Synergy between NMR measurements and MD simulations of protein/RNA complexes: application to the RRMs, the most common RNA recognition motifs
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
27193998
PubMed Central
PMC5291263
DOI
10.1093/nar/gkw438
PII: gkw438
Knihovny.cz E-zdroje
- MeSH
- konformace proteinů MeSH
- lidé MeSH
- magnetická rezonanční spektroskopie MeSH
- molekulární modely MeSH
- motiv rozpoznávající RNA genetika MeSH
- multiproteinové komplexy chemie genetika MeSH
- RNA chemie genetika MeSH
- sekvence aminokyselin genetika MeSH
- serin-arginin sestřihové faktory chemie genetika MeSH
- sestřihové faktory chemie genetika MeSH
- simulace molekulární dynamiky MeSH
- vazebná místa MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- multiproteinové komplexy MeSH
- RBFOX1 protein, human MeSH Prohlížeč
- RNA MeSH
- serin-arginin sestřihové faktory MeSH
- sestřihové faktory MeSH
- SRSF1 protein, human MeSH Prohlížeč
RNA recognition motif (RRM) proteins represent an abundant class of proteins playing key roles in RNA biology. We present a joint atomistic molecular dynamics (MD) and experimental study of two RRM-containing proteins bound with their single-stranded target RNAs, namely the Fox-1 and SRSF1 complexes. The simulations are used in conjunction with NMR spectroscopy to interpret and expand the available structural data. We accumulate more than 50 μs of simulations and show that the MD method is robust enough to reliably describe the structural dynamics of the RRM-RNA complexes. The simulations predict unanticipated specific participation of Arg142 at the protein-RNA interface of the SRFS1 complex, which is subsequently confirmed by NMR and ITC measurements. Several segments of the protein-RNA interface may involve competition between dynamical local substates rather than firmly formed interactions, which is indirectly consistent with the primary NMR data. We demonstrate that the simulations can be used to interpret the NMR atomistic models and can provide qualified predictions. Finally, we propose a protocol for 'MD-adapted structure ensemble' as a way to integrate the simulation predictions and expand upon the deposited NMR structures. Unbiased μs-scale atomistic MD could become a technique routinely complementing the NMR measurements of protein-RNA complexes.
Zobrazit více v PubMed
Venter J.C., Adams M.D., Myers E.W., Li P.W., Mural R.J., Sutton G.G., Smith H.O., Yandell M., Evans C.A., Holt R.A., et al. The sequence of the human genome. Science. 2001;291:1304–1351. PubMed
Daubner G.M., Cléry A., Allain F.H.T. RRM–RNA recognition: NMR or crystallography…and new findings. Curr. Opin. Struct. Biol. 2013;23:100–108. PubMed
Muto Y., Yokoyama S. Structural insight into RNA recognition motifs: versatile molecular lego building blocks for biological systems. Wiley Interdiscip. Rev.: RNA. 2012;3:229–246. PubMed
Kielkopf C.L., Lücke S., Green M.R. U2AF homology motifs: protein recognition in the RRM world. Genes Dev. 2004;18:1513–1526. PubMed PMC
Cléry A., Blatter M., Allain F.H.T. RNA recognition motifs: boring? Not quite. Curr. Opin. Struct. Biol. 2008;18:290–298. PubMed
Burd C.G., Dreyfuss G. Conserved structures and diversity of functions of RNA-binding proteins. Science. 1994;265:615–621. PubMed
Afroz T., Cienikova Z., Cléry A., Allain F.H.T. One, two, three, four! How multiple RRMs read the genome sequence. In: Woodson SA, Allain FHT, editors. Methods Enzymol. Vol. 558. Academic Press; 2015. pp. 235–278. PubMed
Mazza C., Segref A., Mattaj I.W., Cusack S. Large-scale induced fit recognition of an m(7)GpppG cap analogue by the human nuclear cap-binding complex. EMBO J. 2002;21:5548–5557. PubMed PMC
Johansson C., Finger L.D., Trantirek L., Mueller T.D., Kim S., Laird-Offringa I.A., Feigon J. Solution structure of the complex formed by the two N-terminal RNA-binding domains of nucleolin and a pre-rRNA target. J. Mol. Biol. 2004;337:799–816. PubMed
Allain F.H.T., Bouvet P., Dieckmann T., Feigon J. Molecular basis of sequence-specific recognition of pre-ribosomal RNA by nucleolin. EMBO J. 2000;19:6870–6881. PubMed PMC
Cléry A., Sinha R., Anczuków O., Corrionero A., Moursy A., Daubner G.M., Valcárcel J., Krainer A.R., Allain F.H.-T. Isolated pseudo–RNA-recognition motifs of SR proteins can regulate splicing using a noncanonical mode of RNA recognition. Proc. Natl. Acad. Sci. U.S.A. 2013;110:E2802–E2811. PubMed PMC
Tintaru A.M., Hautbergue G.M., Hounslow A.M., Hung M.-L., Lian L.-Y., Craven C.J., Wilson S.A. Structural and functional analysis of RNA and TAP binding to SF2/ASF. EMBO Rep. 2007;8:756–762. PubMed PMC
Dominguez C., Fisette J.F., Chabot B., Allain F.H.T. Structural basis of G-tract recognition and encaging by hnRNP F quasi-RRMs. Nat. Struct. Mol. Biol. 2010;17:853–861. PubMed
Nagata T., Suzuki S., Endo R., Shirouzu M., Terada T., Inoue M., Kigawa T., Kobayashi N., Güntert P., Tanaka A., et al. The RRM domain of poly(A)-specific ribonuclease has a noncanonical binding site for mRNA cap analog recognition. Nucleic Acids Res. 2008;36:4754–4767. PubMed PMC
Oubridge C., Ito N., Evans P.R., Teo C.H., Nagai K. Crystal-structure at 1.92 angstrom resolution of the RNA-binding domain of the U1A spliceosomal protein complexed with an RNA Hhirpin. Nature. 1994;372:432–438. PubMed
Oberstrass F.C., Auweter S.D., Erat M., Hargous Y., Henning A., Wenter P., Reymond L., Amir-Ahmady B., Pitsch S., Black D.L., et al. Structure of PTB bound to RNA: specific binding and implications for splicing regulation. Science. 2005;309:2054–2057. PubMed
Tsuda K., Kuwasako K., Takahashi M., Someya T., Inoue M., Terada T., Kobayashi N., Shirouzu M., Kigawa T., Tanaka A., et al. Structural basis for the sequence-specific RNA-recognition mechanism of human CUG-BP1 RRM3. Nucleic Acids Res. 2009;37:5151–5166. PubMed PMC
Cléry A., Jayne S., Benderska N., Dominguez C., Stamm S., Allain F.H.T. Molecular basis of purine-rich RNA recognition by the human SR-like protein Tra2-β1. Nat. Struct. Mol. Biol. 2011;18:443–450. PubMed
Šponer J., Banáš P., Jurečka P., Zgarbová M., Kührová P., Havrila M., Krepl M., Stadlbauer P., Otyepka M. Molecular dynamics simulations of nucleic acids. From tetranucleotides to the ribosome. J. Phys. Chem. Lett. 2014;5:1771–1782. PubMed
Reyes C.M., Kollman P.A. Structure and thermodynamics of RNA-protein binding: using molecular dynamics and free energy analyses to calculate the free energies of binding and conformational change. J. Mol. Biol. 2000;297:1145–1158. PubMed
Blakaj D.M., McConnell K.J., Beveridge D.L., Baranger A.M. Molecular dynamics and thermodynamics of protein–RNA interactions: mutation of a conserved aromatic residue modifies stacking interactions and structural adaptation in the U1A-stem Loop 2 RNA complex. J. Am. Chem. Soc. 2001;123:2548–2551. PubMed
Law M.J., Linde M.E., Chambers E.J., Oubridge C., Katsamba P.S., Nilsson L., Haworth I.S., Laird-Offringa I.A. The role of positively charged amino acids and electrostatic interactions in the complex of U1A protein and U1 hairpin II RNA. Nucleic Acids Res. 2006;34:275–285. PubMed PMC
Kormos B.L., Pieniazek S.N., Beveridge D.L., Baranger A.M. U1A protein-stem loop 2 RNA recognition: prediction of structural differences from protein mutations. Biopolymers. 2011;95:591–606. PubMed PMC
Kurisaki I., Takayanagi M., Nagaoka M. Combined mechanism of conformational selection and induced fit in U1A–RNA molecular recognition. Biochemistry. 2014;53:3646–3657. PubMed
Krepl M., Havrila M., Stadlbauer P., Banas P., Otyepka M., Pasulka J., Stefl R., Sponer J. Can we execute stable microsecond-scale atomistic simulations of protein–RNA complexes? J. Chem. Theory Comput. 2015;11:1220–1243. PubMed
Guo J.X., Gmeiner W.H. Molecular dynamics simulation of the human U2B '' protein complex with U2 snRNA hairpin IV in aqueous solution. Biophys. J. 2001;81:630–642. PubMed PMC
Schmid N., Zagrovic B., van Gunsteren W.F. Mechanism and thermodynamics of binding of the polypyrimidine tract binding protein to RNA. Biochemistry. 2007;46:6500–6512. PubMed
Clingman C.C., Deveau L.M., Hay S.A., Genga R.M., Shandilya S.M.D., Massi F., Ryder S.P. Allosteric inhibition of a stem cell RNA-binding protein by an intermediary metabolite. Elife. 2014;3:e02848. PubMed PMC
Schmid N., Eichenberger A.P., Choutko A., Riniker S., Winger M., Mark A.E., van Gunsteren W.F. Definition and testing of the GROMOS force-field versions 54A7 and 54B7. Eur. Biophys. J. Biophys. Lett. 2011;40:843–856. PubMed
Palazzesi F., Prakash M.K., Bonomi M., Barducci A. Accuracy of current all-atom force-fields in modeling protein disordered states. J. Chem. Theory Comput. 2015;11:2–7. PubMed
Beauchamp K.A., Lin Y.-S., Das R., Pande V.S. Are protein force fields getting better? A systematic benchmark on 524 diverse NMR measurements. J. Chem. Theory Comput. 2012;8:1409–1414. PubMed PMC
Georgoulia P.S., Glykos N.M. Using J-coupling constants for force field validation: application to hepta-alanine. J. Phys. Chem. B. 2011;115:15221–15227. PubMed
Aliev A.E., Courtier-Murias D. Experimental verification of force fields for molecular dynamics simulations using Gly-Pro-Gly-Gly. J. Phys. Chem. B. 2010;114:12358–12375. PubMed
Condon D.E., Kennedy S.D., Mort B.C., Kierzek R., Yildirim I., Turner D.H. Stacking in RNA: NMR of four tetramers benchmark molecular dynamics. J. Chem. Theory Comput. 2015;11:2729–2742. PubMed PMC
Bergonzo C., Henriksen N.M., Roe D.R., Swails J.M., Roitberg A.E., Cheatham T.E. Multidimensional replica exchange molecular dynamics yields a converged ensemble of an RNA tetranucleotide. J. Chem. Theory Comput. 2014;10:492–499. PubMed PMC
Giambaşu G.M., York D.M., Case D.A. Structural fidelity and NMR relaxation analysis in a prototype RNA hairpin. RNA. 2015;21:963–974. PubMed PMC
Huang J., MacKerell A.D. CHARMM36 all-atom additive protein force field: validation vased on comparison to NMR data. J. Comput. Chem. 2013;34:2135–2145. PubMed PMC
Li D.-W., Brüschweiler R. Protocol to make protein NMR structures amenable to stable long time scale molecular dynamics simulations. J. Chem. Theory Comput. 2014;10:1781–1787. PubMed
Lindorff-Larsen K., Piana S., Palmo K., Maragakis P., Klepeis J.L., Dror R.O., Shaw D.E. Improved side-chain torsion potentials for the amber ff99SB protein force field. Proteins: Struct., Funct., Bioinf. 2010;78:1950–1958. PubMed PMC
Hansen N., Heller F., Schmid N., van Gunsteren W. Time-averaged order parameter restraints in molecular dynamics simulations. J. Biomol. NMR. 2014;60:169–187. PubMed
Allison J.R., Hertig S., Missimer J.H., Smith L.J., Steinmetz M.O., Dolenc J. Probing the structure and dynamics of proteins by combining molecular dynamics simulations and experimental NMR data. J. Chem. Theory Comput. 2012;8:3430–3444. PubMed
Henriksen N., Davis D., Cheatham Iii T. Molecular dynamics re-refinement of two different small RNA loop structures using the original NMR data suggest a common structure. J. Biomol. NMR. 2012;53:321–339. PubMed PMC
Auweter S.D., Fasan R., Reymond L., Underwood J.G., Black D.L., Pitsch S., Allain F.H.T. Molecular basis of RNA recognition by the human alternative splicing factor Fox-1. EMBO J. 2006;25:163–173. PubMed PMC
Brudno M., Gelfand M.S., Spengler S., Zorn M., Dubchak I., Conboy J.G. Computational analysis of candidate intron regulatory elements for tissue-specific alternative pre-mRNA splicing. Nucleic Acids Res. 2001;29:2338–2348. PubMed PMC
Hodgkin J., Zellan J.D., Albertson D.G. Identification of a candidate primary sex determination locus, Fox-1, on the X-chromosome of Caenorhabditis elegans. Development. 1994;120:3681–3689. PubMed
Nakahata S., Kawamoto S. Tissue-dependent isoforms of mammalian Fox-1 homologs are associated with tissue-specific splicing activities. Nucleic Acids Res. 2005;33:2078–2089. PubMed PMC
Underwood J.G., Boutz P.L., Dougherty J.D., Stoilov P., Black D.L. Homologues of the Caenorhabditis elegans Fox-1 protein are neuronal splicing regulators in mammals. Mol. Cell. Biol. 2005;25:10005–10016. PubMed PMC
Birney E., Kumar S., Krainer A.R. Analysis of the RNA-recognition motif and RS and RGG domains: conservation in metazoan pre-mRNA splicing factors. Nucleic Acids Res. 1993;21:5803–5816. PubMed PMC
Long J.C., Caceres J.F. The SR protein family of splicing factors: master regulators of gene expression. Biochem. J. 2009;417:15–27. PubMed
Soret J., Gabut M., Tazi J. SR proteins as potential targets for therapy. In: Jeanteur P, editor. Alternative Splicing and Disease. Vol. 44. Berlin, Heidelberg: Springer; 2006. pp. 65–87. PubMed
Wang J., Takagaki Y., Manley J.L. Targeted disruption of an essential vertebrate gene: ASF/SF2 is required for cell viability. Genes Dev. 1996;10:2588–2599. PubMed
Longman D., Johnstone I.L., Cáceres J.F. Functional characterization of SR and SR-related genes in Caenorhabditis elegans. EMBO J. 2000;19:1625–1637. PubMed PMC
Case D.A.V.B., Berryman J.T., Betz R.M., Cai Q., Cerutti D.S., Cheatham T.E. III, Darden T.A., Duke R.E., Gohlke H., Goetz A.W., et al. San Francisco: University of California; 2014.
Cornell W.D., Cieplak P., Bayly C.I., Gould I.R., Merz K.M., Ferguson D.M., Spellmeyer D.C., Fox T., Caldwell J.W., Kollman P.A. A 2nd generation force-field for the simulation of proteins, nucleic-acids, and organic-molecules. J. Am. Chem. Soc. 1995;117:5179–5197.
Wang J.M., Cieplak P., Kollman P.A. How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules? J. Comput. Chem. 2000;21:1049–1074.
Perez A., Marchan I., Svozil D., Sponer J., Cheatham T.E., Laughton C.A., Orozco M. Refinenement of the AMBER force field for nucleic acids: improving the description of alpha/Gamma Conformers. Biophys. J. 2007;92:3817–3829. PubMed PMC
Banas P., Hollas D., Zgarbova M., Jurecka P., Orozco M., Cheatham T.E., Sponer J., Otyepka M. Performance of molecular mechanics force fields for RNA simulations: stability of UUCG and GNRA hairpins. J. Chem. Theory Comput. 2010;6:3836–3849. PubMed PMC
Zgarbova M., Otyepka M., Sponer J., Mladek A., Banas P., Cheatham T.E., Jurecka P. Refinement of the Cornell et al. nucleic acids force field based on reference quantum chemical calculations of glycosidic torsion profiles. J. Chem. Theory Comput. 2011;7:2886–2902. PubMed PMC
Hornak V., Abel R., Okur A., Strockbine B., Roitberg A., Simmerling C. Comparison of multiple amber force fields and development of improved protein backbone parameters. Proteins: Struct., Funct., Bioinf. 2006;65:712–725. PubMed PMC
Maier J.A., Martinez C., Kasavajhala K., Wickstrom L., Hauser K., Simmerling C. ff14SB: improving the accuracy of protein side chain and backbone parameters from ff99SB. J. Chem. Theory Comput. 2015;11:3696–3713. PubMed PMC
Berendsen H.J.C., Grigera J.R., Straatsma T.P. The missing term in effective pair potentials. J. Phys. Chem. 1987;91:6269–6271.
Joung I.S., Cheatham T.E. Determination of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations. J. Phys. Chem. B. 2008;112:9020–9041. PubMed PMC
Salomon-Ferrer R., Götz A.W., Poole D., Le Grand S., Walker R.C. Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle mesh Ewald. J. Chem. Theory Comput. 2013;9:3878–3888. PubMed
Le Grand S., Götz A.W., Walker R.C. SPFP: speed without compromise—a mixed precision model for GPU accelerated molecular dynamics simulations. Comput. Phys. Commun. 2013;184:374–380.
Darden T., York D., Pedersen L. Particle mesh Ewald – an n.log(n) method for Ewald sums in large systems. J. Chem. Phys. 1993;98:10089–10092.
Essmann U., Perera L., Berkowitz M.L., Darden T., Lee H., Pedersen L.G. A smooth particle mesh Ewald method. J. Chem. Phys. 1995;103:8577–8593.
Ryckaert J.P., Ciccotti G., Berendsen H.J.C. Numerical-integration of Cartesian equations of motion of a system with constraints – molecular-dynamics of n-alkanes. J. Comput. Phys. 1977;23:327–341.
Berendsen H.J.C., Postma J.P.M., Vangunsteren W.F., Dinola A., Haak J.R. Molecular-dynamics with coupling to an external bath. J. Chem. Phys. 1984;81:3684–3690.
Rosta E., Buchete N.-V., Hummer G. Thermostat artifacts in replica exchange molecular dynamics simulations. J. Chem. Theory Comput. 2009;5:1393–1399. PubMed PMC
Harvey S.C., Tan R.K.Z., Cheatham T.E. The flying ice cube: velocity rescaling in molecular dynamics leads to violation of energy equipartition. J. Comput. Chem. 1998;19:726–740.
Krepl M., Reblova K., Koca J., Sponer J. Bioinformatics and molecular dynamics simulation study of L1 stalk non-canonical rRNA elements: kink-turns, loops, and tetraloops. J. Phys. Chem. B. 2013;117:5540–5555. PubMed
Estarellas C., Otyepka M., Koca J., Banas P., Krepl M., Sponer J. Molecular dynamic simulations of protein/RNA complexes: CRISPR/Csy4 endoribonuclease. Biochim. Biophys. Acta, Gen. Subj. 2015;1850:1072–1090. PubMed
Roe D.R., Cheatham T.E. PTRAJ and CPPTRAJ: software for processing and analysis of molecular dynamics trajectory data. J. Chem. Theory Comput. 2013;9:3084–3095. PubMed
Humphrey W., Dalke A., Schulten K. VMD: visual molecular dynamics. J. Mol. Graph. 1996;14:33–38. PubMed
Merritt E.A., Bacon D.J. Raster3D: photorealistic molecular graphics. In: Carter CW, Sweet RM, editors. Macromolecular Crystallography, Pt B. Vol. 277. San Diego: Elsevier Academic Press Inc; 1997. pp. 505–524. PubMed
Steinbrecher T., Mobley D.L., Case D.A. Nonlinear scaling schemes for Lennard-Jones interactions in free energy calculations. J. Chem. Phys. 2007;127:214108. PubMed
Lawrenz M., Baron R., McCammon J.A. Independent-trajectories thermodynamic-integration free-energy changes for biomolecular systems: determinants of H5N1 avian influenza virus neuraminidase inhibition by Peramivir. J. Chem. Theory Comput. 2009;5:1106–1116. PubMed PMC
Krepl M., Otyepka M., Banas P., Sponer J. Effect of guanine to inosine substitution on stability of canonical DNA and RNA duplexes: molecular dynamics thermodynamics integration study. J. Phys. Chem. B. 2013;117:1872–1879. PubMed
Leontis N.B., Stombaugh J., Westhof E. The non-Watson-Crick base pairs and their associated isostericity matrices. Nucleic Acids Res. 2002;30:3497–3531. PubMed PMC
Steinbrecher T., Joung I., Case D.A. Soft-core potentials in thermodynamic integration: comparing one- and two-step transformations. J. Comput. Chem. 2011;32:3253–3263. PubMed PMC
Sponer J., Mladek A., Sponer J.E., Svozil D., Zgarbova M., Banas P., Jurecka P., Otyepka M. The DNA and RNA sugar-phosphate backbone emerges as the key player. An overview of quantum-chemical, structural biology and simulation studies. Phys. Chem. Chem. Phys. 2012;14:15257–15277. PubMed
Sponer J., Cang X.H., Cheatham T.E. Molecular dynamics simulations of G-DNA and perspectives on the simulation of nucleic acid structures. Methods. 2012;57:25–39. PubMed PMC
Rocklin G.J., Mobley D.L., Dill K.A., Hünenberger P.H. Calculating the binding free energies of charged species based on explicit-solvent simulations employing lattice-sum methods: an accurate correction scheme for electrostatic finite-size effects. J. Chem. Phys. 2013;139:184103. PubMed PMC
Caves L.S.D., Evanseck J.D., Karplus M. Locally accessible conformations of proteins: multiple molecular dynamics simulations of crambin. Protein Sci. 1998;7:649–666. PubMed PMC
MD simulations reveal the basis for dynamic assembly of Hfq-RNA complexes
RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview