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.


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.


 

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
Q9UJ90

UPID:
KCNE5_HUMAN

ALTERNATIVE NAMES:
AMME syndrome candidate gene 2 protein; Potassium channel subunit beta MiRP4; Potassium voltage-gated channel subfamily E member 1-like protein

ALTERNATIVE UPACC:
Q9UJ90; Q5JWV7

BACKGROUND:
Potassium voltage-gated channel subfamily E regulatory beta subunit 5, also referred to as AMME syndrome candidate gene 2 protein, Potassium channel subunit beta MiRP4, and Potassium voltage-gated channel subfamily E member 1-like protein, is crucial for the generation of specific native K(+) currents. It achieves this by forming heteromeric ion channel complexes with voltage-gated potassium (Kv) channel pore-forming alpha subunits, acting as an inhibitory beta-subunit for the cardiac potassium ion channel KCNQ1.

THERAPEUTIC SIGNIFICANCE:
Given its association with the AMME complex, which manifests through a range of symptoms including glomerulonephritis, sensorineural hearing loss, and intellectual disability, the exploration of Potassium voltage-gated channel subfamily E regulatory beta subunit 5's function offers promising avenues for therapeutic intervention.

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