Morphogenesis emerges from gene regulatory circuits that translate biochemical cues into spatially organized cell fates; yet, constructing quantitative simulations of these processes remains technically demanding. Here, we present a prompt-only pipeline in which a large language model (LLM) automatically generates CompuCell3D (CC3D) simulations directly from natural-language biological specifications. Using the canonical synNotch spheroid assay as a benchmark, we show that the LLM-generated code captures key features of contact-dependent signaling, cadherin-mediated adhesion, and multicellular sorting dynamics without manual programming. Baseline simulations exhibited the expected qualitative ordering of inducer-responder activation but revealed fragmentation into multiple spheroids, implicating premature reciprocal signaling as a kinetic failure mode. Incorporating a cumulative contact-duration threshold for synNotch activation rescued robust single-spheroid formation, suggesting that sustained cell-cell interactions are a critical design principle for this pattern. Our results establish conversational LLM guidance as a powerful accelerator for multiscale modeling, collapsing the steep learning curve of CC3D into a dialog-driven workflow. This framework enables nonspecialists to test gene-circuit hypotheses in silico and provides a generalizable route toward rapid, mechanism-level exploration of developmental design principles.
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Chen et al. (Sun,) studied this question.
synapsesocial.com/papers/69df2b65e4eeef8a2a6b0530 — DOI: https://doi.org/10.1021/acssynbio.5c00704
Kaiwen Chen
University of Toronto
Kevin Truong
University of Toronto
ACS Synthetic Biology
University of Toronto
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