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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best 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

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.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
P0DPD7

UPID:
EFMT4_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
P0DPD7; A5PLK8; O60344; Q6NTG7; Q6UW36; Q8NFD7; Q96NX3; Q96NX4; Q9BRZ8

BACKGROUND:
The enzyme EEF1A lysine methyltransferase 4, with the unique identifier P0DPD7, is a key player in the post-translational modification of proteins. It specifically methylates the eukaryotic translation elongation factor 1 alpha at Lys-36, a process vital for the proper synthesis of proteins. This activity underscores the enzyme's significant role in maintaining the fidelity and efficiency of protein production within the cell.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of EEF1A lysine methyltransferase 4 offers a promising avenue for drug discovery. Given its critical role in protein synthesis, targeting this enzyme could lead to innovative treatments for conditions characterized by abnormal protein production. The potential to modulate its activity opens up new possibilities for therapeutic intervention in a range of diseases.

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