Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 use our state-of-the-art dedicated workflow for designing focused libraries for receptors.


 

Fig. 1. The screening workflow of Receptor.AI

It includes extensive molecular simulations of the receptor in its native membrane environment and the ensemble virtual screening accounting for its conformational mobility. In the case of dimeric or oligomeric receptors, the whole functional complex is modelled, and the tentative binding pockets are determined on and between the subunits to cover the whole spectrum of possible mechanisms of action.


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
Q13304

UPID:
GPR17_HUMAN

ALTERNATIVE NAMES:
G-protein coupled receptor 17; P2Y-like receptor; R12

ALTERNATIVE UPACC:
Q13304; A8K9L0; B2R9X0; Q8N5S7; Q9UDZ6; Q9UE21

BACKGROUND:
The Uracil nucleotide/cysteinyl leukotriene receptor, also referred to as G-protein coupled receptor 17, P2Y-like receptor, or R12, is integral to the regulation of cellular responses to uracil nucleotides and CysLTs. Its ability to signal through G(i) proteins and the subsequent inhibition of adenylyl cyclase underscores its importance in cellular signaling mechanisms, particularly in the context of brain ischemia.

THERAPEUTIC SIGNIFICANCE:
Exploring the Uracil nucleotide/cysteinyl leukotriene receptor's signaling pathways offers a promising avenue for the development of novel therapeutic interventions. Given its critical role in brain damage following ischemia, targeting this receptor could lead to breakthroughs in treating or preventing ischemic brain injuries.

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