Focused On-demand Library for Kv channel-interacting protein 4

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced 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.

The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We employ our advanced, specialised process to create targeted libraries.

 Fig. 1. The sreening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of 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.







Alternative names:

A-type potassium channel modulatory protein 4; Calsenilin-like protein; Potassium channel-interacting protein 4

Alternative UPACC:

Q6PIL6; Q3YAB8; Q3YAB9; Q3YAC0; Q3YAC1; Q3YAC2; Q4W5G8; Q8NEU0; Q9BWT2; Q9H294; Q9H2A4


Kv channel-interacting protein 4, also known as A-type potassium channel modulatory protein 4, plays a crucial role in modulating the density, inactivation kinetics, and recovery rate from inactivation of Kv4/D-type voltage-gated rapidly inactivating A-type potassium channels. This modulation is calcium-dependent and varies with the isoform of the protein. Notably, isoform 4 has a unique function in retaining KCND3 in the endoplasmic reticulum, thereby regulating its expression on the cell membrane.

Therapeutic significance:

Understanding the role of Kv channel-interacting protein 4 could open doors to potential therapeutic strategies. Its intricate involvement in modulating potassium channel activity highlights its potential as a target for developing treatments for conditions associated with potassium channel dysfunctions.

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