AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Xylosyl- and glucuronyltransferase LARGE1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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 our partner Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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

 Fig. 1. The sreening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve 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

Reaxense

upacc

O95461

UPID:

LARG1_HUMAN

Alternative names:

Acetylglucosaminyltransferase-like 1A; Glycosyltransferase-like protein; LARGE xylosyl- and glucuronyltransferase 1

Alternative UPACC:

O95461; B0QXZ7; O60348; Q17R80; Q9UGD1; Q9UGE7; Q9UGG3; Q9UGZ8; Q9UH22

Background:

Xylosyl- and glucuronyltransferase LARGE1, known alternatively as Acetylglucosaminyltransferase-like 1A or Glycosyltransferase-like protein, plays a pivotal role in the maturation of alpha-dystroglycan through its bifunctional glycosyltransferase activities. This process is crucial for alpha-dystroglycan's high-affinity binding to laminin G-like domain-containing extracellular proteins, facilitating cell-matrix interactions.

Therapeutic significance:

LARGE1's involvement in muscular dystrophy-dystroglycanopathy, both congenital with impaired intellectual development (B6) and with brain and eye anomalies (A6), underscores its therapeutic potential. Targeting LARGE1's pathway could lead to innovative treatments for these severe disorders, highlighting the importance of further research into its functions and mechanisms.

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