AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Potassium voltage-gated channel subfamily H member 8

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.

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.

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.

Our high-tech, dedicated method is applied to construct targeted libraries.

 Fig. 1. The sreening 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.

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.

partner

Reaxense

upacc

Q96L42

UPID:

KCNH8_HUMAN

Alternative names:

ELK1; Ether-a-go-go-like potassium channel 3; Voltage-gated potassium channel subunit Kv12.1

Alternative UPACC:

Q96L42; B7Z2I7; Q59GQ6

Background:

Potassium voltage-gated channel subfamily H member 8, known as ELK1, Ether-a-go-go-like potassium channel 3, or Kv12.1, is a critical component of cellular electrical signaling. This protein functions as the pore-forming (alpha) subunit of voltage-gated potassium channels, facilitating a slowly activating, outward rectifying current. Its activity is essential for the regulation of potassium ion flow across the cell membrane, influenced by cAMP levels and subunit assembly.

Therapeutic significance:

Understanding the role of Potassium voltage-gated channel subfamily H member 8 could open doors to potential therapeutic strategies. Its pivotal function in cellular electrical signaling positions it as a key target for modulating electrical activity in various tissues, offering avenues for the development of treatments for disorders related to ion channel dysfunction.

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