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 promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.


 

Fig. 1. The screening 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q9HA64

UPID:
KT3K_HUMAN

ALTERNATIVE NAMES:
Fructosamine-3-kinase-related protein; Protein-psicosamine 3-kinase FN3KRP

ALTERNATIVE UPACC:
Q9HA64; Q969F4; Q9H0U7

BACKGROUND:
The enzyme Ketosamine-3-kinase, with alternative names Fructosamine-3-kinase-related protein and Protein-psicosamine 3-kinase FN3KRP, is pivotal in the process of deglycating proteins. It specifically phosphorylates ribuloselysine and psicoselysine on glycated proteins to form ribuloselysine-3 phosphate and psicoselysine-3 phosphate, respectively. These products naturally decompose, indicating the enzyme's essential function in reversing the modifications caused by glycation.

THERAPEUTIC SIGNIFICANCE:
The exploration of Ketosamine-3-kinase's function offers a promising avenue for developing new therapeutic approaches. Its key role in mitigating the effects of protein glycation underscores its potential in addressing diseases linked to protein damage and aging.

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