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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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 employ our advanced, specialised process to create targeted 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
Q9BV23

UPID:
ABHD6_HUMAN

ALTERNATIVE NAMES:
2-arachidonoylglycerol hydrolase; Abhydrolase domain-containing protein 6

ALTERNATIVE UPACC:
Q9BV23; B2R7Y9; Q6ZMF7

BACKGROUND:
The enzyme Monoacylglycerol lipase ABHD6, alternatively known as 2-arachidonoylglycerol hydrolase, is integral to lipid signaling and metabolism. It preferentially targets medium-chain saturated monoacylglycerols for hydrolysis, including the endocannabinoid 2-arachidonoylglycerol, thereby modulating endocannabinoid signaling. Additionally, ABHD6 has lysophosphatidyl lipase activity and is vital for the catabolism of bis(monoacylglycero)phosphate (BMP), which influences lipid sorting and the formation of intraluminal vesicles in late endosomes and lysosomes.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Monoacylglycerol lipase ABHD6 offers a promising avenue for developing novel therapeutic approaches in the realm of lipid-related disorders and endocannabinoid system dysregulation.

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