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 effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


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


 

Fig. 1. The screening workflow of Receptor.AI

This includes comprehensive molecular simulations of the receptor in its native membrane environment, paired with ensemble virtual screening that factors in its conformational mobility. In cases involving dimeric or oligomeric receptors, the entire functional complex is modelled, pinpointing potential binding pockets on and between the subunits to capture the full range of mechanisms of action.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P20309

UPID:
ACM3_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
P20309; Q0VAJ8; Q4QRI3; Q5VXY2; Q9HB60

BACKGROUND:
Muscarinic acetylcholine receptor M3, with the unique identifier P20309, orchestrates a spectrum of cellular activities. It achieves this through the inhibition of adenylate cyclase, the catalysis of phosphoinositide degradation, and the modulation of potassium channels, facilitated by G proteins. Its role is crucial in the signaling pathways mediated by the muscarinic acetylcholine receptor family.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Muscarinic acetylcholine receptor M3 could open doors to potential therapeutic strategies for Prune belly syndrome. This condition, marked by distinct abdominal and urinary tract malformations, is caused by genetic variants in the receptor's gene, highlighting its significance in disease pathology and treatment.

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