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PENSim: A Toolkit for PEN-DNA Systems

Authors: Gwendal Ducloz and Nicolas Schabanel

Published in: LIPIcs, Volume 387, 32nd International Conference on DNA Computing and Molecular Programming (DNA 32) (2026)

Abstract

The PEN-DNA toolbox has emerged as a versatile framework for implementing chemical reaction networks with DNA and enzymes, enabling applications ranging from molecular sensing to neural computation. A simulation tool, DACCAD, has provided a standardized approach for translating network schematics into dynamical models, facilitating in silico design and validation. However, the evolution of the PEN-DNA toolbox - particularly the transition from inhibitor-based regulation to drain-template-based inactivation - introduces mechanisms that are only partially captured by existing simulation frameworks, limiting the ability to reliably simulate and design recent PEN-DNA systems. In this context, we introduce PENSim, a simulation package that aims to realign computational modeling with current experimental practices. By extending the repertoire of simulated reactions and incorporating thermodynamic dependencies into kinetic rate calculations via NUPACK, PENSim enables a more faithful representation of modern PEN-DNA systems. In particular, accounting for thermodynamic effects is essential for accurately modeling inactivation via drain templates. PENSim is validated through qualitative reproduction of existing experimental results, including inactivation-driven bistability, microRNA detection circuits, and linear classifiers based on neural networks. By bridging legacy modeling approaches with recent experimental advances, PENSim provides a step toward more realistic and flexible in silico design of systems based on the PEN-DNA toolbox.

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Gwendal Ducloz and Nicolas Schabanel. PENSim: A Toolkit for PEN-DNA Systems. In 32nd International Conference on DNA Computing and Molecular Programming (DNA 32). Leibniz International Proceedings in Informatics (LIPIcs), Volume 387, pp. 4:1-4:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{ducloz_et_al:LIPIcs.DNA.32.4,
  author =	{Ducloz, Gwendal and Schabanel, Nicolas},
  title =	{{PENSim: A Toolkit for PEN-DNA Systems}},
  booktitle =	{32nd International Conference on DNA Computing and Molecular Programming (DNA 32)},
  pages =	{4:1--4:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-444-4},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{387},
  editor =	{Scalise, Dominic and Schweller, Robert},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.32.4},
  URN =		{urn:nbn:de:0030-drops-267743},
  doi =		{10.4230/LIPIcs.DNA.32.4},
  annote =	{Keywords: PEN-DNA toolbox, DNA circuit simulation, DNA reaction kinetics, Enzymatic DNA reaction kinetics}
}

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DOI: 10.4230/LIPIcs.DNA.31.1

Algorithmic Hardness of the Partition Function for Nucleic Acid Strands

Authors: Gwendal Ducloz, Ahmed Shalaby, and Damien Woods

Published in: LIPIcs, Volume 347, 31st International Conference on DNA Computing and Molecular Programming (DNA 31) (2025)

Abstract

To understand and engineer biological and artificial nucleic acid systems, algorithms are employed for prediction of secondary structures at thermodynamic equilibrium. Dynamic programming algorithms are used to compute the most favoured, or Minimum Free Energy (MFE), structure, and the Partition Function (PF) - a tool for assigning a probability to any structure. However, in some situations, such as when there are large numbers of strands, or pseudoknotted systems, NP-hardness results show that such algorithms are unlikely, but only for MFE. Curiously, algorithmic hardness results were not shown for PF, leaving two open questions on the complexity of PF for multiple strands and single strands with pseudoknots. The challenge is that while the MFE problem cares only about one, or a few structures, PF is a summation over the entire secondary structure space, giving theorists the vibe that computing PF should not only be as hard as MFE, but should be even harder. We answer both questions. First, we show that computing PF is #P-hard for systems with an unbounded number of strands, answering a question of Condon Hajiaghayi, and Thachuk [DNA27]. Second, for even a single strand, but allowing pseudoknots, we find that PF is #P-hard. Our proof relies on a novel magnification trick that leads to a tightly-woven set of reductions between five key thermodynamic problems: MFE, PF, their decision versions, and #SSEL that counts structures of a given energy. Our reductions show these five problems are fundamentally related for any energy model amenable to magnification. That general classification clarifies the mathematical landscape of nucleic acid energy models and yields several open questions.

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Gwendal Ducloz, Ahmed Shalaby, and Damien Woods. Algorithmic Hardness of the Partition Function for Nucleic Acid Strands. In 31st International Conference on DNA Computing and Molecular Programming (DNA 31). Leibniz International Proceedings in Informatics (LIPIcs), Volume 347, pp. 1:1-1:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ducloz_et_al:LIPIcs.DNA.31.1,
  author =	{Ducloz, Gwendal and Shalaby, Ahmed and Woods, Damien},
  title =	{{Algorithmic Hardness of the Partition Function for Nucleic Acid Strands}},
  booktitle =	{31st International Conference on DNA Computing and Molecular Programming (DNA 31)},
  pages =	{1:1--1:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-399-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{347},
  editor =	{Schaeffer, Josie and Zhang, Fei},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.31.1},
  URN =		{urn:nbn:de:0030-drops-238504},
  doi =		{10.4230/LIPIcs.DNA.31.1},
  annote =	{Keywords: Partition function, minimum free energy, nucleic acid, DNA, RNA, secondary structure, computational complexity, #P-hardness}
}

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Documents authored by Ducloz, Gwendal

PENSim: A Toolkit for PEN-DNA Systems

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Algorithmic Hardness of the Partition Function for Nucleic Acid Strands

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