AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Nuclear receptor ROR-beta

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 top-notch dedicated system is used to design specialised libraries for receptors.

 Fig. 1. The sreening workflow of Receptor.AI

It features thorough molecular simulations of the receptor within its native membrane environment, complemented by ensemble virtual screening that considers its conformational mobility. For dimeric or oligomeric receptors, the full functional complex is constructed, and tentative binding sites are determined on and between the subunits to cover the entire spectrum of potential mechanisms of action.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.

partner

Reaxense

upacc

Q92753

UPID:

RORB_HUMAN

Alternative names:

Nuclear receptor RZR-beta; Nuclear receptor subfamily 1 group F member 2; Retinoid-related orphan receptor-beta

Alternative UPACC:

Q92753; Q8WX73

Background:

Nuclear receptor ROR-beta, also known as Nuclear receptor subfamily 1 group F member 2, plays a pivotal role in various physiological processes. It binds DNA to regulate transcription of genes involved in the development of rod and cone photoreceptor cells, modulation of circadian rhythms, and neuronal patterning in the neocortex. Its activity is modulated by natural ligands like all-trans retinoic acid, which acts as an inverse agonist.

Therapeutic significance:

ROR-beta's involvement in idiopathic generalized epilepsy 15 highlights its potential as a therapeutic target. Understanding the role of Nuclear receptor ROR-beta could open doors to potential therapeutic strategies for managing epilepsy and possibly other neurological disorders.

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