AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Probable crossover junction endonuclease EME2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner 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 employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening 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.

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

Reaxense

upacc

A4GXA9

UPID:

EME2_HUMAN

Alternative names:

-

Alternative UPACC:

A4GXA9; Q8TEP2; Q96RY3

Background:

The Probable crossover junction endonuclease EME2, identified by the accession number A4GXA9, plays a crucial role in DNA repair mechanisms. It forms a complex with MUS81 to create a DNA structure-specific endonuclease, which is vital for cleaving substrates like 3'-flap structures. This activity is essential for maintaining genomic stability and preventing mutations.

Therapeutic significance:

Understanding the role of Probable crossover junction endonuclease EME2 could open doors to potential therapeutic strategies. Its involvement in DNA repair pathways suggests its potential as a target for developing treatments aimed at enhancing the DNA repair capacity of cells, which is particularly relevant in the context of cancer therapy.

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