  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.
