Advances in computational modeling approaches in pituitary gonadotropin signaling

TL;DR

This paper reviews computational modeling approaches for pituitary gonadotropin signaling, highlighting challenges, recent advances, and potential for drug discovery within the complex multi-scale endocrine system.

Contribution

It provides a comprehensive overview of historical and current modeling techniques, discusses open statistical questions, and emphasizes the importance of multi-scale integration for future research.

Findings

Advances in intracellular pathway modeling for gonadotropins.

Identification of open statistical challenges in signal analysis.

Potential for improved drug discovery through systems biology.

Abstract

Pituitary gonadotropins play an essential and pivotal role in the control of human and animal reproduction within the hypothalamic-pituitary-gonadal (HPG) axis. The computational modeling of pituitary gonadotropin signaling encompasses phenomena of different natures such as the dynamic encoding of gonadotropin secretion, and the intracellular cascades triggered by gonadotropin binding to their cognate receptors, resulting in a variety of biological outcomes. We overview historical and ongoing issues in modeling and data analysis related to gonadotropin secretion in the field of both physiology and neuro-endocrinology. We mention the different mathematical formalisms involved, their interest and limits. We discuss open statistical questions in signal analysis associated with key endocrine issues. We also review recent advances in the modeling of the intracellular pathways activated by gonadotropins, which yields promising development for innovative approaches in drug discovery. The greatest challenge to be tackled in computational modeling of pituitary gonadotropin signaling is the embedding of gonadotropin signaling within its natural multi-scale environment, from the single cell level, to the organic and whole HPG level. The development of modeling approaches of G protein-coupled receptor signaling, together with multicellular systems biology may lead to unexampled mechanistic understanding with critical expected fallouts in the therapeutic management of reproduction.