Focused On-demand Library for Amiloride-sensitive sodium channel subunit beta

Details

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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.

PARTNER
Receptor.AI
 
UPACC
P51168

UPID:
SCNNB_HUMAN

ALTERNATIVE NAMES:
Beta-NaCH; Epithelial Na(+) channel subunit beta; Nonvoltage-gated sodium channel 1 subunit beta; SCNEB

ALTERNATIVE UPACC:
P51168; C5HTZ2; O60891; Q96KG2; Q9UJ32; Q9UMU5

BACKGROUND:
The protein Amiloride-sensitive sodium channel subunit beta, also referred to as SCNEB, is integral to sodium reabsorption and fluid balance across various tissues. Its function in electrolyte and blood pressure regulation, as well as mucus clearance in airways, highlights its systemic importance. The protein's activity is modulated by amiloride, indicating its potential as a drug target.

THERAPEUTIC SIGNIFICANCE:
Mutations in SCNEB are implicated in severe disorders like Pseudohypoaldosteronism 1B2, autosomal recessive, and Liddle syndrome 1, pointing to its critical role in human health. The exploration of SCNEB's function offers promising avenues for therapeutic intervention in these genetic diseases, showcasing the value of innovative drug discovery strategies.

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