AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Follicle-stimulating hormone receptor

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

Our top-notch dedicated system is used to design specialised libraries for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

The method involves detailed molecular simulations of the receptor in its native membrane environment, with ensemble virtual screening focusing on its conformational mobility. When dealing with dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets on and between the subunits are established to address all possible mechanisms of action.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

upacc

P23945

UPID:

FSHR_HUMAN

Alternative names:

Follitropin receptor

Alternative UPACC:

P23945; A0A0A0MSC5; A8K947; G5CBS7; G5E967; J3KQ00; Q05AH0; Q16225; Q4QRJ3; Q4ZFZ2; Q53RW2

Background:

The Follicle-stimulating hormone receptor (FSHR), also known as the Follitropin receptor, is a G protein-coupled receptor essential for reproductive biology. It binds to follitropin, activating cAMP production and downstream PI3K-AKT and ERK1/ERK2 signaling pathways, pivotal for ovarian and testicular function.

Therapeutic significance:

FSHR's involvement in diseases such as Ovarian dysgenesis 1 and Ovarian hyperstimulation syndrome highlights its critical role in reproductive health. Targeting FSHR could lead to innovative treatments for these conditions, offering hope to individuals facing infertility challenges.

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