ORIGINAL RESEARCH article
Front. Mol. Biosci.
Sec. Biological Modeling and Simulation
This article is part of the Research TopicSystems Biology: Encoding Cell Signaling with Quantitative Molecular Tools and ModelsView all 7 articles
Visualizing mechanistic models by integrating site-specific molecular details into reaction networks
Provisionally accepted- UCONN Health, Farmington, United States
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Mechanistic modeling in biology aims to describe biological processes based on details on molecular mechanisms and interactions. Rule-based mechanistic modeling enables the simulation of biological systems while explicitly accounting for molecular details, such as protein domains and their specific interactions. Traditionally, mechanistic models are visually represented by reaction or pathway diagrams that depict transformations and modifications of chemical species. In contrast, rule-based descriptions are effective to encode the detailed specificity of individual interactions (e.g., how phosphorylation at a particular residue affects binding affinity elsewhere in the same protein complex) in a compact and precise form, but are complicated to integrate into comprehensive visual representations. Here, we introduce Molecular Process Diagrams, an approach to embed rule-based specificity directly within reaction network diagrams. Our method highlights three fundamental elements: interacting molecular complexes, molecular sites directly modified by a rule, and molecular sites that modulate but are not directly modified by interactions (e.g., phosphorylation-dependent affinity changes). Implemented at multiple resolution levels within the Virtual Cell (VCell) software, these diagrams maintain pathway-like clarity while accurately reflecting detailed molecular interactions. Additionally, we demonstrate compatibility with Systems Biology Graphical Notation (SBGN) process diagrams, ensuring standardized visual conventions.
Keywords: Systems Biology, mathematical modeling, Rule-based modeling, Reaction network, visualization, SBGN, Virtual cell, VCell
Received: 06 Aug 2025; Accepted: 30 Oct 2025.
Copyright: © 2025 Vasilescu, Schaff, Moraru and Blinov. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Michael  L Blinov, blinov@uchc.edu
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
