AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Heparan sulfate glucosamine 3-O-sulfotransferase 2

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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

 Fig. 1. The sreening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance 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

Q9Y278

UPID:

HS3S2_HUMAN

Alternative names:

Heparan sulfate D-glucosaminyl 3-O-sulfotransferase 2

Alternative UPACC:

Q9Y278; Q52LZ1

Background:

Heparan sulfate glucosamine 3-O-sulfotransferase 2, alternatively known as Heparan sulfate D-glucosaminyl 3-O-sulfotransferase 2, plays a crucial role in the modification of heparan sulfate. This enzyme utilizes 3'-phospho-5'-adenylyl sulfate to catalyze the transfer of a sulfo group, specifically targeting an N-unsubstituted glucosamine linked to a 2-O-sulfo iduronic acid unit. Its activity is pivotal in the O-sulfation of glucosamine, a process essential for the structural diversity and function of heparan sulfate.

Therapeutic significance:

Understanding the role of Heparan sulfate glucosamine 3-O-sulfotransferase 2 could open doors to potential therapeutic strategies. Its specific function in heparan sulfate modification suggests a significant impact on cellular communication and various biological processes, highlighting its potential as a target in therapeutic interventions.

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