AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Beta-1,3-glucosyltransferase

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.

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

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

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 distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.

partner

Reaxense

upacc

Q6Y288

UPID:

B3GLT_HUMAN

Alternative names:

Beta 3-glucosyltransferase; Beta-3-glycosyltransferase-like

Alternative UPACC:

Q6Y288; A8K5F8; Q5W0H2; Q6NUI3

Background:

Beta-1,3-glucosyltransferase, also known as Beta 3-glucosyltransferase and Beta-3-glycosyltransferase-like, plays a crucial role in the post-translational modification of proteins. It specifically targets O-linked fucosylglycan on TSP type-1 domains, facilitating the elongation of O-fucosylglycan chains. This enzymatic activity is pivotal in various biological processes, including cell signaling and development.

Therapeutic significance:

The enzyme's association with Peters-plus syndrome, a genetic disorder marked by eye abnormalities, short stature, and developmental delays, underscores its clinical importance. Understanding the role of Beta-1,3-glucosyltransferase could open doors to potential therapeutic strategies for managing this syndrome and related developmental disorders.

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