Focused On-demand Libraries - Receptor.AI 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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by 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.


Our high-tech, dedicated method is applied to construct targeted 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
Q6ZNA4

UPID:
RN111_HUMAN

ALTERNATIVE NAMES:
RING finger protein 111; RING-type E3 ubiquitin transferase Arkadia

ALTERNATIVE UPACC:
Q6ZNA4; C9JUS4; H0YN55; Q6P9A4; Q6ZMU2; Q7L428; Q7Z346; Q8N1P9; Q8WUA3; Q9NSR1

BACKGROUND:
The protein E3 ubiquitin-protein ligase Arkadia, recognized for its ubiquitination and proteasomal degradation of SMAD inhibitors, is crucial for enhancing TGF-beta and BMP transcriptional responses. It ensures the turnover of SMAD2/SMAD3 effectors by coupling their activation with degradation. Arkadia's involvement in nucleotide excision repair through 'Lys-63'-linked ubiquitination of sumoylated XPC in response to UV irradiation highlights its role in DNA repair mechanisms.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of E3 ubiquitin-protein ligase Arkadia could open doors to potential therapeutic strategies.

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