AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Potassium channel subfamily K member 10

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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. Our collaborator, Reaxense, aids in their synthesis and provision.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage activity and selectivity.

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

Reaxense

upacc

P57789

UPID:

KCNKA_HUMAN

Alternative names:

Outward rectifying potassium channel protein TREK-2; TREK-2 K(+) channel subunit

Alternative UPACC:

P57789; B2R8T4; B2RCT3; B5TJL4; Q6B014; Q8TDK7; Q8TDK8; Q9HB59

Background:

The Potassium channel subfamily K member 10, known as TREK-2, is an outward rectifying potassium channel. It is characterized by its rapid activation and non-inactivating outward rectifier K(+) currents. TREK-2 is uniquely activated by arachidonic acid and other naturally occurring unsaturated free fatty acids, distinguishing it from other potassium channels.

Therapeutic significance:

Understanding the role of Potassium channel subfamily K member 10 could open doors to potential therapeutic strategies. Its unique activation mechanism and function in potassium ion transport make it a compelling target for drug discovery, aiming to modulate cellular excitability and related physiological processes.

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