In Silico Systems Modeling of Endothelial Nitric Oxide Regulation Using CytoSolve® Modular Architecture for Vascular Biology Research

Partner Description

Brigham and Women’s Hospital
Brigham and Women’s Hospital is a leading academic medical center with deep expertise in vascular biology and translational research.

Challenge

Shear-stress–induced nitric oxide (NO) production in endothelial cells is regulated by a complex, multi-timescale biological system involving calcium signaling, kinase-mediated phosphorylation, transcriptional regulation, and protein–protein interactions. Capturing this biology computationally requires integrating multiple independently developed pathway models.

Traditional monolithic modeling approaches force manual pathway merging into a single large model, leading to poor scalability, loss of pathway provenance, limited reusability, and high risk of modeling errors. Such approaches are poorly suited for collaborative research, continuous knowledge updates, or interrogation of pathway-specific perturbations. A new in silico modeling paradigm was required to preserve modularity while enabling system-wide simulation.

How CytoSolve® Helped

CytoSolve® provided a partitioned, ontology-driven in silico systems architecture that enabled dynamic integration of independently developed molecular pathway models without collapsing them into a single monolithic structure.

Four validated pathway models governing endothelial nitric oxide synthase (eNOS) activation and NO production were incorporated:

  • Calcium-mediated eNOS activation
  • AKT-dependent eNOS phosphorylation
  • Transcriptional regulation via AP-1 and KLF2
  • NO production through eNOS protein complexes
Each pathway model was preserved in its original SBML and MIRIAM-compliant form. CytoSolve®’s semantic, binding-based architecture identified shared molecular species and reactions across models using ontology annotations and automated reasoning. This enabled synchronized in silico simulation while maintaining pathway independence.

The models executed in parallel and reconciled shared molecular states through mass-balance controllers, allowing the distributed system to converge to behavior equivalent to a fully integrated model—while retaining transparency, modularity, and extensibility. This approach enabled computational interrogation of pathway perturbations, gene silencing scenarios, and pharmacologic interventions entirely in silico.

Key Benefits Realized

  • Modular, scalable in silico systems architecture replacing fragile monolithic models
  • Preservation of original pathway assumptions, provenance, and experimental lineage
  • Parallel simulation of interacting molecular pathways with synchronized state resolution
  • Support for collaborative modeling across clinical, biological, and engineering teams
  • Ability to simulate genetic and pharmacologic perturbations entirely in silico
  • Architecture designed for continuous expansion as new biological data emerge

Outcome

The CytoSolve®-enabled in silico systems architecture successfully reproduced experimentally observed nitric oxide dynamics in endothelial cells under shear stress, capturing both rapid signaling responses and longer-term regulatory behavior. Beyond predictive accuracy, the collaboration demonstrated a transformative computational modeling paradigm—one that allows institutions such as Brigham and Women’s Hospital to aggregate, evolve, and interrogate complex biological knowledge in a modular, reusable, and rigorously computational manner. This case study establishes CytoSolve® as a foundational platform for large-scale, multi-pathway in silico modeling and collaborative translational research.