Focused On-demand Libraries - Receptor.AI 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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


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
Receptor.AI
 
UPACC
Q9BZK7

UPID:
TBL1R_HUMAN

ALTERNATIVE NAMES:
Nuclear receptor corepressor/HDAC3 complex subunit TBLR1; TBL1-related protein 1; Transducin beta-like 1X-related protein 1

ALTERNATIVE UPACC:
Q9BZK7; D3DNQ9; Q14DC3; Q9H2I1; Q9H9A1

BACKGROUND:
The protein TBL1XR1, with alternative names such as Transducin beta-like 1X-related protein 1, is integral to the ubiquitin/19S proteasome complex's recruitment to nuclear receptor-regulated transcription units. Its function is crucial for the activation of transcription mediated by nuclear receptors, highlighting its role in gene expression regulation.

THERAPEUTIC SIGNIFICANCE:
Involvement of TBL1XR1 in disorders like Pierpont syndrome and Intellectual developmental disorder, autosomal dominant 41, underscores its potential as a target for therapeutic intervention. Exploring TBL1XR1's function offers a promising pathway for developing treatments for these genetic conditions.

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