Structural Systems Biology Toolkit (SSBtoolkit): From Molecular Structure to Subcellular Signaling Pathways

Here, we introduce the Structural Systems Biology (SSB) toolkit, a Python library that integrates structural macromolecular data with systems biology simulations to model signal-transduction pathways of G-protein-coupled receptors (GPCRs). Our framework streamlines simulation and analysis of the mathematical models of GPCRs cellular pathways, facilitating the exploration of the signal-transduction kinetics induced by ligand-GPCR interactions: the dose-response of the ligand can be modeled, along with the corresponding change in the concentration of other signaling molecular species over time, like for instance [Ca<sup>2+</sup>] or [cAMP]. SSB toolkit brings to light the possibility of easily investigating the subcellular effects of ligand binding on receptor activation, even in the presence of genetic mutations, thereby enhancing our understanding of the intricate relationship between ligand-target interactions at the molecular level and the higher-level cellular and (patho)physiological response mechanisms.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2025-04-18
DOI
https://doi.org/10.1021/acs.jcim.5c00165
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

Structural Systems Biology Toolkit (SSBtoolkit): From Molecular Structure to Subcellular Signaling Pathways

Giulia Rossetti, Rui Pedro Ribeiro, Jonas Goßen, Alejandro Giorgetti
Journal of Chemical Information and Modeling
Computational Drug Discovery Methods
article

Structural Systems Biology Toolkit (SSBtoolkit): From Molecular Structure to Subcellular Signaling Pathways

Giulia Rossetti, Rui Pedro Ribeiro, Jonas Goßen, Alejandro Giorgetti
article en

Abstract

Here, we introduce the Structural Systems Biology (SSB) toolkit, a Python library that integrates structural macromolecular data with systems biology simulations to model signal-transduction pathways of G-protein-coupled receptors (GPCRs). Our framework streamlines simulation and analysis of the mathematical models of GPCRs cellular pathways, facilitating the exploration of the signal-transduction kinetics induced by ligand-GPCR interactions: the dose-response of the ligand can be modeled, along with the corresponding change in the concentration of other signaling molecular species over time, like for instance [Ca<sup>2+</sup>] or [cAMP]. SSB toolkit brings to light the possibility of easily investigating the subcellular effects of ligand binding on receptor activation, even in the presence of genetic mutations, thereby enhancing our understanding of the intricate relationship between ligand-target interactions at the molecular level and the higher-level cellular and (patho)physiological response mechanisms.

Journal of Chemical Information and ModelingVol. 65(9)
University of Verona (IT), FZI Research Center for Information Technology (DE), Faculty (United Kingdom) (GB), RWTH Aachen University (DE)
Horizon 2020 Framework Programme
Openalex Percentile: Top 91%
Computational Drug Discovery Methods
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Structural Systems Biology Toolkit (SSBtoolkit): From Molecular Structure to Subcellular Signaling Pathways — Giulia Rossetti, Rui Pedro Ribeiro, et al. · Journal of Chemical Information and Modeling (2025) | TGRS Research Map | TGRS