Focused On-demand Library for Cyclic nucleotide-gated cation channel beta-3

Focused On-demand Libraries - Receptor.AI 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.


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 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.


 

Fig. 1. The screening workflow of Receptor.AI

Our methodology employs molecular simulations to explore a wide array of proteins, capturing their dynamic states both individually and within complexes. Through ensemble virtual screening, we address conformational mobility, uncovering binding sites within functional regions and remote allosteric locations. This thorough exploration ensures no potential mechanism of action is overlooked, aiming to discover novel therapeutic targets and lead compounds across an extensive spectrum of biological functions.


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
Q9NQW8

UPID:
CNGB3_HUMAN

ALTERNATIVE NAMES:
Cone photoreceptor cGMP-gated channel subunit beta; Cyclic nucleotide-gated cation channel modulatory subunit; Cyclic nucleotide-gated channel beta-3

ALTERNATIVE UPACC:
Q9NQW8; C9JA51; Q9NRE9

BACKGROUND:
The protein Cyclic nucleotide-gated cation channel beta-3, with alternative names including Cone photoreceptor cGMP-gated channel subunit beta, is crucial for the conversion of visual signals into electrical signals in the eye. By mediating the effects of cGMP, it allows for the proper functioning of rod photoreceptors, essential for color discrimination and visual clarity.

THERAPEUTIC SIGNIFICANCE:
Given its role in critical eye conditions such as Stargardt disease 1 and Achromatopsia 3, research into Cyclic nucleotide-gated cation channel beta-3 offers a promising avenue for developing targeted therapies. Enhancing our understanding of this protein could lead to breakthroughs in treating or managing these debilitating visual impairments.

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