Focused On-demand Library for Beta-galactosidase-1-like protein 3

Details

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.


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 features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


We utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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
Q8NCI6

UPID:
GLBL3_HUMAN

ALTERNATIVE NAMES:
-

ALTERNATIVE UPACC:
Q8NCI6; A6NEM0; A6NN15; Q6P3S3; Q96FF8

BACKGROUND:
The Beta-galactosidase-1-like protein 3, identified by the unique identifier Q8NCI6, is a protein of interest in the field of molecular biology. Its recommended name hints at a relationship with the beta-galactosidase family, suggesting a role in the metabolism of galactosides. However, the precise biological functions and pathways involving this protein remain to be fully characterized.

THERAPEUTIC SIGNIFICANCE:
Investigating Beta-galactosidase-1-like protein 3's biological roles is pivotal for identifying new therapeutic avenues. As research progresses, the potential for targeting this protein in drug discovery efforts becomes increasingly apparent, offering hope for interventions in conditions linked to its function.

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