Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better 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 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.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
Q9H9V9

UPID:
JMJD4_HUMAN

ALTERNATIVE NAMES:
JmjC domain-containing protein 4; Jumonji domain-containing protein 4; Lysyl-hydroxylase JMJD4

ALTERNATIVE UPACC:
Q9H9V9; Q5TBZ1; Q5TBZ6; Q9H970

BACKGROUND:
2-oxoglutarate and iron-dependent oxygenase JMJD4, with its alternative names including JmjC domain-containing protein 4, Jumonji domain-containing protein 4, and Lysyl-hydroxylase JMJD4, is pivotal in post-translational modifications. Its specific activity involves the hydroxylation of ETF1 at 'Lys-63', a process essential for optimizing the efficiency of translational termination.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of 2-oxoglutarate and iron-dependent oxygenase JMJD4 holds promise for unveiling novel therapeutic avenues.

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