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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q9UPN9

UPID:
TRI33_HUMAN

ALTERNATIVE NAMES:
Ectodermin homolog; RET-fused gene 7 protein; RING-type E3 ubiquitin transferase TRIM33; Transcription intermediary factor 1-gamma; Tripartite motif-containing protein 33

ALTERNATIVE UPACC:
Q9UPN9; O95855; Q5TG72; Q5TG73; Q5TG74; Q9C017; Q9UJ79

BACKGROUND:
The protein E3 ubiquitin-protein ligase TRIM33, with alternative names such as RET-fused gene 7 protein and Tripartite motif-containing protein 33, serves as a transcriptional repressor and a regulator of cell proliferation. It uniquely monoubiquitinates SMAD4, impairing its ability to form a stable complex with activated SMAD2/3, which results in the inhibition of the TGF-beta/BMP signaling pathway.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of E3 ubiquitin-protein ligase TRIM33 offers a promising avenue for the development of novel therapeutic interventions.

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