{
  "abstract": "A full characterisation of a molecular system requires its metastable states, their populations and their interconversion rates. Molecular Dynamics can in principle provide this characterisation but is limited by sampling and by force-field inaccuracies. Enhanced sampling addresses the first problem, but typically requires prior knowledge of reaction coordinates or metastable states and often sacrifices the kinetics, while maximum-caliber reweighting by Brotzakis, Vendruscolo and Bolhuis [Proc. Natl. Acad. Sci. U.S.A., 118(2):e2012423118, 2021] has been implemented to that matter on reweighting continuous pathways by imposing rate constants as kinetic constraints in two-state protein folding. Here, we introduce Anneal-MaxCal, which tackles both problems by imposing rate constants or time-resolved data on a Markov model learned along an annealed solute-tempering ladder spanning softer to physical interactions. MBAR assigns physical free energies to all 160 cells of a slow TICA subspace, against 79 visited at the physical coupling. The square-root approximation (SqRA), a discretised diffusion on this free-energy landscape, converts these populations into a detailed-balance rate matrix. Its prefactors, which act as a position-dependent diffusivity across each cell face, are learned from transitions at the softer couplings and extrapolated log-linearly to the physical coupling. This yields rates and a committor across the TICA space, although the physical rung contains a single barrier crossing. For alanine dipeptide, 665 ns of simulation give a relaxation time of 5430 {+/-} 996 ps against 4413 {+/-} 446 ps from 15.4 s of unbiased dynamics, whereas a constant prefactor is 2.5 times too slow. Maximum caliber then minimally perturbs this prior, with the posterior populations following from a generalised Doob transform. A synthetic time-resolved density with a tenfold slower back-transition lowers {Delta}F from 5.191 to 2.885 kBT , raises the product-basin population from 0.0055 to 0.0529 and slows relaxation 9.47-fold, leaving the reactant basin unchanged. Forward and backward rates accelerated 3 and 20-fold raise {Delta}F by 1.892 kBT and shorten relaxation from 4818 to 289 ps.",
  "abstract_shown": true,
  "affiliations": [
    "[1] Department of Biotechnology, Agricultural University of Athens, 75 Iera Odos Str., 11855 Athens, Greece. [2] Archimedes Unit, Athena Research Center, 15125"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Z. F. Brotzakis"
    },
    {
      "name": "N. Rekatsinas"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cb51eea3dbxns.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.10.05.756723",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.10.05.756723v1.full",
  "id": "cb51eea3dbxns",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.10.05.756723v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "biophysics"
    ],
    [
      "openalex",
      "1312|Protein Structure and Dynamics"
    ]
  ],
  "openalex": "W7221174167",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.10.05.756723v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-05",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/cb51eea3dbxns.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:26:46Z",
      "native_id": "10.64898/2026.10.05.756723",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.10.05.756723v1"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "biorxiv:biophysics",
      "subfield": "biophysics"
    }
  ],
  "title": "Anneal-MaxCal: kinetic ensembles from a Markov model learned along a solute-tempering ladder",
  "title_text": "Anneal-MaxCal: kinetic ensembles from a Markov model learned along a solute-tempering ladder",
  "type": "preprint",
  "updated_at": "2026-10-30T12:26:46Z",
  "url": "https://research.draconitic.com/paper/cb51eea3dbxns",
  "venue": "bioRxiv",
  "versions": []
}