Focused On-demand Library for Monoglyceride lipase

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.


We employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

PARTNER
Receptor.AI
 
UPACC
Q99685

UPID:
MGLL_HUMAN

ALTERNATIVE NAMES:
HU-K5; Lysophospholipase homolog; Lysophospholipase-like; Monoacylglycerol lipase

ALTERNATIVE UPACC:
Q99685; B3KRC2; B7Z9D1; Q6IBG9; Q96AA5

BACKGROUND:
The enzyme Monoglyceride lipase, also referred to as HU-K5 or Lysophospholipase-like, is pivotal in breaking down monoacylglycerides into glycerol and free fatty acids. This process is essential for endocannabinoid signaling and nociperception. Additionally, it plays a role in modulating fatty acids that are key in tumor growth and metastasis.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Monoglyceride lipase offers a pathway to novel therapeutic approaches. Its critical role in endocannabinoid signaling and cancer progression makes it a promising target for developing treatments for pain and cancer.

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.


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