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

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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 use our state-of-the-art dedicated workflow for designing focused 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.

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

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:

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.