AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Phospholysine phosphohistidine inorganic pyrophosphate phosphatase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher activity, selectivity, and safety.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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.

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

 Fig. 1. The sreening 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 stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9H008

UPID:

LHPP_HUMAN

Alternative names:

-

Alternative UPACC:

Q9H008; B3KP20; Q2TBE9; Q5VUV9; Q5VUW0

Background:

The Phospholysine phosphohistidine inorganic pyrophosphate phosphatase, encoded by the gene with accession number Q9H008, plays a crucial role in cellular processes through its ability to hydrolyze a variety of substrates including imidodiphosphate, 3-phosphohistidine, and 6-phospholysine. Its broad substrate specificity extends to the hydrolysis of inorganic diphosphate, albeit at a lower efficiency.

Therapeutic significance:

Understanding the role of Phospholysine phosphohistidine inorganic pyrophosphate phosphatase could open doors to potential therapeutic strategies.

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