PMCpy

PMCpy is a Python package for Polymer Monte Carlo (PMC) simulations of double-stranded DNA (dsDNA). It implements sequence-dependent, coarse-grained rigid base pair-step models that capture structural and mechanical properties of DNA at the base pair level — enabling efficient conformational sampling of DNA molecules spanning hundreds to thousands of base pairs.

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Features

• Sequence-dependent energy model — base pair-step stiffness and ground-state parameters derived from atomistic MD simulations (Lankas / RBP parametrisation), with support for systematic coarse-graining to lower-resolution representations.
• Flexible boundary conditions — open linear chains and closed (circular) DNA.
• Rich set of Monte Carlo moves — Pivot, Double Pivot, Crankshaft, Cluster Translation, Single Triad, and Midstep Move, all with Metropolis acceptance.
• Excluded volume — bead-based excluded-volume interactions with optional self-crossing detection.
• External constraints and forces — stretching forces (tweezer geometry), repulsion planes, and user-defined fixed triads.
• Equilibration protocol — automated convergence detection for burn-in.
• Built-in observables — tangent-tangent correlation (persistence length), writhe and linking number via the PyLk submodule.
• Trajectory I/O — XYZ-format trajectory writing and reading.
• Optional Numba acceleration — just-in-time compilation of performance-critical kernels.

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Installation

Clone the repository together with all required git submodules:

git clone --recurse-submodules -j8 git@github.com:eskoruppa/PMCpy.git

Then install the package in editable mode:

cd PMCpy
pip install -e .

Optional dependencies

Extra	Packages	Purpose
numba	numba	JIT-accelerated MC moves and evaluators
plot	matplotlib	Visualisation utilities
all	all of the above	Full feature set

Install extras with, e.g.:

pip install -e ".[all]"

Note: The submodules (SO3, RBPStiff, pyConDec, PyLk) are included as git submodules and are not separately published on PyPI. The recursive clone above is the recommended installation path.

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Quick start

import numpy as np
from pmcpy import Run
from pmcpy.GenConfs.straight import gen_straight

nbp      = 500
sequence = "".join(np.random.choice(list("ATCG"), nbp))
triads, positions = gen_straight(nbp)

sim = Run(
    triads=triads,
    positions=positions,
    sequence=sequence,
    closed=False,
    endpoints_fixed=True,
    temp=300,
    exvol_rad=2.0,
    parameter_set="md",
)

sim.run(num_steps=100_000, dump_every=1_000, outfile="traj.xyz")

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Citation

If you use PMCpy in your research, please cite the following papers:

Enrico Skoruppa, Helmut Schiessel,
Systematic coarse-graining of sequence-dependent structure and elasticity of double-stranded DNA,
Physical Review Research 7, 013044 (2025).
DOI: 10.1103/PhysRevResearch.7.013044

Willem Vanderlinden, Enrico Skoruppa, Pauline J. Kolbeck, Enrico Carlon, Jan Lipfert,
DNA fluctuations reveal the size and dynamics of topological domains,
PNAS Nexus 1(5), pgac268 (2022).
DOI: 10.1093/pnasnexus/pgac268

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License

PMCpy is released under the GNU General Public License v2.0.