AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for E3 ubiquitin-protein ligase RNF31

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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 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.

partner

Reaxense

upacc

Q96EP0

UPID:

RNF31_HUMAN

Alternative names:

HOIL-1-interacting protein; RING finger protein 31; RING-type E3 ubiquitin transferase RNF31; Zinc in-between-RING-finger ubiquitin-associated domain protein

Alternative UPACC:

Q96EP0; A0A962; Q86VI2; Q8TEI0; Q96GB4; Q96NF1; Q9H5F1; Q9NWD2

Background:

E3 ubiquitin-protein ligase RNF31, also known as HOIL-1-interacting protein, plays a pivotal role in the regulation of inflammation and NF-kappa-B activation through its involvement in the LUBAC complex. This complex is crucial for conjugating linear polyubiquitin chains to substrates, thereby influencing key signaling pathways such as the canonical NF-kappa-B and JNK pathways. RNF31's function extends to preventing TNF-induced cell death, promoting innate immunity, and regulating the canonical Wnt signaling during angiogenesis.

Therapeutic significance:

Understanding the role of E3 ubiquitin-protein ligase RNF31 could open doors to potential therapeutic strategies.

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