Focused On-demand Library for Adenosylhomocysteinase 3

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner Reaxense.

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

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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.







Alternative names:

IP(3)Rs binding protein released with IP(3) 2; Long-IRBIT; S-adenosyl-L-homocysteine hydrolase 3; S-adenosylhomocysteine hydrolase-like protein 2

Alternative UPACC:

Q96HN2; B4DIZ5; D9N155; O94917


Adenosylhomocysteinase 3, also known as S-adenosyl-L-homocysteine hydrolase 3, plays a crucial role in cellular metabolism by potentially regulating the activity of the sodium/bicarbonate cotransporter SLC4A4 and its sensitivity to magnesium ions. Unlike its homolog AHCYL1, it does not affect the sensitivity of ITPR1 to inositol 1,4,5-trisphosphate, highlighting its unique function in cellular processes.

Therapeutic significance:

Understanding the role of Adenosylhomocysteinase 3 could open doors to potential therapeutic strategies. Its distinct regulatory functions suggest it could be a target for modulating cellular metabolism and ion transport mechanisms, offering new avenues for drug discovery.

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