The conserved protein Hfq is a key factor in the RNA-mediated control of gene expression in most known bacteria. The transient intermediates Hfq forms with RNA support intricate and robust regulatory networks. In Pseudomonas, Hfq recognizes repeats of adenine-purine-any nucleotide (ARN) in target mRNAs via its distal binding side, and together with the catabolite repression control (Crc) protein, assembles into a translation-repression complex. Earlier experiments yielded static, ensemble-averaged structures of the complex, but details of its interface dynamics and assembly pathway remained elusive. Using explicit solvent atomistic molecular dynamics simulations, we modeled the extensive dynamics of the Hfq-RNA interface and found implications for the assembly of the complex. We predict that syn/anti flips of the adenine nucleotides in each ARN repeat contribute to a dynamic recognition mechanism between the Hfq distal side and mRNA targets. We identify a previously unknown binding pocket that can accept any nucleotide and propose that it may serve as a 'status quo' staging point, providing nonspecific binding affinity, until Crc engages the Hfq-RNA binary complex. The dynamical components of the Hfq-RNA recognition can speed up screening of the pool of the surrounding RNAs, participate in rapid accommodation of the RNA on the protein surface, and facilitate competition among different RNAs. The register of Crc in the ternary assembly could be defined by the recognition of a guanine-specific base-phosphate interaction between the first and last ARN repeats of the bound RNA. This dynamic substrate recognition provides structural rationale for the stepwise assembly of multicomponent ribonucleoprotein complexes nucleated by Hfq-RNA binding.

Department of Biochemistry University of Cambridge Cambridge United Kingdom

Department of Biochemistry University of Cambridge Cambridge United Kingdom; MRC LMB Cambridge United Kingdom

Institute of Biophysics of the Czech Academy of Sciences Brno Czech Republic

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Vogel J., Luisi B.F. Hfq and its constellation of RNA. Nat. Rev. Microbiol. 2011;9:578–589. PubMed PMC

Hoekzema M., Romilly C., Holmqvist E., Wagner E.G.H. Hfq-dependent mRNA unfolding promotes sRNA-based inhibition of translation. EMBO J. 2019;38 PubMed PMC

Azam M.S., Vanderpool C.K. Translational regulation by bacterial small RNAs via an unusual Hfq-dependent mechanism. Nucleic Acids Res. 2017;46:2585–2599. PubMed PMC

Kwiatkowska J., Wroblewska Z., Johnson K.A., Olejniczak M. The binding of class II sRNA MgrR to two different sites on matchmaker protein Hfq enables efficient competition for Hfq and annealing to regulated mRNAs. RNA. 2018;24:1761–1784. PubMed PMC

Vecerek B., Moll I., BLASI U. Translational autocontrol of the Escherichia coli Hfq RNA chaperone gene. RNA. 2005;11:976–984. PubMed PMC

Sonnleitner E., Wulf A., Campagne S., Pei X.-Y., Wolfinger M.T., Forlani G., Prindl K., Abdou L., Resch A., Allain F.H.-T., Luisi B.F., Urlaub H., Bläsi U. Interplay between the catabolite repression control protein Crc, Hfq and RNA in Hfq-dependent translational regulation in Pseudomonas aeruginosa. Nucleic Acids Res. 2018;46:1470–1485. PubMed PMC

Schumacher M.A., Pearson R.F., Møller T., Valentin-Hansen P., Brennan R.G. Structures of the pleiotropic translational regulator Hfq and an Hfq–RNA complex: A bacterial Sm-like protein. EMBO J. 2002;21:3546–3556. PubMed PMC

Link T.M., Valentin-Hansen P., Brennan R.G. Structure of Escherichia coli Hfq bound to polyriboadenylate RNA. Proc. Natl. Acad. Sci. U. S. A. 2009;106:19292–19297. PubMed PMC

Mikulecky P.J., Kaw M.K., Brescia C.C., Takach J.C., Sledjeski D.D., Feig A.L. Escherichia coli Hfq has distinct interaction surfaces for DsrA, rpoS and poly(A) RNAs. Nat. Struct. Mol. Biol. 2004;11:1206–1214. PubMed PMC

Brennan R.G., Link T.M. Hfq structure, function and ligand binding. Curr. Opin. Microbiol. 2007;10:125–133. PubMed

Santiago-Frangos A., Kavita K., Schu D.J., Gottesman S., Woodson S.A. C-terminal domain of the RNA chaperone Hfq drives sRNA competition and release of target RNA. Proc. Natl. Acad. Sci. U. S. A. 2016;113:E6089–E6096. PubMed PMC

Wen B., Wang W., Zhang J., Gong Q., Shi Y., Wu J., Zhang Z. Structural and dynamic properties of the C-terminal region of the Escherichia coli RNA chaperone Hfq: Integrative experimental and computational studies. Phys. Chem. Chem. Phys. 2017;19:21152–21164. PubMed

Robinson K.E., Orans J., Kovach A.R., Link T.M., Brennan R.G. Mapping Hfq-RNA interaction surfaces using tryptophan fluorescence quenching. Nucleic Acids Res. 2014;42:2736–2749. PubMed PMC

Sonnleitner E., Bläsi U. Regulation of Hfq by the RNA CrcZ in Pseudomonas aeruginosa carbon catabolite repression. PLoS Genet. 2014;10 PubMed PMC

Van den Bossche A., Ceyssens P.-J., De Smet J., Hendrix H., Bellon H., Leimer N., Wagemans J., Delattre A.-S., Cenens W., Aertsen A., Landuyt B., Minakhin L., Severinov K., Noben J.-P., Lavigne R. Systematic identification of hypothetical bacteriophage proteins targeting key protein complexes of Pseudomonas aeruginosa. J. Proteome Res. 2014;13:4446–4456. PubMed

Milojevic T., Grishkovskaya I., Sonnleitner E., Djinovic-Carugo K., Bläsi U. The Pseudomonas aeruginosa catabolite repression control protein Crc is devoid of RNA binding activity. PLoS One. 2013;8 PubMed PMC

Wolff J.A., MacGregor C.H., Eisenberg R.C., Phibbs P.V. Isolation and characterization of catabolite repression control mutants of Pseudomonas aeruginosa PAO. J. Bacteriol. 1991;173:4700–4706. PubMed PMC

Sonnleitner E., Abdou L., Haas D. Small RNA as global regulator of carbon catabolite repression in Pseudomonas aeruginosa. Proc. Natl. Acad. Sci. U. S. A. 2009;106:21866–21871. PubMed PMC

Pei X.Y., Dendooven T., Sonnleitner E., Chen S., Bläsi U., Luisi B.F. Architectural principles for Hfq/Crc-mediated regulation of gene expression. Elife. 2019;8 PubMed PMC

Nikulin A., Stolboushkina E., Perederina A., Vassilieva I., Blaesi U., Moll I., Kachalova G., Yokoyama S., Vassylyev D., Garber M., Nikonov S. Structure of Pseudomonas aeruginosa Hfq protein. Acta Crystallogr. D Biol. Crystallogr. 2005;61:141–146. PubMed

Šponer J., Bussi G., Krepl M., Banáš P., Bottaro S., Cunha R.A., Gil-Ley A., Pinamonti G., Poblete S., Jurečka P., Walter N.G., Otyepka M. RNA structural dynamics as captured by molecular simulations: A comprehensive overview. Chem. Rev. 2018;118:4177–4338. PubMed PMC

Nerenberg P.S., Head-Gordon T. New developments in force fields for biomolecular simulations. Curr. Opin. Struct. Biol. 2018;49:129–138. PubMed

Campagne S., Krepl M., Sponer J., Allain F.H.T. Chapter fourteen - combining NMR spectroscopy and molecular dynamic simulations to solve and analyze the structure of protein–RNA complexes. In: Wand A.J., editor. Methods Enzymol. Academic Press; Cambridge, MA: 2019. pp. 393–422. PubMed

Borišek J., Saltalamacchia A., Gallì A., Palermo G., Molteni E., Malcovati L., Magistrato A. Disclosing the impact of carcinogenic SF3b mutations on pre-mRNA recognition via all-atom simulations. Biomolecules. 2019;9 PubMed PMC

Sharma M., Sharma S., Alawada A. Understanding the binding specificities of mRNA targets by the mammalian quaking protein. Nucleic Acids Res. 2019;47:10564–10579. PubMed PMC

Casalino L., Palermo G., Spinello A., Rothlisberger U., Magistrato A. All-atom simulations disentangle the functional dynamics underlying gene maturation in the intron lariat spliceosome. Proc. Natl. Acad. Sci. U. S. A. 2018;115:6584–6589. PubMed PMC

Palermo G., Casalino L., Magistrato A., Andrew McCammon J. Understanding the mechanistic basis of non-coding RNA through molecular dynamics simulations. J. Struct. Biol. 2019;206:267–279. PubMed PMC

Sharma M., Anirudh C.R. Mechanism of mRNA-STAR domain interaction: Molecular dynamics simulations of mammalian quaking STAR protein. Sci. Rep. 2017;7 PubMed PMC

Górecka K.M., Krepl M., Szlachcic A., Poznański J., Šponer J., Nowotny M. RuvC uses dynamic probing of the holliday junction to achieve sequence specificity and efficient resolution. Nat. Commun. 2019;10 PubMed PMC

Ripin N., Boudet J., Duszczyk M.M., Hinniger A., Faller M., Krepl M., Gadi A., Schneider R.J., Šponer J., Meisner-Kober N.C., Allain F.H.-T. Molecular basis for AU-rich element recognition and dimerization by the HuR C-terminal RRM. Proc. Natl. Acad. Sci. U. S. A. 2019;116:2935–2944. PubMed PMC

Borkar A.N., Bardaro M.F., Camilloni C., Aprile F.A., Varani G., Vendruscolo M. Structure of a low-population binding intermediate in protein-RNA recognition. Proc. Natl. Acad. Sci. U. S. A. 2016;113:7171–7176. PubMed PMC

Fender A., Elf J., Hampel K., Zimmermann B., Wagner E.G.H. RNAs actively cycle on the Sm-like protein Hfq. Genes Dev. 2010;24:2621–2626. PubMed PMC

Wagner E.G.H. Cycling of RNAs on Hfq. RNA Biol. 2013;10:619–626. PubMed PMC

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. Theor. Comput. 2015;11:1220–1243. PubMed

Bergonzo C., Henriksen N.M., Roe D.R., Cheatham T.E. Highly sampled tetranucleotide and tetraloop motifs enable evaluation of common RNA force fields. RNA. 2015;21:1578–1590. PubMed PMC

Richardson J.S., Schneider B., Murray L.W., Kapral G.J., Immormino R.M., Headd J.J., Richardson D.C., Ham D., Hershkovits E., Williams L.D., Keating K.S., Pyle A.M., Micallef D., Westbrook J., Berman H.M. RNA backbone: Consensus all-angle conformers and modular string nomenclature (an RNA Ontology Consortium contribution) RNA. 2008;14:465–481. PubMed PMC

Zirbel C.L., Sponer J.E., Sponer J., Stombaugh J., Leontis N.B. Classification and energetics of the base-phosphate interactions in RNA. Nucleic Acids Res. 2009;37:4898–4918. PubMed PMC

Daubner G.M., Cléry A., Jayne S., Stevenin J., Allain F.H.-T. A syn–anti conformational difference allows SRSF2 to recognize guanines and cytosines equally well. EMBO J. 2012;31:162–174. PubMed PMC

Kligun E., Mandel-Gutfreund Y. The role of RNA conformation in RNA-protein recognition. RNA Biol. 2015;12:720–727. PubMed PMC

Schulz E.C., Seiler M., Zuliani C., Voigt F., Rybin V., Pogenberg V., Mücke N., Wilmanns M., Gibson T.J., Barabas O. Intermolecular base stacking mediates RNA-RNA interaction in a crystal structure of the RNA chaperone Hfq. Sci. Rep. 2017;7 PubMed PMC

Horstmann N., Orans J., Valentin-Hansen P., Shelburne S.A., III, Brennan R.G. Structural mechanism of Staphylococcus aureus Hfq binding to an RNA A-tract. Nucleic Acids Res. 2012;40:11023–11035. PubMed PMC

Wlodawer A., Minor W., Dauter Z., Jaskolski M. Protein crystallography for non-crystallographers, or how to get the best (but not more) from published macromolecular structures. FEBS J. 2008;275:1–21. PubMed PMC

Chou F.-C., Sripakdeevong P., Dibrov S.M., Hermann T., Das R. Correcting pervasive errors in RNA crystallography through enumerative structure prediction. Nat. Methods. 2012;10:74. PubMed PMC

Krepl M., Blatter M., Cléry A., Damberger F.F., Allain F.H.T., Sponer J. Structural study of the fox-1 RRM protein hydration reveals a role for key water molecules in RRM-RNA recognition. Nucleic Acids Res. 2017;45:8046–8063. PubMed PMC

Atakisi H., Moreau D.W., Thorne R.E. Effects of protein-crystal hydration and temperature on side-chain conformational heterogeneity in monoclinic lysozyme crystals. Acta Crystallogr. D Struct. Biol. 2018;74:264–278. PubMed PMC

Ganser L.R., Kelly M.L., Herschlag D., Al-Hashimi H.M. The roles of structural dynamics in the cellular functions of RNAs. Nat. Rev. Mol. Cell Biol. 2019;20:474–489. PubMed PMC

Santiago-Frangos A., Woodson S.A. Hfq chaperone brings speed dating to bacterial sRNA. Wiley Interdiscip. Rev. RNA. 2018;9 PubMed PMC

Krepl M., Cléry A., Blatter M., Allain F.H.T., Sponer J. Synergy between NMR measurements and MD simulations of protein/RNA complexes: Application to the RRMs, the most common RNA recognition motifs. Nucleic Acids Res. 2016;44:6452–6470. PubMed PMC

Šponer J., Leszczyński J., Hobza P. Nature of nucleic acid−base stacking: Nonempirical ab Initio and empirical potential characterization of 10 stacked base dimers. Comparison of stacked and H-bonded base pairs. J. Phys. Chem. 1996;100:5590–5596.

Šponer J., Jurečka P., Marchan I., Luque F.J., Orozco M., Hobza P. Nature of base stacking: Reference quantum-chemical stacking energies in ten unique B-DNA base-pair steps. Chemistry. 2006;12:2854–2865. PubMed

Šponer J., Riley K.E., Hobza P. Nature and magnitude of aromatic stacking of nucleic acid bases. Phys. Chem. Chem. Phys. 2008;10:2595–2610. PubMed

Sponer J., Sponer J.E., Mladek A., Jurecka P., Banas P., Otyepka M. Nature and magnitude of aromatic base stacking in DNA and RNA: Quantum chemistry, molecular mechanics, and experiment. Biopolymers. 2013;99:978–988. PubMed

Wang L., Wang W., Li F., Zhang J., Wu J., Gong Q., Shi Y. Structural insights into the recognition of the internal A-rich linker from OxyS sRNA by Escherichia coli Hfq. Nucleic Acids Res. 2015;43:2400–2411. PubMed PMC

Case IYB-SDA, Brozell S.R., Cerutti D.S., Cheatham T.E., III, Cruzeiro V.W.D., Darden T.A., Duke R.E., Ghoreishi D., Gilson M.K., Gohlke H., Goetz A.W., Greene D., Harris R., Homeyer N., Izadi S. University of California; San Francisco, San Francisco, CA: 2018. AMBER 18.

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. Theor. Comput. 2011;7:2886–2902. 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. Theor. Comput. 2015;11:3696–3713. PubMed PMC

Šponer J., Krepl M., Banáš P., Kührová P., Zgarbová M., Jurečka P., Havrila M., Otyepka M. How to understand atomistic molecular dynamics simulations of RNA and protein–RNA complexes? Wiley Interdiscip. Rev. RNA. 2017;8 PubMed

Kuhrova P., Best R., Bottaro S., Bussi G., Sponer J., Otyepka M., Banas P. Computer folding of RNA tetraloops: Identification of key force field deficiencies. J. Chem. Theor. Comput. 2016;12:4534–4548. PubMed PMC

Noel J.K., Levi M., Raghunathan M., Lammert H., Hayes R.L., Onuchic J.N., Whitford P.C. SMOG 2: A versatile software package for generating structure-based models. PLoS Comput. Biol. 2016;12 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

Krepl M., Vögele J., Kruse H., Duchardt-Ferner E., Wöhnert J., Sponer J. An intricate balance of hydrogen bonding, ion atmosphere and dynamics facilitates a seamless uracil to cytosine substitution in the U-turn of the neomycin-sensing riboswitch. Nucleic Acids Res. 2018;46:6528–6543. PubMed PMC

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.

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.

Hopkins C.W., Le Grand S., Walker R.C., Roitberg A.E. Long-time-step molecular dynamics through hydrogen mass repartitioning. J. Chem. Theor. Comput. 2015;11:1864–1874. PubMed

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

Roe D.R., Cheatham T.E. PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data. J. Chem. Theor. 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 C.W., Sweet R.M., editors. Macromolecular Crystallography, Pt B. Elsevier Academic Press Inc; San Diego, CA: 1997. pp. 505–524.

Zhao J., Kennedy S.D., Berger K.D., Turner D.H. Nuclear magnetic resonance of single-stranded RNAs and DNAs of CAAU and UCAAUC as benchmarks for molecular dynamics simulations. J. Chem. Theor. Comput. 2020;16:1968–1984. PubMed

Mlýnský V., Kührová P., Kühr T., Otyepka M., Bussi G., Banáš P., Šponer J. Fine-tuning of the AMBER RNA force field with a new term adjusting interactions of terminal nucleotides. J. Chem. Theor. Comput. 2020;16:3936–3946. PubMed

Kuhrova P., Mlynsky V., Zgarbova M., Krepl M., Bussi G., Best R.B., Otyepka M., Sponer J., Banas P. Improving the performance of the RNA amber force field by tuning the hydrogen-bonding interactions. J. Chem. Theor. Comput. 2019;15:3288–3305. PubMed PMC

Bottaro S., Bussi G., Kennedy S.D., Turner D.H., Lindorff-Larsen K. Conformational ensembles of RNA oligonucleotides from integrating NMR and molecular simulations. Sci. Adv. 2018;4 PubMed PMC

Szabla R., Havrila M., Kruse H., Šponer J. Comparative assessment of different RNA tetranucleotides from the DFT-D3 and force field perspective. J. Phys. Chem. B. 2016;120:10635–10648. PubMed

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. Theor. Comput. 2014;10:492–499. PubMed PMC

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. Theor. Comput. 2015;11:2729–2742. PubMed PMC

Banáš P., Mládek A., Otyepka M., Zgarbová M., Jurečka P., Svozil D., Lankaš F., Šponer J. Can we accurately describe the structure of adenine tracts in B-DNA? Reference quantum-chemical computations reveal overstabilization of stacking by molecular mechanics. J. Chem. Theor. Comput. 2012;8:2448–2460. PubMed

Spontaneous binding of single-stranded RNAs to RRM proteins visualized by unbiased atomistic simulations with a rescaled RNA force field