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 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 utilise our cutting-edge, exclusive workflow to develop focused 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 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
Q6Q4G3

UPID:
AMPQ_HUMAN

ALTERNATIVE NAMES:
CHL2 antigen; Laeverin

ALTERNATIVE UPACC:
Q6Q4G3; A8K6J0; C9JGD2; Q32MR1; Q4G0I9; Q4G0V2; Q86XA3; Q8NBZ2

BACKGROUND:
Aminopeptidase Q, recognized alternatively as Laeverin or CHL2 antigen, plays a crucial role in the regulation of peptide activity crucial for successful placentation. It exhibits a strong substrate preference, notably for Leu-4-methylcoumaryl-7-amide, and is involved in the processing of several key peptides, including angiotensin-3 and kisspeptin-10, which are vital for embryo-maternal interaction.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Aminopeptidase Q offers a promising pathway to uncover novel therapeutic approaches.

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