AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Growth hormone-releasing hormone receptor

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 high-tech, dedicated method is applied to construct targeted libraries for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

It includes extensive molecular simulations of the receptor in its native membrane environment and the ensemble virtual screening accounting for its conformational mobility. In the case of dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets are determined on and between the subunits to cover the whole spectrum of possible mechanisms of action.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q02643

UPID:

GHRHR_HUMAN

Alternative names:

Growth hormone-releasing factor receptor

Alternative UPACC:

Q02643; Q99863

Background:

The Growth hormone-releasing hormone receptor (GHRHR), encoded by the gene with accession number Q02643, plays a pivotal role in human growth processes. It acts as a receptor for GRF, coupling with G proteins to activate adenylyl cyclase, which in turn stimulates somatotroph cell growth, growth hormone gene transcription, and secretion.

Therapeutic significance:

GHRHR is directly implicated in Growth hormone deficiency, isolated, 4, a condition characterized by severe growth failure and short stature due to autosomal recessive deficiency of growth hormone. Understanding the role of GHRHR could open doors to potential therapeutic strategies, including growth hormone therapy which has shown positive responses in patients.

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