Focused On-demand Libraries - Receptor.AI 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.


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


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.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for ion channels.


 

Fig. 1. The screening workflow of Receptor.AI

This process includes comprehensive molecular simulations of the ion channel in its native membrane environment, depicting its open, closed, and inactivated states, and ensemble virtual screening that accounts for conformational mobility in each state. Tentative binding pockets are investigated inside the pore, at the gating region, and in allosteric sites to cover the full spectrum of possible mechanisms of action.


Our library stands out due to several important features:


  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.

  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.

  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.

  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
O00305

UPID:
CACB4_HUMAN

ALTERNATIVE NAMES:
Calcium channel voltage-dependent subunit beta 4

ALTERNATIVE UPACC:
O00305; A7BJ74; A8K1Y4; B4DG40; O60515; Q6B000; Q96L40

BACKGROUND:
Voltage-dependent L-type calcium channel subunit beta-4 is integral to calcium channel functionality, affecting activation, inactivation, and G protein interactions. It also plays a role in the alpha-1 subunit's membrane targeting.

THERAPEUTIC SIGNIFICANCE:
Its association with conditions like idiopathic generalized epilepsy and episodic ataxia underscores the therapeutic potential of targeting this protein. Exploring its mechanisms could unveil new pathways for treating these neurological diseases.

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