Focused On-demand Library for NEDD4-like E3 ubiquitin-protein ligase WWP2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We use our state-of-the-art dedicated workflow for designing focused 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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







Alternative names:

Atrophin-1-interacting protein 2; HECT-type E3 ubiquitin transferase WWP2; WW domain-containing protein 2

Alternative UPACC:

O00308; A6NEP1; B2R706; B4DTL5; F5H213; H3BRF3; I3RSG8; Q6ZTQ5; Q96CZ2; Q9BWN6


NEDD4-like E3 ubiquitin-protein ligase WWP2, also known as Atrophin-1-interacting protein 2 and WW domain-containing protein 2, plays a crucial role in protein ubiquitination. It facilitates the transfer of ubiquitin to substrates, influencing their degradation or functional modification. WWP2 targets several proteins for ubiquitination, including POU5F1, EGR2, SLC11A2, and RPB1, affecting processes in embryonic stem cells, T-cells, and beyond.

Therapeutic significance:

Understanding the role of NEDD4-like E3 ubiquitin-protein ligase WWP2 could open doors to potential therapeutic strategies. Its involvement in the regulation of key proteins through ubiquitination highlights its potential as a target for modulating cellular processes in disease states.

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