Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Q9NPD8

UPID:
UBE2T_HUMAN

ALTERNATIVE NAMES:
Cell proliferation-inducing gene 50 protein; E2 ubiquitin-conjugating enzyme T; Ubiquitin carrier protein T; Ubiquitin-protein ligase T

ALTERNATIVE UPACC:
Q9NPD8; Q2TU36

BACKGROUND:
The Ubiquitin-conjugating enzyme E2 T, known for its involvement in mitomycin-C-induced DNA repair, acts as a specific E2 ubiquitin-conjugating enzyme for the Fanconi anemia complex. It is instrumental in the monoubiquitination of FANCD2 and FANCI, key processes in the DNA damage repair pathway, and prefers 'Lys-11', 'Lys-27', 'Lys-48', and 'Lys-63'-linked polyubiquitination.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Ubiquitin-conjugating enzyme E2 T could open doors to potential therapeutic strategies for treating Fanconi anemia, a disease marked by anemia, leukopenia, thrombopenia, and a higher risk of malignancies, by enhancing DNA repair mechanisms.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.