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.


In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We use our state-of-the-art dedicated workflow for designing focused libraries for ion channels.


 

Fig. 1. The screening workflow of Receptor.AI

It includes extensive molecular simulations of the channel in its native membrane environment in open, closed and inactivated forms and the ensemble virtual screening accounting for conformational mobility in each of these states. Tentative binding pockets are considered inside the pore, in the gating region and in the allosteric locations to cover the whole spectrum of possible mechanisms 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
Q14003

UPID:
KCNC3_HUMAN

ALTERNATIVE NAMES:
KSHIIID; Voltage-gated potassium channel subunit Kv3.3

ALTERNATIVE UPACC:
Q14003

BACKGROUND:
The protein Kv3.3, also known as KSHIIID, plays a pivotal role in neuron function by regulating the frequency, shape, and duration of action potentials. This regulation is essential for normal motor function and cerebellar neuron survival, highlighting its significance in the nervous system.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in Spinocerebellar ataxia 13, Kv3.3 represents a promising target for therapeutic intervention. Exploring Kv3.3's function and its pathogenic variants could lead to novel treatments for this and potentially other neurodegenerative diseases.

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