Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
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:
The Retinoic acid receptor RXR-alpha, a key player in the nuclear receptor signaling pathway, interacts with ligands like all-trans or 9-cis retinoic acid to activate gene transcription. It serves as a heterodimeric partner for several nuclear receptors, influencing fatty acid oxidation, vascular endothelial function, and immune response. This receptor's ability to switch between repressor and activator roles underscores its versatility in gene regulation.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Retinoic acid receptor RXR-alpha offers a promising avenue for developing novel therapeutic approaches. Its central role in mediating gene expression related to metabolism, immune modulation, and cell differentiation presents a unique opportunity for targeted interventions in metabolic disorders, inflammatory conditions, and cancer.

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