Focused On-demand Library for Calcium-activated potassium channel subunit alpha-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.

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.

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 ion channels.

 Fig. 1. The sreening workflow of Receptor.AI

The method involves in-depth molecular simulations of the ion channel in its native membrane environment, including its open, closed, and inactivated states, along with ensemble virtual screening that focuses on conformational mobility for each state. Tentative binding pockets are identified inside the pore, in the gating area, and at allosteric sites to address every conceivable mechanism of action.

Our library is unique due to several crucial aspects:

  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.
  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.
  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.
  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.







Alternative names:

BK channel; BKCA alpha; Calcium-activated potassium channel, subfamily M subunit alpha-1; K(VCA)alpha; KCa1.1; Maxi K channel; Slo-alpha; Slo1; Slowpoke homolog

Alternative UPACC:

Q12791; F8WA96; Q12886; Q12917; Q12921; Q12960; Q13150; Q5JQ23; Q5SQR9; Q96LG8; Q9UBB0; Q9UCX0; Q9UQK6


The Calcium-activated potassium channel subunit alpha-1, known as KCa1.1 or BK channel, plays a pivotal role in cellular excitability. By mediating K+ export in response to membrane depolarization and cytosolic Ca2+ increase, it contributes to the repolarization of the membrane potential. Its activity is crucial in various systems, including smooth muscle contraction, cochlear hair cell tuning, neurotransmitter release, and innate immunity.

Therapeutic significance:

KCa1.1 is implicated in several neurological disorders, including Paroxysmal nonkinesigenic dyskinesia, Epilepsy, idiopathic generalized 16, and Liang-Wang syndrome. Understanding the role of KCa1.1 could open doors to potential therapeutic strategies for these conditions.

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