{
  "abstract": "Transferable coarse-grained (CG) force fields compress chemical space: by aggregating atoms into a reduced set of interaction beads, models such as MARTINI reduce the number of distinguishable compounds by roughly three orders of magnitude, making high-throughput screening of thermodynamic properties tractable across soft matter, with drug--membrane permeability as a well-developed example. The compression is lossy and, so far, one-way: a screen returns a combination of beads, with no established route back to the compounds it stands for. Recovering those compounds--compositional backmapping--is a one-to-many inverse map, distinct from the better-studied conformational problem of rebuilding atomic coordinates from a known mapping. Here we formulate compositional backmapping as conditional graph generation by introducing juniper, a discrete denoising diffusion model over molecular graphs conditioned on the octanol--water partition free energy $ΔG_{\\mathrm{W} \\mapsto \\mathrm{O}}$, the principal driver of MARTINI bead type assignment and hence a proxy for bead identity. Trained on molecules of up to 9 heavy atoms mapped onto one or two beads, juniper generates molecules that are 93\\% valid and 92\\% unique for two-bead targets, and whose $ΔG_{\\mathrm{W} \\mapsto \\mathrm{O}}$ distributions track the target $ΔG^{\\mathrm{CG}}_{\\mathrm{W} \\mapsto \\mathrm{O}}$ linearly ($r^{2} \\geq 0.96$), departing only in the hydrophobic and hydrophilic tails. Although the model receives no chemical information beyond a single scalar, the functional groups shift systematically with the imposed free energy, from branched hydrocarbons at the apolar end to amides, imides, and isocyanates at the polar end. A bead combination flagged by a CG screen can therefore be turned into candidate molecules for atomistic study or synthesis.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.04432",
  "author_total": 2,
  "authors": [
    {
      "name": "Luis Itza Vazquez-Salazar"
    },
    {
      "name": "Tristan Bereau"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bpk1vp6wk6vwr.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.04432",
  "fulltext_url": null,
  "id": "bpk1vp6wk6vwr",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.04432",
  "language": null,
  "licence": "CC-BY-NC-SA-4.0",
  "licence_label": "CC BY-NC-SA 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-nc-sa/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cond-mat.soft"
    ],
    [
      "arxiv",
      "cs.LG"
    ],
    [
      "arxiv",
      "physics.bio-ph"
    ],
    [
      "arxiv",
      "physics.chem-ph"
    ],
    [
      "openalex",
      "1703|Computational Drug Discovery Methods"
    ]
  ],
  "openalex": "W7211909045",
  "pdf_url": "https://arxiv.org/pdf/2609.04432",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-03",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bpk1vp6wk6vwr.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:14Z",
      "native_id": "2609.04432",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.04432"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "arxiv:physics.chem-ph",
      "subfield": "physical"
    },
    {
      "field": "physics",
      "origin": "arxiv:physics.bio-ph",
      "subfield": "biological-medical"
    },
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.soft",
      "subfield": "condensed-matter"
    }
  ],
  "title": "Recovering molecules from coarse-grained beads: free-energy-conditioned generative backmapping across chemical space",
  "title_text": "Recovering molecules from coarse-grained beads: free-energy-conditioned generative backmapping across chemical space",
  "type": "preprint",
  "updated_at": "2026-10-30T12:19:14Z",
  "url": "https://research.draconitic.com/paper/bpk1vp6wk6vwr",
  "venue": "arXiv",
  "versions": []
}