Nafarelin acetate: a gonadotropin-releasing hormone agonist for the treatment of endometriosis

Ovarian hyperstimulation syndrome without gonadotropin stimulation: an unusual response to a GnRH agonist

Ovarian hyperstimulation syndrome (OHSS) is a well-known iatrogenic complication of ovarian stimulation with gonadotropins. We present the case of a woman in her 30s who developed OHSS without the administration of gonadotropins. She was due to undergo intracytoplasmic sperm injection (ICSI) for primary subfertility. After taking a gonadotropin-releasing hormone (GnRH) receptor agonist for 3 weeks, she presented with abdominal pain, nausea and bloating. She was diagnosed with moderate to severe OHSS, requiring management as an inpatient.Investigations included a pelvic ultrasound scan showing an enlarged ovary, serum oestradiol >30 000 pmol/L and an MRI of the brain with an incidental finding of a 5 mm pituitary microadenoma.She recovered rapidly and was referred for endocrinology evaluation and multidisciplinary team discussion. The OHSS was felt to be explained by an unusual 'flare' response to a GnRH agonist. A further ICSI cycle with an antagonist protocol is planned.

Rational Design, Synthesis and Binding Affinity Studies of Anthraquinone Derivatives Conjugated to Gonadotropin-Releasing Hormone (GnRH) Analogues towards Selective Immunosuppression of Hormone-Dependent Cancer

Gonadotropin-releasing hormone (GnRH) is pivotal in regulating human reproduction and fertility through its specific receptors. Among these, gonadotropin-releasing hormone receptor type I (GnRHR I), which is a member of the G-protein-coupled receptor family, is expressed on the surface of both healthy and malignant cells. Its presence in cancer cells has positioned this receptor as a primary target for the development of novel anti-cancer agents. Moreover, the extensive regulatory functions of GnRH have underscored decapeptide as a prominent vehicle for targeted drug delivery, which is accomplished through the design of appropriate conjugates. On this basis, a rationally designed series of anthraquinone/mitoxantrone-GnRH conjugates (con1-con8) has been synthesized herein. Their in vitro binding affinities range from 0.06 to 3.42 nM, with six of them (con2-con7) demonstrating higher affinities for GnRH than the established drug leuprolide (0.64 nM). Among the mitoxantrone based GnRH conjugates, con3 and con7 show the highest affinities at 0.07 and 0.06 nM, respectively, while the disulfide bond present in the conjugates is found to be readily reduced by the thioredoxin (Trx) system. These findings are promising for further pharmacological evaluation of the synthesized conjugates with the prospect of performing future clinical studies.

Gonadotropin-Releasing Hormone and GnRH Receptor: Structure, Function and Drug Development

BACKGROUND

Gonadotropin-Releasing Hormone (GnRH) is a key element in sexual maturation and regulation of the reproductive cycle in the human organism. GnRH interacts with the pituitary cells through the activation of the Gonadotropin Releasing Hormone Receptors (GnRHR). Any impairments/dysfunctions of the GnRH-GnRHR complex lead to the development of various cancer types and disorders. Furthermore, the identification of GnRHR as a potential drug target has led to the development of agonist and antagonist molecules implemented in various treatment protocols. The development of these drugs was based on the information derived from the functional studies of GnRH and GnRHR.

OBJECTIVE

This review aims at shedding light on the versatile function of GnRH and GnRH receptor and offers an apprehensive summary regarding the development of different agonists, antagonists and non-peptide GnRH analogues.

CONCLUSION

The information derived from these studies can enhance our understanding of the GnRH-GnRHR versatile nature and offer valuable insight into the design of new more potent molecules.

Machine learning for predicting lifespan-extending chemical compounds

Increasing age is a risk factor for many diseases; therefore developing pharmacological interventions that slow down ageing and consequently postpone the onset of many age-related diseases is highly desirable. In this work we analyse data from the DrugAge database, which contains chemical compounds and their effect on the lifespan of model organisms. Predictive models were built using the machine learning method random forests to predict whether or not a chemical compound will increase Caenorhabditis elegans' lifespan, using as features Gene Ontology (GO) terms annotated for proteins targeted by the compounds and chemical descriptors calculated from each compound's chemical structure. The model with the best predictive accuracy used both biological and chemical features, achieving a prediction accuracy of 80%. The top 20 most important GO terms include those related to mitochondrial processes, to enzymatic and immunological processes, and terms related to metabolic and transport processes. We applied our best model to predict compounds which are more likely to increase C. elegans' lifespan in the DGIdb database, where the effect of the compounds on an organism's lifespan is unknown. The top hit compounds can be broadly divided into four groups: compounds affecting mitochondria, compounds for cancer treatment, anti-inflammatories, and compounds for gonadotropin-releasing hormone therapies.