AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ubiquitin-conjugating enzyme E2 R1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our collaborator, Reaxense, aids in their synthesis and provision.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening 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.

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

Reaxense

upacc

P49427

UPID:

UB2R1_HUMAN

Alternative names:

(E3-independent) E2 ubiquitin-conjugating enzyme R1; E2 ubiquitin-conjugating enzyme R1; Ubiquitin-conjugating enzyme E2-32 kDa complementing; Ubiquitin-conjugating enzyme E2-CDC34; Ubiquitin-protein ligase R1

Alternative UPACC:

P49427; A8K689

Background:

Ubiquitin-conjugating enzyme E2 R1, known for its pivotal role in protein ubiquitination, facilitates the covalent attachment of ubiquitin to target proteins, a process critical for cellular regulation. This enzyme is instrumental in 'Lys-48'-linked polyubiquitination, influencing protein degradation via the proteasome pathway. It collaborates with E2 UBCH5C and SCF(FBXW11) for NFKBIA degradation, and with SCF(SKP2) in cell proliferation by targeting MYBL2 and KIP1. Additionally, it plays a role in the cell cycle, particularly in the G2/M phase by targeting WEE1 kinase.

Therapeutic significance:

Understanding the role of Ubiquitin-conjugating enzyme E2 R1 could open doors to potential therapeutic strategies.

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