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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
O60928

UPID:
KCJ13_HUMAN

ALTERNATIVE NAMES:
Inward rectifier K(+) channel Kir7.1; Potassium channel, inwardly rectifying subfamily J member 13

ALTERNATIVE UPACC:
O60928; A0PGH1; O76023; Q53SA1; Q8N3Y4

BACKGROUND:
The protein Inward rectifier potassium channel 13, with alternative names Kir7.1 and Potassium channel, inwardly rectifying subfamily J member 13, is pivotal for potassium ion transport into cells. Its function is essential for the electrical stability of cells and is influenced by the concentration of extracellular potassium.

THERAPEUTIC SIGNIFICANCE:
Mutations in KCNJ13 are causative factors in diseases such as Snowflake vitreoretinal degeneration and Leber congenital amaurosis 16, highlighting its significance in ocular health. Targeting KCNJ13 could provide innovative approaches to treating these hereditary eye diseases.

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