Focused On-demand Library for Galectin-2

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.


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


 

Fig. 1. The screening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across 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
P05162

UPID:
LEG2_HUMAN

ALTERNATIVE NAMES:
Beta-galactoside-binding lectin L-14-II; HL14; Lactose-binding lectin 2; S-Lac lectin 2

ALTERNATIVE UPACC:
P05162; Q6FGY4

BACKGROUND:
Galectin-2, with alternative names such as Beta-galactoside-binding lectin L-14-II and Lactose-binding lectin 2, is recognized for its beta-galactoside binding properties. The full spectrum of its physiological roles remains to be elucidated, presenting a fascinating area for research within the biological and medical sciences.

THERAPEUTIC SIGNIFICANCE:
The exploration of Galectin-2's functions is not just an academic pursuit but a pathway to uncovering novel therapeutic avenues. As research progresses, the potential for Galectin-2 to be at the heart of breakthrough treatments becomes increasingly plausible, underscoring its therapeutic significance.

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