Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 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 screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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
Q96BH1

UPID:
RNF25_HUMAN

ALTERNATIVE NAMES:
RING finger protein 25; RING finger protein AO7

ALTERNATIVE UPACC:
Q96BH1; A8K0D6; Q53HQ5; Q9H874

BACKGROUND:
The E3 ubiquitin-protein ligase RNF25, recognized alternatively as RING finger protein AO7, is integral to the translation quality control pathway, particularly during ribosome stalling. It facilitates the ubiquitination and subsequent degradation of specific translation factors and ribosomal proteins, such as RPL0 and RPS17, on stalled ribosomes. RNF25's function extends to the ubiquitination of ETF1/eRF1 and NKD2, and it potentially influences NF-kappa-B transcriptional activity via RELA/p65 interaction.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of E3 ubiquitin-protein ligase RNF25 unveils potential avenues for therapeutic intervention.

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