Focused On-demand Libraries - Receptor.AI 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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We use our state-of-the-art dedicated workflow for designing focused libraries for ion channels.


 

Fig. 1. The screening 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.


PARTNER
Receptor.AI
 
UPACC
Q12791

UPID:
KCMA1_HUMAN

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

BACKGROUND:
The BK channel, or Calcium-activated potassium channel subunit alpha-1, is essential for regulating cell excitability across multiple systems. Activation by cytosolic Ca2+ or membrane depolarization helps in controlling smooth muscle contraction, cochlear hair cell frequency tuning, and neurotransmitter release. Its modulation by factors like alternative splicing and phosphorylation status underlines its versatility.

THERAPEUTIC SIGNIFICANCE:
Involvement of the BK channel in diseases such as Paroxysmal nonkinesigenic dyskinesia and Epilepsy, idiopathic generalized 16, highlights its therapeutic potential. Targeting KCa1.1 could lead to innovative treatments for these and other related neurological disorders.

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