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.


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


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

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
Receptor.AI
 
UPACC
Q5VTB9

UPID:
RN220_HUMAN

ALTERNATIVE NAMES:
RING finger protein 220; RING-type E3 ubiquitin transferase RNF220

ALTERNATIVE UPACC:
Q5VTB9; B3KPJ3; B4DLZ9; E9PCS1; Q4KMX2; Q9NVP6

BACKGROUND:
The E3 ubiquitin-protein ligase RNF220, known for its ubiquitination and proteasomal degradation of SIN3B, also stabilizes CTNNB1 through USP7-mediated deubiquitination, promoting Wnt signaling. Its critical role in nuclear lamina regulation underscores its importance in cellular function and structure.

THERAPEUTIC SIGNIFICANCE:
Given its association with a specific neurodegenerative disorder, exploring E3 ubiquitin-protein ligase RNF220's function offers a promising avenue for developing targeted therapies for Leukodystrophy, hypomyelinating, 23. This protein's study could lead to groundbreaking treatments for patients suffering from this debilitating condition.

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