AI-ACCELERATED DRUG DISCOVERY

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

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.

partner

Reaxense

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 Amiloride-sensitive sodium channel subunit beta, known as Beta-NaCH, plays a pivotal role in maintaining electrolyte and blood pressure homeostasis. This non-voltage-sensitive ion channel, inhibited by the diuretic amiloride, is crucial for the electrodiffusion of sodium across epithelial cells, impacting kidney, colon, lung, and sweat gland functions. It also influences airway surface liquid homeostasis and taste perception.

Therapeutic significance:

Linked to diseases such as Pseudohypoaldosteronism 1B2, Liddle syndrome 1, and Bronchiectasis, the protein's dysfunction underscores its therapeutic potential. Understanding its role could lead to novel treatments for these conditions, emphasizing the importance of targeted drug discovery efforts to modulate its activity.

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