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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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 employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes in-depth molecular simulations of both the catalytic and allosteric binding pockets, with ensemble virtual screening focusing on their conformational flexibility. For modulators, the process includes considering the structural shifts due to reaction intermediates to boost activity and selectivity.


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
P09382

UPID:
LEG1_HUMAN

ALTERNATIVE NAMES:
14 kDa laminin-binding protein; 14 kDa lectin; Beta-galactoside-binding lectin L-14-I; Galaptin; HBL; HPL; Lactose-binding lectin 1; Lectin galactoside-binding soluble 1; Putative MAPK-activating protein PM12; S-Lac lectin 1

ALTERNATIVE UPACC:
P09382; B2R5E8; Q9UDK5

BACKGROUND:
Galectin-1, with alternative names such as 14 kDa laminin-binding protein and Lectin galactoside-binding soluble 1, plays a pivotal role in cellular mechanisms. Its ability to bind to a wide array of complex carbohydrates and beta-galactoside underlines its significance in biological systems. The protein is a key player in regulating apoptosis, cell proliferation, and differentiation, and it inhibits the activity of CD45 protein phosphatase, thereby affecting the phosphorylation status of Lyn kinase.

THERAPEUTIC SIGNIFICANCE:
The exploration of Galectin-1's functions offers promising avenues for therapeutic development. Its critical role in apoptosis and cell proliferation makes it a compelling target for drug discovery, aiming to modulate these processes in various diseases.

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