Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This extensive focused library is tailor-made using the latest virtual screening and parameter assessment technology, operated by the Receptor.AI drug discovery platform. This technique is more effective than traditional methods, offering compounds with improved activity, selectivity, and safety.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed 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.


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


 

Fig. 1. The screening workflow of Receptor.AI

By deploying molecular simulations, our approach comprehensively covers a broad array of proteins, tracking their flexibility and dynamics individually and within complexes. Ensemble virtual screening is utilised to take into account conformational dynamics, identifying pivotal binding sites located within functional regions and at allosteric locations. This thorough exploration ensures that every conceivable mechanism of action is considered, aiming to identify new therapeutic targets and advance lead compounds throughout a vast spectrum of biological functions.


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
Q9UGI6

UPID:
KCNN3_HUMAN

ALTERNATIVE NAMES:
KCa2.3

ALTERNATIVE UPACC:
Q9UGI6; B1ANX0; O43517; Q86VF9; Q8WXG7

BACKGROUND:
The protein KCa2.3, alternatively named Small conductance calcium-activated potassium channel protein 3, is instrumental in forming a potassium channel that responds to calcium levels without the need for voltage changes. Its role is crucial in modulating neuronal excitability and synaptic activity, ensuring proper neuronal communication and function.

THERAPEUTIC SIGNIFICANCE:
Understanding the role of KCa2.3 could open doors to potential therapeutic strategies for Zimmermann-Laband syndrome 3, a disorder marked by significant developmental challenges and neurological symptoms. Exploring KCa2.3's function and its dysregulation offers a promising avenue for developing targeted therapies that could improve patient outcomes.

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