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ANTAGONIST - Astrophysics Data System

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Last Updated: 10 August 2022

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A Ligand-and-structure Dual-driven Deep Learning Method for the Discovery of Highly Potent GnRH1R Antagonist to treat Uterine Diseases

Gonadotrophin-releasing hormone receptor receptor, which is a promising therapeutic target for the treatment of uterine diseases. Several GnRH1R antagonists are currently available in clinical trials without satisfying multiple property constraints. We're trying to create a deep learning-based framework to enable the rapid and cost-effective discovery of a new orally active small-molecule drug targeting GnRH1R with desired properties. In vitro and in vivo studies showed that three of them had potent inhibition capabilities against GnRH1R, and that compound 5 delivered good results in basic PK traits, such as half-life, oral bioavailability, and PPB, among other things. The proposed ligand-and-structure combined molecular generative model and the complete computer-aided workflow may be adapted to similar tasks for de novo drug design or lead optimization.

Source link: https://ui.adsabs.harvard.edu/abs/2022arXiv220711547L/abstract

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions