AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Ectonucleoside triphosphate diphosphohydrolase 3

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate 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 use our state-of-the-art dedicated workflow for designing focused 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

O75355

UPID:

ENTP3_HUMAN

Alternative names:

CD39 antigen-like 3; Ecto-ATP diphosphohydrolase 3; Ecto-apyrase 3; HB6

Alternative UPACC:

O75355; B2R8D0; G5E9N0; O60495; Q8N6K2

Background:

Ectonucleoside triphosphate diphosphohydrolase 3, known by alternative names such as CD39 antigen-like 3, Ecto-ATP diphosphohydrolase 3, Ecto-apyrase 3, and HB6, plays a crucial role in cellular processes by preferring the hydrolysis of ATP over ADP. This specificity indicates a unique enzymatic activity that could be pivotal in regulating extracellular ATP levels, a key molecule in energy transfer and signaling.

Therapeutic significance:

Understanding the role of Ectonucleoside triphosphate diphosphohydrolase 3 could open doors to potential therapeutic strategies. Its unique preference for ATP hydrolysis over ADP suggests a significant function in maintaining cellular energy balance and signaling, making it a compelling target for drug discovery efforts aimed at modulating energy metabolism and signal transduction pathways.

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