{ "id": "1791", "updated": "2023-06-08T09:43:12.714396+00:00", "metadata": { "version": 1, "contributors": [ { "givennames": "Domen", "affiliations": [ "Department of Theoretical Physics, Jozef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia" ], "email": "domenvaupotic@gmail.com", "familyname": "Vaupoti\u010d" }, { "givennames": "Angelo", "affiliations": [ "Scuola Internazionale Superiore di Studi Avanzati (SISSA), Via Bonomea 265, 34136 Trieste, Italy" ], "email": "anrosa@sissa.it", "familyname": "Rosa" }, { "givennames": "Luca", "affiliations": [ "Department of Physics, University of Trento, via Sommarive 14, 38123 Trento, Italy", "INFN-TIFPA, Trento Institute for Fundamental Physics and Applications, via Sommarive 14, 38123 Trento, Italy" ], "email": "Luca.tubiana@unitn.it", "familyname": "Tubiana" }, { "givennames": "An\u017ee", "affiliations": [ "Department of Theoretical Physics, Jozef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia" ], "email": "Anze.Bozic@ijs.si", "familyname": "Bo\u017ei\u010d" } ], "title": "Scaling properties of RNA as a randomly branching polymer", "_oai": { "id": "oai:materialscloud.org:1791" }, "keywords": [ "RNA", "polymer physics", "statistical mechanics", "scaling" ], "publication_date": "Jun 08, 2023, 11:43:12", "_files": [ { "key": "Fig1.txt", "description": "RNA fold in dot-bracket format (figure 1)", "checksum": "md5:007b052df5ee0d522981bb9aeb97e2bf", "size": 158 }, { "key": "Fig2a.csv", "description": "Average Ladder Distance as a function of the number of nucleotides (figure 2a)", "checksum": "md5:94c2b5d2fb61ba560952a337936dd242", "size": 263 }, { "key": "Fig2a_inset.csv", "description": "estimation of rho exponent from ALD scaling (inset figure 2a)", "checksum": "md5:6a0962d78f99095645c14fdb614a8998", "size": 247 }, { "key": "Fig2b_13500.csv", "description": "probability distribution of scaled path length for N=13500 (figure 2b)", "checksum": "md5:9277b79cfaf7fd1b4496f3cd14f82022", "size": 20170 }, { "key": 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"key": "Fig2b_inset.csv", "description": "Estimation of exponents rho_theta and rho_t from scaled path length distributions, (figure 2b,inset)", "checksum": "md5:8b9721e4a0b55db18e1944c9ed86f997", "size": 460 }, { "key": "Fig2c.csv", "description": "branch length as a function of the number of nucleotides (figure 2c)", "checksum": "md5:18c8f10266e7184ba31d6df547d2b9d0", "size": 263 }, { "key": "Fig2c_inset.csv", "description": "estimation of epsilon exponent from branch weight scaling (figure 2c, inset)", "checksum": "md5:5f55152e6dd96a820cbd1078d8a65a7a", "size": 249 }, { "key": "Fig2d_100.csv", "description": "probability distribution of branch weights for N=100 (figure 2d)", "checksum": "md5:98b2591fb647693eb243dd8adc447b1e", "size": 173 }, { "key": "Fig2d_200.csv", "description": "probability distribution of branch weights for N=200 (figure 2d)", "checksum": "md5:bc9b21b532c92ae2e2d0199039bc8102", "size": 368 }, { "key": "Fig2d_300.csv", "description": "probability distribution of 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"key": "Fig2d_4000.csv", "description": "probability distribution of branch weights for N=4000 (figure 2d)", "checksum": "md5:27b945836d6ae7afe548f5a912c15577", "size": 9480 }, { "key": "Fig2d_6000.csv", "description": "probability distribution of branch weights for N=6000 (figure 2d)", "checksum": "md5:b3465edfc2f1c74e3641ad4e2f9d67b7", "size": 14366 }, { "key": "Fig2d_9000.csv", "description": "probability distribution of branch weights for N=9000 (figure 2d)", "checksum": "md5:7938c2a6a9bd0259f6abb1419b8f69b7", "size": 22138 }, { "key": "Fig2d_13500.csv", "description": "probability distribution of branch weights for N=13500 (figure 2d)", "checksum": "md5:9f76ae73cde084f6780dd0aebef177ce", "size": 33887 }, { "key": "Fig2d_inset.csv", "description": "estimation of epsilon exponent from branch weight distributions (figure 2d, inset)", "checksum": "md5:6d626b26491fc8d407db79209ae33583", "size": 270 }, { "key": "Fig3.csv", "description": "convergence of scaling exponents with N", "checksum": "md5:7ede661cfaa595056d8b5b4eb5dc63c0", "size": 987 }, { "key": "Fig4.csv", "description": "comparison of scaling exponents with notable ones from polymer theory", "checksum": "md5:0c30b8f99d19b0b5695e5d7533a7dbcf", "size": 161 } ], "references": [ { "comment": "Paper where the data is discussed", "doi": "", "citation": "D. Vaupoti\u010d, A. Rosa, L. Tubiana, A. Bo\u017ei\u010d, The Journal of Chemical Physics, 158 (2023) (accepted)", "type": "Journal reference" } ], "description": "Formation of base pairs between the nucleotides of a ribonucleic acid (RNA) sequence gives rise to a complex and often highly branched RNA structure. While numerous studies have demonstrated the functional importance of the high degree of RNA branching\u2014for instance, for its spatial compactness or interaction with other biological macromolecules\u2014RNA branching topology remains largely unexplored. Here, we use the theory of randomly branching polymers to explore the scaling properties of RNAs by mapping their secondary structures onto planar tree graphs. Focusing on random RNA sequences of varying lengths, we determine the two scaling exponents related to their topology of branching. Our results indicate that ensembles of RNA secondary structures are characterized by annealed random branching and scale similarly to self-avoiding trees in three dimensions. We further show that the obtained scaling exponents are robust upon changes in nucleotide composition, tree topology, and folding energy parameters. Finally, in order to apply the theory of branching polymers to biological RNAs, whose length cannot be arbitrarily varied, we demonstrate how both scaling exponents can be obtained from distributions of the related topological quantities of individual RNA molecules with fixed length. In this way, we establish a framework to study the branching properties of RNA and compare them to other known classes of branched polymers. By understanding the scaling properties of RNA related to its branching structure, we aim to improve our understanding of the underlying principles and open up the possibility to design RNA sequences with desired topological properties.", "status": "published", "license": "Creative Commons Attribution 4.0 International", "conceptrecid": "1790", "is_last": true, "mcid": "2023.91", "edited_by": 576, "id": "1791", "owner": 1051, "license_addendum": null, "doi": "10.24435/materialscloud:js-fx" }, "revision": 2, "created": "2023-06-07T20:47:12.861420+00:00" }