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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


We utilise our cutting-edge, exclusive workflow to develop focused 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 is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P00491

UPID:
PNPH_HUMAN

ALTERNATIVE NAMES:
Inosine phosphorylase; Inosine-guanosine phosphorylase

ALTERNATIVE UPACC:
P00491; B2R8S5; D3DS00; Q15160; Q5PZ03

BACKGROUND:
The enzyme Purine nucleoside phosphorylase, with alternative names Inosine phosphorylase and Inosine-guanosine phosphorylase, is pivotal in purine metabolism. It facilitates the phosphorolytic breakdown, generating free purine bases and pentose-1-phosphate, with a preference for 6-oxopurine nucleosides such as inosine and guanosine.

THERAPEUTIC SIGNIFICANCE:
Deficiency in Purine nucleoside phosphorylase leads to severe T-cell immunodeficiency and recurrent infections, highlighting its critical role in immune response. The enzyme's dysfunction is linked to Purine nucleoside phosphorylase deficiency, underscoring the importance of targeted therapeutic interventions to mitigate this genetic disorder.

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