Focused On-demand Library for F-box-like/WD repeat-containing protein TBL1XR1

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 pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

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.

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

 Fig. 1. The sreening workflow of Receptor.AI

Our methodology leverages molecular simulations to examine a vast array of proteins, capturing their dynamics in both isolated forms and in complexes with other proteins. Through ensemble virtual screening, we thoroughly account for the protein's conformational mobility, identifying critical binding sites within functional regions and distant allosteric locations. This detailed exploration ensures that we comprehensively assess every possible mechanism of action, with the objective of identifying novel therapeutic targets and lead compounds that span a wide spectrum of biological functions.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







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


F-box-like/WD repeat-containing protein TBL1XR1, also known as Nuclear receptor corepressor/HDAC3 complex subunit TBLR1, plays a pivotal role in transcription activation mediated by nuclear receptors. It acts as an essential component of the N-Cor corepressor complex, facilitating the recruitment of the 19S proteasome complex, leading to proteasomal degradation of the N-Cor complex, thereby enabling cofactor exchange and transcription activation.

Therapeutic significance:

TBL1XR1 is implicated in Pierpont syndrome and Intellectual developmental disorder, autosomal dominant 41, diseases characterized by developmental delays, learning disabilities, and distinctive physical features. Understanding the role of TBL1XR1 could open doors to potential therapeutic strategies for these conditions.

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