AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Retinoic acid receptor RXR-alpha

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

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

P19793

UPID:

RXRA_HUMAN

Alternative names:

Nuclear receptor subfamily 2 group B member 1; Retinoid X receptor alpha

Alternative UPACC:

P19793; B3KY83; Q2NL52; Q2V504

Background:

Retinoic acid receptor RXR-alpha, also known as Nuclear receptor subfamily 2 group B member 1, is a pivotal transcription factor activated by retinoic acid. It forms dimers with retinoic acid receptors (RARs) to regulate gene expression in vital biological processes. This protein binds to retinoic acid response elements (RARE) to modulate transcription, playing a crucial role in various cellular functions including lipid metabolism, immune response, and cellular differentiation.

Therapeutic significance:

Understanding the role of Retinoic acid receptor RXR-alpha could open doors to potential therapeutic strategies. Its involvement in transcription regulation and cellular processes highlights its potential as a target for drug discovery, aiming to modulate gene expression in diseases where these pathways are disrupted.

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