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.


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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


Our top-notch dedicated system is used to design specialised libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.


Our library distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
Q9NPI9

UPID:
KCJ16_HUMAN

ALTERNATIVE NAMES:
Inward rectifier K(+) channel Kir5.1; Potassium channel, inwardly rectifying subfamily J member 16

ALTERNATIVE UPACC:
Q9NPI9

BACKGROUND:
The inward rectifier potassium channel 16, or Kir5.1, encoded by the KCNJ16 gene, is a key player in potassium ion transport across cellular membranes. Its ability to facilitate potassium influx over efflux is crucial for maintaining the electrochemical gradient essential for various physiological processes. In the renal system, KCNJ16 collaborates with KCNJ10 to ensure effective potassium recycling in the distal tubules, thereby supporting sodium reabsorption and the maintenance of fluid and pH equilibrium.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Inward rectifier potassium channel 16 could open doors to potential therapeutic strategies. Given its direct link to Hypokalemic tubulopathy and deafness, research into KCNJ16 offers a promising avenue for developing targeted therapies that could alleviate or even prevent the symptoms associated with this genetic disorder.

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