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February 21, 2026Biophysical Journal0 citations

BPS2026 – A multi-scale simulation approach to elucidate PRC1-mediated microtubule organization

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ASAbhilash SahooWCWilliam ConwayBPBryce Palmer

Key Points

  • To elucidate the role of PRC1 in microtubule organization using a multi-scale simulation approach.
  • Developed a multi-resolution simulation pipeline integrated with cryo-electron tomography data.
  • Employed a bottom-up coarse-graining strategy to create minimal coarse-grained models.
  • Parametrized interaction potentials using relative-entropy minimization guided by Bayesian optimization.
  • Incorporated a stochastic kinetic Monte Carlo component for dynamic modeling of cytoskeletal networks.
  • Accurately captured emergent bundling dynamics of microtubules.
  • Reproduced key structural and thermodynamic properties of the cytoskeleton.
  • Provided quantitative insights into biological structures formed by passive crosslinkers.

Abstract

Microtubule-associated proteins (MAPs) are critical for organizing the cytoskeleton to support specialized cellular functions. This work focuses on PRC1, a passive crosslinker that stabilizes the mitotic spindle by selectively bundling antiparallel microtubules. To understand how molecular interactions produce robust spindle-wide organization, we have developed a multi-resolution simulation pipeline that works in synergy with cryo-electron tomography (cryo-ET) data. Our approach is built on a bottom-up coarse-graining (CG) strategy where we develop minimal coarse-grained models. The interaction potentials for these CG models are systematically parametrized using relative-entropy minimization guided by Bayesian optimization to faithfully reproduce key structural and thermodynamic properties. To capture the dynamic nature of the cytoskeleton, the CG model also incorporates a stochastic kinetic Monte Carlo component (through aLENS) that allows for the spontaneous formation and breaking of crosslinker-mediated networks. This combined approach allows our simulations to accurately capture emergent bundling dynamics and, at larger scales, complex network mechanics. Ultimately, this work aims to provide a clearer, quantitative picture of how passive crosslinkers build robust biological structures, contributing to our fundamental understanding of spindle mechanics and offering a transferable approach for multi-scale modeling in other complex systems.

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Cite This Study

Sahoo et al. (2026) studied this question.

synapsesocial.com/papers/69990e015b97ab4c14ac2f39https://doi.org/10.1016/j.bpj.2025.11.2509
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