Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior activity, selectivity and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


The library includes a list of the most promising modulators annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Also, each compound is presented with its optimal docking poses, affinity scores, and activity scores, providing a comprehensive overview.


We employ our advanced, specialised process to create targeted libraries.


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q6P3W7

UPID:
SCYL2_HUMAN

ALTERNATIVE NAMES:
Coated vesicle-associated kinase of 104 kDa

ALTERNATIVE UPACC:
Q6P3W7; A8KAB5; Q96EF4; Q96ST4; Q9H7V5; Q9NVH3; Q9P2I7

BACKGROUND:
The SCY1-like protein 2, known for its alternative name Coated vesicle-associated kinase of 104 kDa, is integral to the regulation of clathrin-dependent trafficking. This protein is a component of the AP2-containing clathrin coat, playing a probable role in trafficking across the plasma membrane, TGN, and endosomal system. It is also implicated in neuronal function and brain development, through its regulation of excitatory receptor expression at synapses.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in Arthrogryposis multiplex congenita 4, neurogenic, with agenesis of the corpus callosum, SCY1-like protein 2 represents a promising target for therapeutic intervention. Exploring its functions could open doors to potential therapeutic strategies for related neurological conditions.

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