Evidence map›Paper›PMID 41915672›Full record

ArticlePLoS computational biology2026

BIOPOINT: A particle-based model for probing nuclear mechanics and cell-ECM interactions via experimentally derived parameters.

Sandipan Chattaraj, Julius Zimmermann, Francesco Silvio Pasqualini

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Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Sandipan ChattarajDept of Civil Engineering and Architecture, University of Pavia: Universita degli Studi di Pavia, Pavia, ITALY.
Julius ZimmermannDept of Civil Engineering and Architecture, University of Pavia: Universita degli Studi di Pavia, Pavia, ITALY.ORCID https://orcid.org/0000-0003-1486-0426
Francesco Silvio PasqualiniDept of Civil Engineering and Architecture, University of Pavia: Universita degli Studi di Pavia, Pavia, ITALY.ORCID https://orcid.org/0000-0001-7038-3121

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Morphogenesis arises from biochemical and biomechanical interactions across multiple spatial and temporal scales. Experimental studies alone cannot fully resolve these dynamics, motivating computational models. Subcellular element modeling (SEM) is well suited for simulating emergent cellular and tissue morphologies, but traditional SEM frameworks do not explicitly include nuclear deformation or direct cell-extracellular matrix (ECM) interactions: capabilities typically associated with continuum approaches based on the finite-element method (FEM) approaches. FEM excels at modeling cell and tissue mechanics, but struggle to accommodate the large, non-linear deformations driven by local, geometry-changing events that define morphogenesis. Here, we introduce BIOPOINT, a particle-based framework that augments SEM with FEM-like mechanical capabilities by incorporating (1) a deformable, multi-particle nucleus capable of capturing nuclear stress and strain distributions and (2) an explicit ECM layer represented by structured static particles with tunable adhesive potentials. To ensure biological relevance, we calibrate BIOPOINT against single-cell indentation experiments (SKOV3). We then apply this calibrated parameter set, without additional refitting, to two independent scenarios: (i) cell (EC and hMSC) spreading on ECM micropatterns, capturing qualitative coupling between cell and nuclear shape; and (ii) confined migration (MDA-MB-231) through rigid constrictions, qualitatively reproducing the characteristic sequence of nuclear elongation and partial recovery. Differently from previous work, we present a full SEM model that uses heterogeneous particles to model nuclei, cells, and ECM via phase separation. By combining SEM's strength in modeling emergent cell and tissue geometry with a mechanically sound handling of nuclear and ECM interactions, BIOPOINT provides a versatile platform for studying cell behaviors, like shape acquisition and migration through confinement that are relevant to morphogenesis. Implemented within the widely used, open-source LAMMPS ecosystem, BIOPOINT offers an accessible and extensible tool for the community.

Indexed as

Cell NucleusExtracellular MatrixModels, BiologicalBiomechanical PhenomenaComputational BiologyComputer SimulationFinite Element AnalysisHumansMorphogenesis

Identifiers

PMID41915672
PMCPMC13056257

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.