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 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.


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.


PARTNER
Receptor.AI
 
UPACC
O14981

UPID:
BTAF1_HUMAN

ALTERNATIVE NAMES:
ATP-dependent helicase BTAF1; B-TFIID transcription factor-associated 170 kDa subunit; TAF(II)170; TBP-associated factor 172

ALTERNATIVE UPACC:
O14981; B4E0W6; O43578

BACKGROUND:
The protein TATA-binding protein-associated factor 172, with aliases such as ATP-dependent helicase BTAF1, is integral to transcription regulation. It facilitates the removal of TBP from the TATA box, an essential step for the transcription initiation process, operating in an ATP-dependent manner. This protein is also known by names like B-TFIID transcription factor-associated 170 kDa subunit and TAF(II)170.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionality of TATA-binding protein-associated factor 172 offers a promising avenue for developing novel therapeutic interventions. Its critical role in the transcription initiation process makes it a potential target for modulating disease-related gene expression.

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