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.


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 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 utilise our cutting-edge, exclusive workflow to develop focused 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.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
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:
The Ubiquitin-conjugating enzyme E2 R1, also known as E2 ubiquitin-conjugating enzyme R1, plays a crucial role in the ubiquitin-proteasome system. This enzyme is key in catalyzing the attachment of ubiquitin to substrates, facilitating their subsequent degradation. It is involved in various cellular processes including the degradation of NFKBIA, regulation of cell proliferation through MYBL2 and KIP1, and the cell cycle's G2/M phase transition by targeting WEE1 kinase for degradation. Its activity is essential for maintaining cellular homeostasis and responding to stress.

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

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