predictions of PTM's functional relevance for 200,000 sites from 11 eukaryotic species is based on the conservation analysis. Moreover, the Mechismo tool (15Betts M.J. Lu Q. Jiang Y. Drusko A. Wichmann O. Utz M. Valtierra-Gutiérrez I.A. Schlesner M. Jaeger N. Jones D.T. Pfister S. Lichter P. Eils R. Siebert R. Bork P. Apic G. Gavin A.-C. Russell R.B. Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions.Nucleic Acids Res. 2015; 43: e10Crossref PubMed Scopus (59) Google Scholar) was developed, which estimates the effect of an interface located mutation or modification on interaction stability, based on the observed amino acids interaction patterns, but without the explicit 3D modeling of neither the query, nor the mutated/modified complex. In a recent expansion of the Mechismo work, the accent was placed on detecting phosphorylation sites that act as protein interaction switches (16Betts M.J. Wichmann O. Utz M. Andre T. Petsalaki E. Minguez P. Parca L. Roth F.P. Gavin A.-C. Bork P. Russell R.B. Systematic identification of phosphorylation-mediated protein interaction switches.PLOS Comput. Biol. 2017; 13: e1005462Crossref PubMed Scopus (28) Google Scholar) by additionally considering the similarity of the protein with its template, as well as conservation of the phosphorylation site. However, in all these tools the dynamic information is missing, so a mechanistic understanding of PTMs effect is still lacking. Various efforts have also been undertaken to understand the functional roles of PTMs in specific (sets of) proteins, using not only experimental, but also computational approaches. For instance, Nishi et al. (17Nishi H. Hashimoto K. Panchenko A.R. Phosphorylation in protein-protein binding: effect on stability and function.Structure. 2011; 19: 1807-1815Abstract Full Text Full Text PDF PubMed Scopus (190) Google Scholar) examined the effect on energetics of binding caused by interface phosphorylations in human protein complexes. The calculations were performed using the empirical force field FoldX(18Schymkowitz J. Borg J. Stricher F. Nys R. Rousseau F. Serrano L. The FoldX web server: an online force field.Nucleic Acids Res. 2005; 33: W382-W388Crossref PubMed Scopus (1547) Google Scholar), in which side chains of the residues surrounding the phosphorylation site are optimized before binding energy calculation is performed. The obtained distribution was very much shifted toward destabilization, and for approximately one third of the sites destabilization effect was larger than 2 kcal/mol, which was taken as a threshold for a site to have a strong effect on interaction. Several studies also applied molecular dynamics (MD) simulations to assess the effect of PTMs on proteins, e.g. Narayanan et al. (19Narayanan A. LeClaire L.L. Barber D.L. Jacobson M.P. Phosphorylation of the Arp2 subunit relieves auto-inhibitory interactions for Arp2/3 complex activation.PLoS Comput. Biol. 2011; 7: e1002226Crossref PubMed Scopus (15) Google Scholar) investigated actin-related protein 2/3 complex, and Kumar et al. (20Kumar P. Chimenti M.S. Pemble H. Schönichen A. Thompson O. Jacobson M.P. Wittmann T. Multisite phosphorylation disrupts arginine-glutamate salt bridge networks required for binding of cytoplasmic linker-associated protein 2 (CLASP2) to end-binding protein 1 (EB1).J. Biol. Chem. 2012; 287: 17050-17064Abstract Full Text Full Text PDF PubMed Scopus (62) Google Scholar) cytoplasmic linker-associated protein 2 binding to end-binding protein 1. Their conclusions were of qualitative nature, for instance they observed the reorientation of proteins, formation and breaking of salt bridges and hydrogen bonds in the respective complexes. Additionally, an MD-based method employing nine physicochemical parameters extracted from the trajectories was recently proposed to predict the impact of phosphorylation on protein-protein interactions (21Chiappori F. Mattiazzi L. Milanesi L. Merelli I. A novel molecular dynamics approach to evaluate the effect of phosphorylation on multimeric protein interface: the αB-Crystallin case study.BMC Bioinformatics. 2016; 17: 57Crossref PubMed Scopus (16) Google Scholar). Until now, PTMs have been identified in whole cell lysates and mapped to protein structures, but it was unclear if they were actually present in native protein complexes. In this study, we aimed to elucidate the roles of phosphorylation and acetylation sites in three large yeast complexes that are essential for life - exosome, RNA polymerase II and 26S proteasome - by combining experimental and computational approaches (Fig. 1). Exosome catalyzes 3′-5′ ribonucleic acid (RNA) degradation in eukaryotes, which is involved in regulating the amount of transcripts, as well as their maturation and quality control (22Makino D.L. Baumgärtner M. Conti E. Crystal structure of an RNA-bound 11-subunit eukaryotic exosome complex.Nature. 2013; 495: 70-75Crossref PubMed Scopus (165) Google Scholar). The core of the exosome consists of a hexameric ring (subunits Rrp41, Rrp42, Rrp43, Rrp45, Rrp46 and Mtr3) and a trimeric cap (Rrp4, Rrp40 and Csl4) (22Makino D.L. Baumgärtner M. Conti E. Crystal structure of an RNA-bound 11-subunit eukaryotic exosome complex.Nature. 2013; 495: 70-75Crossref PubMed Scopus (165) Google Scholar, 23Wasmuth E.V. Januszyk K. Lima C.D. Structure of an Rrp6-RNA exosome complex bound to poly(A) RNA.Nature. 2014; 511: 435-439Crossref PubMed Scopus (95) Google Scholar). In the cytoplasm, this nonamer recruits the catalytically active Rrp44 subunit (23Wasmuth E.V. Januszyk K. Lima C.D. Structure of an Rrp6-RNA exosome complex bound to poly(A) RNA.Nature. 2014; 511: 435-439Crossref PubMed Scopus (95) Google Scholar), whereas nuclear exosome additionally has Rrp6 subunit and its obligate partner C1D (24Zinder J.C. Lima C.D. Targeting RNA for processing or destruction by the eukaryotic RNA exosome and its cofactors.Genes Dev. 2017; 31: 88-100Crossref PubMed Scopus (121) Google Scholar). The second complex that we investigated, RNA polymerase II, is responsible for synthesis of all messenger RNA molecules, as well as several noncoding ones in eukaryotic cells (25Hsin J.-P. Manley J.L. The RNA polymerase II CTD coordinates transcription and RNA processing.Genes Dev. 2012; 26: 2119-2137Crossref PubMed Scopus (430) Google Scholar, 26Cramer P. Bushnell D.A. Kornberg R.D. Structural Basis of Transcription: RNA Polymerase II at 2.8 Ångstrom Resolution.Science. 2001; 292: 1863-1876Crossref PubMed Scopus (966) Google Scholar). Although 10 of its 12 subunits are conserved across species and identical or homologous to those in RNA polymerases I and III (26Cramer P. Bushnell D.A. Kornberg R.D. Structural Basis of Transcription: RNA Polymerase II at 2.8 Ångstrom Resolution.Science. 2001; 292: 1863-1876Crossref PubMed Scopus (966) Google Scholar, 27Vannini A. Cramer P. Conservation between the RNA Polymerase I, II, and III transcription initiation machineries.Mol. Cell. 2012; 45: 439-446Abstract Full Text Full Text PDF PubMed Scopus (287) Google Scholar), the remaining subunits Rpb4 and Rpb7 are specific for RNA polymerase II and are not important for the elongation process (28Hahn S. Structure and mechanism of the RNA polymerase II transcription machinery.Nat. Struct. Mol. Biol. 2004; 11: 394-403Crossref PubMed Scopus (367) Google Scholar). Till date, the investigation of PTMs' function in RNA polymerase II was mainly focused on phosphorylation of the C-terminal domain (CTD) of its largest subunit, Rpb1, an important regulatory element not found in other RNA polymerases (28Hahn S. Structure and mechanism of the RNA polymerase II transcription machinery.Nat. Struct. Mol. Biol. 2004; 11: 394-403Crossref PubMed Scopus (367) Google Scholar). CTD is composed of the consensus sequence Tyr-Ser-Pro-Thr-Ser-Pro-Ser repeats (29Fuchs S.M. Laribee R.N. Strahl B.D. Protein modifications in transcription elongation.Biochim. Biophys. Acta. 2009; 1789: 26-36Crossref PubMed Scopus (50) Google Scholar), known to change their phosphorylation status during the transcription cycle, and therefore dictate CTD's shape and binding of specific factors (28Hahn S. Structure and mechanism of the RNA polymerase II transcription machinery.Nat. Struct. Mol. Biol. 2004; 11: 394-403Crossref PubMed Scopus (367) Google Scholar). Other PTM types—OGlcNAcylation, ubiquitylation, methylation, proline isomerization—have also been reported for CTD (25Hsin J.-P. Manley J.L. The RNA polymerase II CTD coordinates transcription and RNA processing.Genes Dev. 2012; 26: 2119-2137Crossref PubMed Scopus (430) Google Scholar, 29Fuchs S.M. Laribee R.N. Strahl B.D. Protein modifications in transcription elongation.Biochim. Biophys. Acta. 2009; 1789: 26-36Crossref PubMed Scopus (50) Google Scholar), as well as acetylation of Lys from the non-consensus repeats found in some organisms (30Schröder S. Herker E. Itzen F. He D. Thomas S. Gilchrist D.A. Kaehlcke K. Cho S. Pollard K.S. Capra J.A. Schnölzer M. Cole P.A. Geyer M. Bruneau B.G. Adelman K. Ott M. Acetylation of RNA polymerase II regulates growth-factor-induced gene transcription in mammalian cells.Mol. Cell. 2013; 52: 314-324Abstract Full Text Full Text PDF PubMed Scopus (83) Google Scholar). Finally, the proteasome is the major protein degradation machinery present in all three domains of life. Its substrates differ from other proteins in the cell by an attached chain of small proteins, ubiquitins. In eukaryotes, the 26S proteasome contains the proteolytically active 20S core particle (CP), composed of α and β subunits, and the 19S regulatory particle (RP), which together count 33 different protein subunits (31Livneh I. Cohen-Kaplan V. Cohen-Rosenzweig C. Avni N. Ciechanover A. The life cycle of the 26S proteasome: from birth, through regulation and function, and onto its death.Cell Res. 2016; 26: 869-885Crossref PubMed Scopus (193) Google Scholar). Acetylation of CP and phosphorylation of both CP and RP subunits were found to affect proteasome activity (31Livneh I. Cohen-Kaplan V. Cohen-Rosenzweig C. Avni N. Ciechanover A. The life cycle of the 26S proteasome: from birth, through regulation and function, and onto its death.Cell Res. 2016; 26: 869-885Crossref PubMed Scopus (193) Google Scholar), while phosphorylation of the Rpt6 ATPase subunit of RP was found to have a role in proteasome assembly (31Livneh I. Cohen-Kaplan V. Cohen-Rosenzweig C. Avni N. Ciechanover A. The life cycle of the 26S proteasome: from birth, through regulation and function, and onto its death.Cell Res. 2016; 26: 869-885Crossref PubMed Scopus (193) Google Scholar, 32Satoh K. Sasajima H. Nyoumura K.I. Yokosawa H. Sawada H. Assembly of the 26S proteasome is regulated by phosphorylation of the p45/Rpt6 ATPase subunit.Biochemistry. 2001; 40: 314-319Crossref PubMed Scopus (115) Google Scholar). Recently, more than 345 PTMs of 11 different types were detected on the 26S proteasome (33Hirano H. Kimura Y. Kimura A. Biological significance of co- and post-translational modifications of the yeast 26S proteasome.J. Proteomics. 2016; 134: 37-46Crossref PubMed Scopus (44) Google Scholar), however because most of the obtained PTM data is quite novel and originates from large proteomics studies, their roles are still predominantly unknown (34Im E. Chung K.C. Precise assembly and regulation of 26S proteasome and correlation between proteasome dysfunction and neurodegenerative diseases.BMB Rep. 2016; 49: 459-473Crossref PubMed Scopus (16) Google Scholar). In this work, we first employ tandem affinity purification (TAP) followed by high resolution mass spectrometry (MS) in order to obtain the high fidelity information about PTM sites in the three natively purified complexes. Our data set contains a total of 129 acetylation and 41 phosphorylation sites detected within the complexes, almost all of which are novel. Secondly, we employ the available high-resolution 3D data to map the detected PTMs on the protein structures. Our focus is then placed on PTMs that are located at the subunits' interfaces, as such locations are generally more conserved, and therefore more likely functionally important and involved in the regulation of binding affinities (14Beltrao P. Albanèse V. Kenner L.R. Swaney D.L. Burlingame A. Villén J. Lim W.A. Fraser J.S. Frydman J. Krogan N.J. Systematic functional prioritization of protein posttranslational modifications.Cell. 2012; 150: 413-425Abstract Full Text Full Text PDF PubMed Scopus (298) Google Scholar, 17Nishi H. Hashimoto K. Panchenko A.R. Phosphorylation in protein-protein binding: effect on stability and function.Structure. 2011; 19: 1807-1815Abstract Full Text Full Text PDF PubMed Scopus (190) Google Scholar). Thirdly, in order to elucidate the effects of interface located novel PTMs on binding of subunits, we employ a computational approach consisting of meticulous conformational sampling via molecular dynamics simulations, followed by calculation of the Gibbs energy of binding by MM/GBSA method. We first test the robustness of this approach on yeast Skp1:Met30 system, benchmark it against Mechismo and FoldX on a set of mammalian protein complexes, apply it on the three large complexes, and experimentally validate our results. Finally, we compare the results for yeast complexes with predictions of the Mechismo tool and look into conservation of the PTM sites. Our predictions suggest the locally stabilizing role of the interface located acetylated lysines, and a locally destabilizing one for the phosphorylated residues. Moreover, our approach based on protein dynamics allowed us to capture global effects of PTMs on binding, with even binding of the chains that are not in a direct vicinity of PTMs being affected by their presence. Exosome, RNA polymerase II and 26S proteasome were purified from yeast Saccharomyces cerevisiae in native conditions, using tandem affinity purification (TAP). TAP was performed using one bait for each protein complex: YHR069C (Rrp4, exosome), YOR151C (Rpb2, RNA polymerase II) and YKL145W (Rpt1, 26S proteasome). Purified proteins were separated by SDS-PAGE followed by staining with Coomassie Brilliant Blue. Gel lanes were cut into slices, and subjected to in-gel digestion, using two different proteolytic enzymes (trypsin and chymotrypsin) in parallel, to increase the coverage. Obtained peptides were identified using high-resolution mass spectrometry (MS), as previously described (35Cristobal A. Hennrich M.L. Giansanti P. Goerdayal S.S. Heck A.J.R. Mohammed S. In-house construction of a UHPLC system enabling the identification of over 4000 protein groups in a single analysis.Analyst. 2012; 137: 3541-3548Crossref PubMed Scopus (42) Google Scholar). In brief, peptides were subjected to reversed phase nLC-MS/MS analysis using an Agilent (Santa Clara, CA) 1290 Infinity UHPLC system, coupled to a TripleTOF 5600 (AB Sciex, Framingham, MA) mass spectrometer. The UHPLC was equipped with a double frit trapping column (Agilent Zorbax SB-C18, 1.8 μm material, 0.5 cm x 100 μm) and a single frit analytical column (Agilent Zorbax SB-C18, 1.8 μm material, 40 cm x 50 μm). Trapping was performed for 10 min in solvent A (0.1% FA in water) at 5 μl/min, whereas chromatographic separation was performed with a gradient of 23 min from 13% to 44% of solvent B (80% ACN/0.1% FA). Total analysis time was 45 min. The mass spectrometer was operated in data-dependent mode. After the initial survey scan in high resolution mode, the 20 most intense precursors were selected for subsequent HCD fragmentation using rolling collision energy, and tandem mass spectra were acquired in high sensitivity mode with a resolution of 20,000. The acquired raw files were first recalibrated based on two background ions with m/z values of 371.1012 and 445.1200, and then converted to peak lists by the AB Sciex MS Data Converter tool version 1.1. Database search was performed with Mascot (Matrix Science, Boston, MA, version 2.3.2) using Proteome Discoverer (Thermo Scientific, Waltham, MA, version 1.2). The spectra were searched individually against the Saccharomyces cerevisiae SwissProt database (version 02_2012 - 6,619 sequences). All the results belonging to the same purification and enzyme digestion were grouped together in Proteome Discoverer, to get the final list of identifications. Trypsin or chymotrypsin were set as the enzyme accordingly, and up to two missed cleavages were allowed. Cysteine carbamidomethylation was set as the fixed modification. Methionine oxidation, serine, threonine, and tyrosine phosphorylation, protein n-term acetylation, as well as lysine acetylation were set as the variable modifications. Peptide tolerance was set to 50 ppm, whereas the MS/MS tolerance was 0.15 Da. Peptides identification where filtered for: (1) minimum ion score of 20, (2) position rank 1, (3) minimum peptide length of 6 amino acids, and (4) peptide tolerance 10 ppm. The phosphorylation site localization of the identified phosphopeptides was performed by the phosphoRS algorithm(36Taus T. Köcher T. Pichler P. Paschke C. Schmidt A. Henrich C. Mechtler K. Universal and confident phosphorylation site localization using phosphoRS.J. Proteome Res. 2011; 10: 5354-5362Crossref PubMed Scopus (568) Google Scholar), implemented in Proteome Discoverer. A site localization probability of at least 0.75 was used as the threshold for confident localization. The MS proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository (37Vizcaíno J.A. Côté R.G. Csordas A. Dianes J.A. Fabregat A. Foster J.M. Griss J. Alpi E. Birim M. Contell J. O'Kelly G. Schoenegger A. Ovelleiro D. Pérez-Riverol Y. Reisinger F. Ríos D. Wang R. Hermjakob H. The Proteomics Identifications (PRIDE) database and associated tools: status in 2013.Nucleic Acids Res. 2012; 41: D1063-D1069Crossref PubMed Scopus (1594) Google Scholar) with the data set identifier PXD008324. The following experimentally obtained structures deposited in PDB (38Berman H.M. Westbrook J. Feng Z. Gilliland G. Bhat T.N. Weissig H. Shindyalov I.N. Bourne P.E. The Protein Data Bank.Nucleic Acids Res. 2000; 28: 235-242Crossref PubMed Scopus (27325) Google Scholar) (www.rcsb.org/) were used: 4OO11 for the exosome (23Wasmuth E.V. Januszyk K. Lima C.D. Structure of an Rrp6-RNA exosome complex bound to poly(A) RNA.Nature. 2014; 511: 435-439Crossref PubMed Scopus (95) Google Scholar), 1I3Q2 for the RNA polymerase II (26Cramer P. Bushnell D.A. Kornberg R.D. Structural Basis of Transcription: RNA Polymerase II at 2.8 Ångstrom Resolution.Science. 2001; 292: 1863-1876Crossref PubMed Scopus (966) Google Scholar) and 4CR23 for the 26S proteasome (39Unverdorben P. Beck F. Śledź Schweitzer P.A. Pfeifer G. Plitzko J.M. Baumeister W. Förster F. Deep classification of a large cryo-EM dataset defines the conformational landscape of the 26S proteasome.Proc. Natl. Acad. Sci. U.S.A. 2014; 111: 5544-5549Crossref PubMed Scopus (143) Google Scholar). We worked with the exosome structure 4OO1 which does not contain Rrp44 subunit, even though the complete 11 subunits structure is also deposited under ID 4IFD4 (22Makino D.L. Baumgärtner M. Conti E. Crystal structure of an RNA-bound 11-subunit eukaryotic exosome complex.Nature. 2013; 495: 70-75Crossref PubMed Scopus (165) Google Scholar). None of the Rrp44 PTMs found in this study are located at its interface with other subunits in 4IFD, so the 4OO1 structure that does not contain this 1003 amino acid long chain was used to make calculations less demanding. The structure of yeast Skp1:Met30 complex was obtained from Genome Wide Docking Database GWIDD (40Kundrotas P.J. Zhu Z. Vakser I.A. GWIDD: Genome-wide protein docking database.Nucleic Acids Res. 2010; 38: D513-D517Crossref PubMed Scopus (37) Google Scholar) as the homology model GWD368CM. For obtaining the model, chains A and B of 1NEX5 PDB structure (41Orlicky S. Tang X. Willems A. Tyers M. Sicheri F. Structural Basis for Phosphodependent Substrate Selection and Orientation by the SCFCdc4 Ubiquitin Ligase.Cell. 2003; 112: 243-256Abstract Full Text Full Text PDF PubMed Scopus (424) Google Scholar), corresponding to the yeast Skp1 and Cdc4 proteins, were used as templates. However, the N-terminal part of Met30 remained unstructured because of lack of a Cdc4 region that would serve as a t
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