Focused On-demand Library for Voltage-gated potassium channel subunit beta-2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 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 our associate 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 high-tech, dedicated method is applied to construct targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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.







Alternative names:

K(+) channel subunit beta-2; Kv-beta-2

Alternative UPACC:

Q13303; A0AVM9; A8K1A4; B0AZR7; O43659; Q2YD85; Q5TG82; Q5TG83; Q6ZNE4; Q99411


Voltage-gated potassium channel subunit beta-2 (Kv-beta-2) plays a pivotal role in modulating potassium channel activity, crucial for nerve signaling and preventing neuronal hyperexcitability. It enhances the expression and activity of various potassium channels, including KCNA4 and KCNB2, and possesses NADPH-dependent aldoketoreductase activity with broad substrate specificity.

Therapeutic significance:

Understanding the role of Voltage-gated potassium channel subunit beta-2 could open doors to potential therapeutic strategies, particularly in neurological disorders where dysregulation of potassium channels contributes to disease pathology.

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