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

. 2022 Nov 28 ; 50 (21) : 12480-12496.

Jazyk angličtina Země Anglie, Velká Británie Médium print

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid36454011

Recognition of single-stranded RNA (ssRNA) by RNA recognition motif (RRM) domains is an important class of protein-RNA interactions. Many such complexes were characterized using nuclear magnetic resonance (NMR) and/or X-ray crystallography techniques, revealing ensemble-averaged pictures of the bound states. However, it is becoming widely accepted that better understanding of protein-RNA interactions would be obtained from ensemble descriptions. Indeed, earlier molecular dynamics simulations of bound states indicated visible dynamics at the RNA-RRM interfaces. Here, we report the first atomistic simulation study of spontaneous binding of short RNA sequences to RRM domains of HuR and SRSF1 proteins. Using a millisecond-scale aggregate ensemble of unbiased simulations, we were able to observe a few dozen binding events. HuR RRM3 utilizes a pre-binding state to navigate the RNA sequence to its partially disordered bound state and then to dynamically scan its different binding registers. SRSF1 RRM2 binding is more straightforward but still multiple-pathway. The present study necessitated development of a goal-specific force field modification, scaling down the intramolecular van der Waals interactions of the RNA which also improves description of the RNA-RRM bound state. Our study opens up a new avenue for large-scale atomistic investigations of binding landscapes of protein-RNA complexes, and future perspectives of such research are discussed.

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Varani G., Nagai K.. RNA recognition by RNP proteins during RNA processing. Annu. Rev. Biophys. Biomol. Struct. 1998; 27:407–445. PubMed

Chen Y., Varani G.. Protein families and RNA recognition. FEBS J. 2005; 272:2088–2097. PubMed

Hogg J.R., Collins K.. Structured non-coding RNAs and the RNP renaissance. Curr. Opin. Chem. Biol. 2008; 12:684–689. PubMed PMC

Änkö M.-L., Neugebauer K.M.. RNA protein interactions in vivo: global gets specific. Trends Biochem. Sci. 2012; 37:255–262. PubMed

Glisovic T., Bachorik J.L., Yong J., Dreyfuss G.. RNA-binding proteins and post-transcriptional gene regulation. FEBS Lett. 2008; 582:1977–1986. PubMed PMC

Stefl R., Skrisovska L., Allain F.H.T.. RNA sequence- and shape-dependent recognition by proteins in the ribonucleoprotein particle. EMBO Rep. 2005; 6:33–38. PubMed PMC

Chen Y., Varani G.. Engineering RNA-binding proteins for biology. FEBS J. 2013; 280:3734–3754. PubMed PMC

Lunde B.M., Moore C., Varani G.. RNA-binding proteins: modular design for efficient function. Nat. Rev. Mol. Cell Biol. 2007; 8:479–490. PubMed PMC

Corley M., Burns M.C., Yeo G.W.. How RNA-binding proteins interact with RNA: molecules and mechanisms. Mol. Cell. 2020; 78:9–29. PubMed PMC

Pal A., Levy Y.. Structure, stability and specificity of the binding of ssDNA and ssRNA with proteins. PLoS Comput. Biol. 2019; 15:e1006768. 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

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

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

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

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

Afroz T., Cienikova Z., Cléry A., Allain F.H.T.. One, two, three, four! How multiple RRMs read the genome sequence. Methods Enzymol. 2015; 558:235–278. PubMed

Cléry A., Krepl M., Nguyen C.K.X., Moursy A., Jorjani H., Katsantoni M., Okoniewski M., Mittal N., Zavolan M., Sponer J.et al. .. Structure of SRSF1 RRM1 bound to RNA reveals an unexpected bimodal mode of interaction and explains its involvement in SMN1 exon7 splicing. Nat. Commun. 2021; 12:428. PubMed PMC

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

Yoo J., Winogradoff D., Aksimentiev A.. Molecular dynamics simulations of DNA–DNA and DNA–protein interactions. Curr. Opin. Struct. Biol. 2020; 64:88–96. PubMed

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

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

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

Bottaro S., Gil-Ley A., Bussi G.. RNA folding pathways in stop motion. Nucleic Acids Res. 2016; 44:5883–5891. 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:eaar8521. PubMed PMC

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. Theory Comput. 2019; 15:3288–3305. PubMed PMC

Mráziková K., Mlýnský V., Kührová P., Pokorná P., Kruse H., Krepl M., Otyepka M., Banáš P., Šponer J.. UUCG RNA tetraloop as a formidable force-field challenge for MD simulations. J. Chem. Theory Comput. 2020; 16:7601–7617. PubMed

Haldar S., Kuhrova P., Banas P., Spiwok V., Sponer J., Hobza P., Otyepka M.. Insights into stability and folding of GNRA and UNCG tetra loops revealed by microsecond molecular dynamics and well-tempered metadynamics. J. Chem. Theory Comput. 2015; 11:3866–3877. 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

Chen A.A., García A.E.. High-resolution reversible folding of hyperstable RNA tetraloops using molecular dynamics simulations. Proc. Natl Acad. Sci. USA. 2013; 110:16820–16825. 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

Tubbs J.D., Condon D.E., Kennedy S.D., Hauser M., Bevilacqua P.C., Turner D.H.. The nuclear magnetic resonance of CCCC RNA reveals a right-handed helix, and revised parameters for AMBER force field torsions improve structural predictions from molecular dynamics. Biochemistry. 2013; 52:996–1010. 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. Theory Comput. 2015; 11:2729–2742. PubMed PMC

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. Theory 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. Theory Comput. 2020; 16:3936–3946. PubMed

Fröhlking T., Mlýnský V., Janeček M., Kührová P., Krepl M., Banáš P., Šponer J., Bussi G.. Automatic learning of hydrogen-bond fixes in an AMBER RNA force field. J. Chem. Theory Comput. 2022; 18:4490–4502. PubMed PMC

Yang C., Lim M., Kim E., Pak Y.. Predicting RNA structures via a simple van der Waals correction to an all-atom force field. J. Chem. Theory Comput. 2017; 13:395–399. PubMed

Yoo J., Aksimentiev A.. New tricks for old dogs: improving the accuracy of biomolecular force fields by pair-specific corrections to non-bonded interactions. Phys. Chem. Chem. Phys. 2018; 20:8432–8449. PubMed PMC

Qiu Y., Shan W., Zhang H.. Force field benchmark of amino acids. 3. Hydration with scaled Lennard–Jones interactions. J. Chem. Inf. Model. 2021; 61:3571–3582. PubMed

Siebenmorgen T., Zacharias M.. Efficient refinement and free energy scoring of predicted protein–protein complexes using replica exchange with repulsive scaling. J. Chem. Inf. Model. 2020; 60:5552–5562. PubMed

Leherte L., Vercauteren D.P.. Reduced point charge models of proteins: effect of protein–water interactions in molecular dynamics simulations of ubiquitin systems. J. Phys. Chem. B. 2017; 121:9771–9784. PubMed

Li Z., Buck M.. Modified potential functions result in enhanced predictions of a protein complex by all-atom molecular dynamics simulations, confirming a stepwise association process for native protein–protein interactions. J. Chem. Theory Comput. 2019; 15:4318–4331. PubMed

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

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

Pabis M., Popowicz G.M., Stehle R., Fernández-Ramos D., Asami S., Warner L., García-Mauriño S.M., Schlundt A., Martínez-Chantar M.L., Díaz-Moreno I.et al. .. HuR biological function involves RRM3-mediated dimerization and RNA binding by all three RRMs. Nucleic Acids Res. 2018; 47:1011–1029. PubMed PMC

Cléry A., Sinha R., Anczuków O., Corrionero A., Moursy A., Daubner G.M., Valcárcel J., Krainer A.R., Allain F.H.. Isolated pseudo–RNA-recognition motifs of SR proteins can regulate splicing using a noncanonical mode of RNA recognition. Proc. Natl Acad. Sci. USA. 2013; 110:E2802–E2811. PubMed PMC

Woodson S.A. Compact intermediates in RNA folding. Annu. Rev. Biophys. 2010; 39:61–77. PubMed PMC

Case D.A., Aktulga H.M., Belfon K., Ben-Shalom I.Y., Brozell S.R., Cerutti D.S., Cheatham T.E. I, Cisneros G.A., Cruzeiro V.W.D., Darden T.A.et al. .. AMBER 20. 2021; San Francisco: University of California.

Duchardt-Ferner E., Gottstein-Schmidtke S.R., Weigand J.E., Ohlenschläger O., Wurm J.-P., Hammann C., Suess B., Wöhnert J.. What a difference an OH makes: conformational dynamics as the basis for the ligand specificity of the neomycin-sensing riboswitch. Angew. Chem. Int. Ed. 2016; 55:1527–1530. PubMed

Steinbrecher T., Latzer J., Case D.A.. Revised AMBER parameters for bioorganic phosphates. J. Chem. Theory Comput. 2012; 8:4405–4412. PubMed PMC

Mlynsky V., Kuhrova P., Zgarbova M., Jurecka P., Walter N.G., Otyepka M., Sponer J., Banas P.. Reactive conformation of the active site in the hairpin ribozyme achieved by molecular dynamics simulations with epsilon/zeta force field reparametrizations. J. Phys. Chem. B. 2015; 119:4220–4229. 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. Theory Comput. 2016; 12:4534–4548. PubMed PMC

Tan D., Piana S., Dirks R.M., Shaw D.E.. RNA force field with accuracy comparable to state-of-the-art protein force fields. Proc. Natl Acad. Sci. USA. 2018; 115:E1346–E1355. 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

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

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:e1405. PubMed

Krepl M., Dendooven T., Luisi B.F., Sponer J.. MD simulations reveal the basis for dynamic assembly of Hfq–RNA complexes. J. Biol. Chem. 2021; 296:e100656. PubMed PMC

Krepl M., Damberger F.F., von Schroetter C., Theler D., Pokorná P., Allain F.H.T., Šponer J.. Recognition of N6-methyladenosine by the YTHDC1 YTH domain studied by molecular dynamics and NMR spectroscopy: the role of hydration. J. Phys. Chem. B. 2021; 125:7691–7705. PubMed

Berendsen H.J.C., Grigera J.R., Straatsma T.P.. The missing term in effective pair potentials. J. Phys. Chem. 1987; 91:6269–6271.

Izadi S., Anandakrishnan R., Onufriev A.V.. Building water models: a different approach. J. Phys. Chem. Lett. 2014; 5:3863–3871. PubMed PMC

Tian C., Kasavajhala K., Belfon K.A.A., Raguette L., Huang H., Migues A.N., Bickel J., Wang Y., Pincay J., Wu Q.et al. .. ff19SB: amino-acid-specific protein backbone parameters trained against quantum mechanics energy surfaces in solution. J. Chem. Theory Comput. 2020; 16:528–552. PubMed

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. Theory 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:e10089.

Wang L., Friesner R.A., Berne B.J.. Replica exchange with solute scaling: a more efficient version of replica exchange with solute tempering (REST2). J. Phys. Chem. B. 2011; 115:9431–9438. PubMed PMC

Zhang C., Lu C., Jing Z., Wu C., Piquemal J.-P., Ponder J.W., Ren P.. AMOEBA polarizable atomic multipole force field for nucleic acids. J. Chem. Theory Comput. 2018; 14:2084–2108. PubMed PMC

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

Weiser J., Shenkin P.S., Still W.C.. Approximate atomic surfaces from linear combinations of pairwise overlaps (LCPO). J. Comput. Chem. 1999; 20:217–230.

Lu X.-J., Olson W.K.. 3DNA: a software package for the analysis, rebuilding and visualization of three-dimensional nucleic acid structures. Nucleic Acids Res. 2003; 31:5108–5121. PubMed PMC

Rodriguez A., Laio A.. Clustering by fast search and find of density peaks. Science. 2014; 344:1492–1496. PubMed

Bottaro S., Di Palma F., Bussi G.. The role of nucleobase interactions in RNA structure and dynamics. Nucleic Acids Res. 2014; 42:13306–13314. PubMed PMC

de Beauchene I.C., de Vries S.J., Zacharias M.. Fragment-based modelling of single stranded RNA bound to RNA recognition motif containing proteins. Nucleic Acids Res. 2016; 44:4565–4580. PubMed PMC

Robustelli P., Piana S., Shaw D.E.. Mechanism of coupled folding-upon-binding of an intrinsically disordered protein. J. Am. Chem. Soc. 2020; 142:11092–11101. PubMed

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

Toba G., White K.. The third RNA recognition motif of Drosophila ELAV protein has a role in multimerization. Nucleic Acids Res. 2008; 36:1390–1399. PubMed PMC

Hayashi T., Oshima H., Mashima T., Nagata T., Katahira M., Kinoshita M.. Binding of an RNA aptamer and a partial peptide of a prion protein: crucial importance of water entropy in molecular recognition. Nucleic Acids Res. 2014; 42:6861–6875. PubMed PMC

Hayashi T., Matsuda T., Nagata T., Katahira M., Kinoshita M.. Mechanism of protein–RNA recognition: analysis based on the statistical mechanics of hydration. Phys. Chem. Chem. Phys. 2018; 20:9167–9180. PubMed

Shoemaker B.A., Portman J.J., Wolynes P.G.. Speeding molecular recognition by using the folding funnel: the fly-casting mechanism. Proc. Natl Acad. Sci. USA. 2000; 97:8868–8873. PubMed PMC

Yu S., Wang S., Larson R.G.. Proteins searching for their target on DNA by one-dimensional diffusion: overcoming the ‘speed–stability’ paradox. J. Biol. Phys. 2013; 39:565–586. PubMed PMC

Dai L., Xu Y., Du Z., Su X.-d., Yu J.. Revealing atomic-scale molecular diffusion of a plant-transcription factor WRKY domain protein along DNAM. Proc. Natl Acad. Sci. USA. 2021; 118:e2102621118. 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

Dimitrova-Paternoga L., Jagtap P.K.A., Chen P.-C., Hennig J.. Integrative structural biology of protein–RNA complexes. Structure. 2020; 28:6–28. PubMed

Simmel F.C., Yurke B., Singh H.R.. Principles and applications of nucleic acid strand displacement reactions. Chem. Rev. 2019; 119:6326–6369. PubMed

Hong F., Šulc P.. An emergent understanding of strand displacement in RNA biology. J. Struct. Biol. 2019; 207:241–249. PubMed

Bushhouse D.Z., Choi E.K., Hertz L.M., Lucks J.B.. How does RNA fold dynamically?. J. Mol. Biol. 2022; 434:167665. 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

Baker C.M., Lopes P.E.M., Zhu X., Roux B., MacKerell A.D.. Accurate calculation of hydration free energies using pair-specific Lennard–Jones parameters in the CHARMM drude polarizable force field. J. Chem. Theory Comput. 2010; 6:1181–1198. PubMed PMC

Luo Y., Roux B.. Simulation of osmotic pressure in concentrated aqueous salt solutions. J. Phys. Chem. Lett. 2010; 1:183–189.

Zhang Z., Vogele J., Mrazikova K., Kruse H., Cang X., Wohnert J., Krepl M., Sponer J.. Phosphorothioate substitutions in RNA structure studied by molecular dynamics simulations, QM/MM calculations and NMR experiments. J. Phys. Chem. B. 2021; 125:825–840. PubMed

Lay W.K., Miller M.S., Elcock A.H.. Reparameterization of solute–solute interactions for amino acid–sugar systems using isopiestic osmotic pressure molecular dynamics simulations. J. Chem. Theory Comput. 2017; 13:1874–1882. PubMed PMC

Yoo J., Aksimentiev A.. Improved parametrization of Li+, Na+, K+, and Mg2+ ions for all-atom molecular dynamics simulations of nucleic acid systems. J. Phys. Chem. Lett. 2012; 3:45–50.

Yoo J., Aksimentiev A.. Improved parameterization of amine–carboxylate and amine–phosphate interactions for molecular dynamics simulations using the CHARMM and AMBER force fields. J. Chem. Theory Comput. 2016; 12:430–443. 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

Xue Y., Gracia B., Herschlag D., Russell R., Al-Hashimi H.M.. Visualizing the formation of an RNA folding intermediate through a fast highly modular secondary structure switch. Nat. Commun. 2016; 7:ncomms11768. PubMed PMC

Henriksen N.M., Roe D.R., Cheatham T.E.. Reliable oligonucleotide conformational ensemble generation in explicit solvent for force field assessment using reservoir replica exchange molecular dynamics simulations. J. Phys. Chem. B. 2013; 117:4014–4027. PubMed PMC

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