AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for E3 ubiquitin-protein ligase RNF216

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.

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.

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.

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.

partner

Reaxense

upacc

Q9NWF9

UPID:

RN216_HUMAN

Alternative names:

RING finger protein 216; RING-type E3 ubiquitin transferase RNF216; Triad domain-containing protein 3; Ubiquitin-conjugating enzyme 7-interacting protein 1; Zinc finger protein inhibiting NF-kappa-B

Alternative UPACC:

Q9NWF9; Q6Y691; Q75ML7; Q7Z2H7; Q7Z7C1; Q8NHW7; Q9NYT1

Background:

E3 ubiquitin-protein ligase RNF216, known for its roles as an E3 ubiquitin ligase, is pivotal in cellular processes through the ubiquitination pathway. It is involved in the degradation of key signaling molecules such as TRAF3, TLR4, and TLR9, playing a crucial role in antiviral responses and immune regulation. Its alternative names include RING finger protein 216 and Zinc finger protein inhibiting NF-kappa-B.

Therapeutic significance:

RNF216's mutation is linked to Gordon Holmes syndrome, characterized by cerebellar ataxia and hypogonadism, highlighting its therapeutic potential. Understanding RNF216's function could lead to novel treatments for this syndrome and other ubiquitin-mediated diseases.

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