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.


The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by Reaxense.


The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.


Our top-notch dedicated system is used to design specialised 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.


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
Receptor.AI
 
UPACC
P35499

UPID:
SCN4A_HUMAN

ALTERNATIVE NAMES:
SkM1; Sodium channel protein skeletal muscle subunit alpha; Sodium channel protein type IV subunit alpha; Voltage-gated sodium channel subunit alpha Nav1.4

ALTERNATIVE UPACC:
P35499; Q15478; Q16447; Q7Z6B1

BACKGROUND:
Nav1.4, or Sodium channel protein type 4 subunit alpha, plays a pivotal role in muscle physiology by regulating Na(+) ion flow, crucial for muscle strength and responsiveness. Known variably as SkM1, Sodium channel protein skeletal muscle subunit alpha, and Voltage-gated sodium channel subunit alpha Nav1.4, it is essential for normal muscle operations.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of Nav1.4 could open doors to potential therapeutic strategies. Its involvement in diseases like Paramyotonia congenita, Periodic paralysis (both hypokalemic and hyperkalemic), and Myotonia SCN4A-related, positions it as a key target for developing treatments aimed at alleviating muscle-related disorders.

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