Focused On-demand Library for Potassium channel subfamily K member 9

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create targeted 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.


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
Q9NPC2

UPID:
KCNK9_HUMAN

ALTERNATIVE NAMES:
Acid-sensitive potassium channel protein TASK-3; TWIK-related acid-sensitive K(+) channel 3; Two pore potassium channel KT3.2

ALTERNATIVE UPACC:
Q9NPC2; Q2M290; Q540F2

BACKGROUND:
The protein Potassium channel subfamily K member 9, known as TASK-3, functions as a background potassium channel protein sensitive to pH changes but not to voltage. It is essential for setting the resting membrane potential in neurons, highlighting its significance in neurophysiology. TASK-3 is recognized by several names, including Acid-sensitive potassium channel protein TASK-3 and TWIK-related acid-sensitive K(+) channel 3.

THERAPEUTIC SIGNIFICANCE:
Given its pivotal role in Birk-Barel syndrome, characterized by a spectrum of neurological and physical anomalies, TASK-3 presents a valuable target for therapeutic intervention. The exploration of TASK-3's function and its modulation could lead to novel treatments for this syndrome.

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