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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


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
Q05469

UPID:
LIPS_HUMAN

ALTERNATIVE NAMES:
Monoacylglycerol lipase LIPE; Retinyl ester hydrolase

ALTERNATIVE UPACC:
Q05469; Q3LRT2; Q6NSL7

BACKGROUND:
The enzyme Hormone-sensitive lipase, known for its alternative names Monoacylglycerol lipase LIPE and Retinyl ester hydrolase, is integral to the hydrolysis of various lipid molecules. Its ability to preferentially hydrolyze diacylglycerols over triacylglycerols and monoacylglycerols, and its specific action on the fatty acid esters at different positions of the glycerol backbone, highlight its critical role in lipid metabolism. This enzyme is vital in mobilizing stored triglycerides in adipose tissue and heart, and in the production of free cholesterol in steroidogenic tissues.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Hormone-sensitive lipase could open doors to potential therapeutic strategies. Its direct link to Lipodystrophy, familial partial, 6, through gene variants, presents a unique opportunity to develop targeted therapies for this and potentially other metabolic diseases, emphasizing the enzyme's significance in drug discovery.

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