Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved 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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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
Q969M7

UPID:
UBE2F_HUMAN

ALTERNATIVE NAMES:
NEDD8 carrier protein UBE2F; NEDD8 protein ligase UBE2F; NEDD8-conjugating enzyme 2; RING-type E3 NEDD8 transferase UBE2F; Ubiquitin-conjugating enzyme E2 F

ALTERNATIVE UPACC:
Q969M7; A8K1Z8; B4DDT9; B4DFI1; B4DMK3; B4DZU2; B8ZZG2; C9J212; H9KVB9

BACKGROUND:
The NEDD8-conjugating enzyme UBE2F, known by alternative names such as NEDD8 carrier protein UBE2F and Ubiquitin-conjugating enzyme E2 F, is crucial for the neddylation process. It facilitates the covalent attachment of NEDD8 to other proteins, a key step in protein modification. Its selective interaction with RBX2 over RBX1 for neddylating targets like CUL5 highlights its specificity in cellular processes.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of NEDD8-conjugating enzyme UBE2F unveils new avenues for developing therapeutic interventions.

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