AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Fructosamine-3-kinase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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 our partner 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 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 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

Reaxense

upacc

Q9H479

UPID:

FN3K_HUMAN

Alternative names:

Protein-psicosamine 3-kinase FN3K; Protein-ribulosamine 3-kinase FN3K

Alternative UPACC:

Q9H479

Background:

Fructosamine-3-kinase, known by its alternative names Protein-psicosamine 3-kinase FN3K and Protein-ribulosamine 3-kinase FN3K, plays a pivotal role in protein deglycation. It achieves this by phosphorylating fructoselysine residues on glycated proteins to generate fructoselysine-3 phosphate, which decomposes under physiological conditions. This enzyme is crucial in erythrocytes' intracellular deglycation and responds to oxidative stress by deglycating NFE2L2/NRF2, enhancing its function.

Therapeutic significance:

Understanding the role of Fructosamine-3-kinase could open doors to potential therapeutic strategies.

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