{
  "abstract": "Ribonucleic acid (RNA) function is intrinsically linked to its three-dimensional architecture, yet experimental structure determination remains challenging. Here, we introduce TAPERSS-MoCa (Theoretical Analyses, Prediction, and Evaluation of RNA Structures from Sequence using a Monte-Carlo Simulator), a physics-based fragment assembly framework for predicting RNA tertiary structures directly from sequence. By utilizing a novel fragment library grounded in dinucleoside monophosphate (DNMP) energetics parameterized via Discrete Path Sampling (DPS), TAPERSS-MoCa efficiently samples low-energy conformational landscapes. Evaluated across 6-, 10-, and 12-nucleotide RNA test sets, TAPERSS-MoCa consistently recovers native-like global minima with canonical Watson–Crick base pairs adopting near-planar geometry. By combining dinucleoside fragment energetics with an angularly constrained hydrogen-bonding potential, TAPERSS-MoCa accurately captures A-form structures in 6-nucleotide linear RNAs, outperforming traditional fragment-assembly algorithms that frequently misfold these flexible sequences. Thermodynamic evaluations based on ensemble partition functions (Δ G folding ) and macrostate basin free energies (Δ F folding ) demonstrate strong predictive performance for rigid, well-stacked GNRA tetraloops. Furthermore, TAPERSS-MoCa systematically reproduces key physical stability trends predicted by empirical nearest-neighbor models. This physics-based approach provides a robust platform for structural prediction and thermodynamic profiling of short RNA motifs, supporting RNA-targeted drug discovery and functional design.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Chemistry and Biochemistry",
    "Florida Atlantic University",
    "Department of Chemistry",
    "Massachusetts Institute of Technology"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Mariam Ibrahim",
      "orcid": "0009-0009-8367-103X"
    },
    {
      "affs": [
        0,
        1,
        2,
        3
      ],
      "name": "Ivan Issac Riveros",
      "orcid": "0000-0002-1454-7125"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Nanayakkara P.N.R. Kumarachchi",
      "orcid": "0009-0007-9137-2852"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Ilyas Yildirim",
      "orcid": "0000-0001-8357-1922"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4evt478c2gxp3.bib",
  "cited_by": 0,
  "doi": "10.26434/chemrxiv.15010570/v1",
  "fulltext_url": null,
  "id": "4evt478c2gxp3",
  "issns": [],
  "landing_url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010570/v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|RNA and protein synthesis mechanisms"
    ]
  ],
  "openalex": "W7222631437",
  "pdf_url": "https://chemrxiv.org/doi/pdf/10.26434/chemrxiv.15010570/v1",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-16",
  "publisher": "American Chemical Society (ACS)",
  "ris": "https://research.draconitic.com/paper/4evt478c2gxp3.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:24Z",
      "native_id": "10.26434/chemrxiv.15010570",
      "source": "chemrxiv",
      "url": "https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010570/v1"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|RNA and protein synthesis mechanisms",
      "subfield": "molecular-biology"
    }
  ],
  "title": "TAPERSS-MoCa: A Physics-Based Monte Carlo Framework for 3D RNA Structure Prediction from Sequence",
  "title_text": "TAPERSS-MoCa: A Physics-Based Monte Carlo Framework for 3D RNA Structure Prediction from Sequence",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:24Z",
  "url": "https://research.draconitic.com/paper/4evt478c2gxp3",
  "venue": "ChemRxiv",
  "versions": []
}