An active area of research in pharmacology and drug discovery applies to biased signaling: the ability of a ligand to selectively activate some signal transduction pathways as compared to the native ligand acting at the same receptor. At the practical level, experimentalists seek to quantify ligand bias in order to classify ligands according to their selectivity. One popular method uses the so-called operational model to fit dose-response curves.

In this presentation, I will review the main limitations of this methodology, recently pointed out by our group and others. Our objective is then to design a method that fully take into account the kinetic nature of signaling pathways and as well as their possible cross-talks. Kinetic experiments, that measure the activity of several downstream effectors of a receptor after ligand binding with respect to time, are now widely available. I will explain how one can exploit such data and dynamical reaction network modeling with suitable statistical framework to provide a complete “bias map” of a ligand, compared to the native ligand, that successfully answer to our objective [2,3].

Going further, we can extend this methodology to take into account recently discovered compartmentalised signaling, which can eventually lead to spatial or location signaling bias. We have thus build a dynamical model that incorporate endocytosis/recycling event and spatial specificity, helping to quantify kinetic experiments under various receptor trafficking perturbations [4]. This new methodology is formulated as either partial differential equations (PDE) [1] or piecewise deterministic Markov processes (PDMP), which calls for interesting new developments in long time behavior analysis.

[1] Claire Alamichel, Juan Calvo, Erwan Hingant, Saoussen Latrach, Nathan Quiblier and Romain Yvinec. Modeling compartmentalization within intracellular signaling pathway. 2024, ESAIM: Proceedings and Surveys 77, pp100–122. 10.1051/proc/202477100

[2] Francesco de Pascali, Mohammed Akli Ayoub, Riccardo Benevelli, Silvia Sposini, Jordan Lehoux, Nathalie Gallay, Pauline Raynaud, Flavie Landomiel, Frédéric Jean-Alphonse, Christophe Gauthier, Lucie P. Pellissier, Pascale Crépieux, Anne Poupon, Asuka Inoue, Nicolas Joubert, Marie-Claude Viaud-Massuard, Livio Casarini, Manuela Simoni, Aylin C Hanyaloglu, Selva G Nataraja, Henry N Yu, Stephen S Palmer, Romain Yvinec and Eric Reiter. Pharmacological characterization of low molecular weight biased agonists at the follicle stimulating hormone receptor. International Journal of Molecular Sciences, 2021, 22 (18), pp.1-23. 10.3390/ijms22189850.

[3] Caroline Gora, Nicolas Azzopardi, Lucile Drobecq, Emmanuel Pecnard, Patrick Schnider, Pascale David-Pierson, Romain Yvinec, Christophe Grundschober and Lucie P. Pellissier. Targeting selectively oxytocin receptor signalling efficiently improves social interaction in Fmr1 KO mice. 2024. hal-04740514

[4] Chloé Weckel, Juliette Gourdon, Léo Darrigade, Vinesh Jugnarain, Pascale Crépieux, Eric Reiter, Frédéric Jean-Alphonse, Stefan Haar and Romain Yvinec. Spatiotemporal Modeling of GPCR Signaling: The Role of Endosomal Dynamics and Receptor Recycling. 2026. hal-05562673