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.


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 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.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P10253

UPID:
LYAG_HUMAN

ALTERNATIVE NAMES:
Acid maltase; Aglucosidase alfa

ALTERNATIVE UPACC:
P10253; Q09GN4; Q14351; Q16302; Q8IWE7

BACKGROUND:
The enzyme Lysosomal alpha-glucosidase, with alternative names Acid maltase and Aglucosidase alfa, is essential for glycogen degradation in lysosomes. It exhibits highest activity on alpha-1,4-linked glycosidic linkages and can also act on alpha-1,6-linked glucans, playing a vital role in cellular energy release.

THERAPEUTIC SIGNIFICANCE:
Variants in the gene encoding Lysosomal alpha-glucosidase cause Glycogen storage disease 2, manifesting in forms from severe infantile Pompe disease to adult-onset muscular dystrophy. The enzyme's critical role in glycogen breakdown and disease association highlights its potential as a therapeutic target for developing treatments for these metabolic disorders.

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