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

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize activity and selectivity.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.







Alternative names:

Bendless-like ubiquitin-conjugating enzyme; E2 ubiquitin-conjugating enzyme N; Ubc13; UbcH13; Ubiquitin carrier protein N; Ubiquitin-protein ligase N

Alternative UPACC:

P61088; Q16781; Q53Y81


Ubiquitin-conjugating enzyme E2 N (Ubc13) plays a pivotal role in DNA repair, cell cycle progression, and differentiation. It forms heterodimers with UBE2V1 or UBE2V2 to catalyze 'Lys-63'-linked polyubiquitination, crucial for non-proteasomal protein regulation, transcriptional activation, and DNA damage response. Ubc13's involvement in 'Lys-63'-linked polyubiquitination of PCNA and JKAMP underlines its significance in maintaining genomic stability and protein homeostasis.

Therapeutic significance:

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

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