Focused On-demand Library for Voltage-gated potassium channel subunit beta-1

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 employ our advanced, specialised process to create targeted libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.

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:

K(+) channel subunit beta-1; Kv-beta-1

Alternative UPACC:

Q14722; A8K9H8; A8KAD4; B3KPZ4; Q13031; Q13302; Q16547; Q6PI60; Q99869


Voltage-gated potassium channel subunit beta-1, also known as Kv-beta-1, plays a crucial role in modulating the characteristics of channel-forming alpha-subunits, impacting action potentials and channel activity. It promotes the expression of alpha subunits at the cell membrane, enhancing channel activity. Kv-beta-1 is instrumental in the closure of delayed rectifier potassium channels and accelerates the closure of channels like KCNA1, KCNA2, and KCNA5. Additionally, it possesses NADPH-dependent aldoketoreductase activity, essential for down-regulating potassium channel activity.

Therapeutic significance:

Understanding the role of Voltage-gated potassium channel subunit beta-1 could open doors to potential therapeutic strategies.

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