Focused On-demand Library for Potassium voltage-gated channel subfamily A member 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

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

 Fig. 1. The sreening workflow of Receptor.AI

It features detailed molecular simulations of the ion channel in its native membrane environment across its open, closed, and inactivated forms, coupled with ensemble virtual screening considering conformational mobility in these states. Potential binding sites are explored within the pore, in the gating region, and at allosteric locations to encompass all potential mechanisms of action.

Several key aspects differentiate our library:

  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.
  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.
  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.
  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.







Alternative names:

NGK1; Voltage-gated K(+) channel HuKIV; Voltage-gated potassium channel HBK5; Voltage-gated potassium channel subunit Kv1.2

Alternative UPACC:

P16389; A0A024R0D3; A8K1Z6; Q86XG6


Potassium voltage-gated channel subfamily A member 2 (KCNA2) is pivotal in mediating transmembrane potassium transport in excitable membranes, notably in the brain and central nervous system. It forms tetrameric potassium-selective channels, crucial for maintaining neuronal excitability and action potential firing. KCNA2's ability to form both homotetrameric and heterotetrameric channels, with diverse alpha subunits, allows for a wide range of channel properties, influencing neuronal output and cardiovascular system function.

Therapeutic significance:

KCNA2's role in Developmental and Epileptic Encephalopathy 32 (DEE32), a severe early-onset epilepsy, underscores its therapeutic potential. Understanding the function of KCNA2 could lead to novel interventions for DEE32 and other neurological disorders, by targeting aberrant action potential firing and neuronal hyperexcitability.

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