AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Fructose-1,6-bisphosphatase 1

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.

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.

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 employ our advanced, specialised process to create 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

P09467

UPID:

F16P1_HUMAN

Alternative names:

D-fructose-1,6-bisphosphate 1-phosphohydrolase 1; Liver FBPase

Alternative UPACC:

P09467; O75571; Q53F94; Q96E46

Background:

Fructose-1,6-bisphosphatase 1, known alternatively as D-fructose-1,6-bisphosphate 1-phosphohydrolase 1 or Liver FBPase, is pivotal in gluconeogenesis. It catalyzes the conversion of fructose 1,6-bisphosphate to fructose 6-phosphate, a key step in glucose production from non-carbohydrate sources. This enzyme's activity is essential for maintaining blood glucose levels during fasting. It also influences insulin secretion, glycerol conversion in the liver, and plays a crucial role in appetite regulation and body weight management by modulating satiety hormones.

Therapeutic significance:

Fructose-1,6-bisphosphatase deficiency, a metabolic disorder resulting from gene variants affecting this enzyme, underscores its clinical importance. This condition manifests with hypoglycemia and metabolic acidosis, potentially lethal in infants and young children. Understanding the enzyme's role could lead to innovative treatments for this deficiency and contribute to managing diabetes and obesity by influencing glucose metabolism and appetite regulation.

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