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.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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 distinguishes itself through several key aspects:


  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.

  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.

  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.

  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.


PARTNER
Receptor.AI
 
UPACC
P22001

UPID:
KCNA3_HUMAN

ALTERNATIVE NAMES:
HGK5; HLK3; HPCN3; Voltage-gated K(+) channel HuKIII; Voltage-gated potassium channel subunit Kv1.3

ALTERNATIVE UPACC:
P22001; Q5VWN2

BACKGROUND:
The protein Potassium voltage-gated channel subfamily A member 3, with aliases such as Voltage-gated K(+) channel HuKIII and Kv1.3, is pivotal in controlling the flow of potassium ions across excitable membranes. It achieves this by altering its conformation in response to the membrane's voltage differences, thereby regulating the potassium-selective channel's opening or closing. This process is essential for maintaining the electrochemical gradient of potassium ions.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Potassium voltage-gated channel subfamily A member 3 unveils potential avenues for therapeutic intervention.

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