Focused On-demand Libraries - Receptor.AI 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.


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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


Our top-notch dedicated system is used to design specialised 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.


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
O00757

UPID:
F16P2_HUMAN

ALTERNATIVE NAMES:
D-fructose-1,6-bisphosphate 1-phosphohydrolase 2; Muscle FBPase

ALTERNATIVE UPACC:
O00757; Q17R39; Q6FI53

BACKGROUND:
D-fructose-1,6-bisphosphate 1-phosphohydrolase 2, commonly referred to as Muscle FBPase, is integral to the process of converting fructose 1,6-bisphosphate into fructose 6-phosphate, a critical step in glycogen synthesis from lactate and other carbohydrates. This enzyme's activity is crucial for maintaining energy balance within muscle tissues.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in a rare autosomal dominant disorder that affects neurological development and myelination, the study of Muscle FBPase offers promising avenues for therapeutic intervention. The enzyme's role in metabolic pathways highlights its potential as a target for treating Leukodystrophy, childhood-onset, remitting, and possibly other metabolic disorders.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.