Focused On-demand Library for Potassium channel subfamily T member 1

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.


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.


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


 

Fig. 1. The screening workflow of Receptor.AI

This process includes comprehensive molecular simulations of the ion channel in its native membrane environment, depicting its open, closed, and inactivated states, and ensemble virtual screening that accounts for conformational mobility in each state. Tentative binding pockets are investigated inside the pore, at the gating region, and in allosteric sites to cover the full spectrum of possible mechanisms of action.


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
Q5JUK3

UPID:
KCNT1_HUMAN

ALTERNATIVE NAMES:
KCa4.1

ALTERNATIVE UPACC:
Q5JUK3; B3KXF7; B7ZVY4; B9EGP2; G5E9V0; Q9P2C5

BACKGROUND:
The protein KCa4.1, alternatively named Potassium channel subfamily T member 1, is integral to regulating neuronal activity through its role as an outwardly rectifying potassium channel. It is activated by elevated levels of intracellular sodium or chloride and upon stimulation by specific G-protein coupled receptors. The regulation of KCa4.1 may also involve calcium signaling, highlighting its complex control mechanisms in neuronal function.

THERAPEUTIC SIGNIFICANCE:
Involvement of KCa4.1 in disorders such as Developmental and Epileptic Encephalopathy 14 and Epilepsy, Nocturnal Frontal Lobe, 5, underscores its clinical significance. These diseases, marked by intractable seizures and cognitive impairments, are linked to genetic variants affecting KCa4.1. Targeting KCa4.1's function presents a promising avenue for developing novel treatments for these challenging epileptic conditions.

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