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.


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 top-notch dedicated system is used to design specialised 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
Q8IY26

UPID:
PLPP6_HUMAN

ALTERNATIVE NAMES:
Lipid phosphatase-related protein-B; PA-PSP; Phosphatidic acid phosphatase type 2 domain-containing protein 2; Phospholipid phosphatase 6; Presqualene diphosphate phosphatase; Type 1 polyisoprenoid diphosphate phosphatase

ALTERNATIVE UPACC:
Q8IY26; B3KY05; Q5JVJ6; Q8NCK9

BACKGROUND:
The enzyme Polyisoprenoid diphosphate/phosphate phosphohydrolase PLPP6, with alternative names such as PA-PSP and Phospholipid phosphatase 6, is integral to lipid metabolism. It dephosphorylates presqualene, farnesyl, and geranylgeranyl diphosphates, crucial for cholesterol synthesis and protein modification. Additionally, it plays a role in phospholipids and triacylglycerols biosynthesis, indicating its broad impact on cellular lipid composition.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Polyisoprenoid diphosphate/phosphate phosphohydrolase PLPP6 offers a promising avenue for developing novel therapeutic approaches. Its pivotal role in lipid metabolism and signaling pathways makes it a compelling target for addressing metabolic and immune-related diseases.

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