Focused On-demand Library for Inosine triphosphate pyrophosphatase

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.

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.

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 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:

Non-canonical purine NTP pyrophosphatase; Non-standard purine NTP pyrophosphatase; Nucleoside-triphosphate diphosphatase; Nucleoside-triphosphate pyrophosphatase; Putative oncogene protein hlc14-06-p

Alternative UPACC:

Q9BY32; A2A2N2; A4UIM5; B2BCH7; O14878; Q5JWH4; Q9BYN1; Q9BYX0; Q9H3H8


Inosine triphosphate pyrophosphatase, known by alternative names such as Non-canonical purine NTP pyrophosphatase, plays a crucial role in hydrolyzing non-canonical purine nucleotides to prevent their incorporation into RNA and DNA, thereby avoiding chromosomal lesions. This enzyme's activity is pivotal in maintaining the integrity of genetic material by excluding non-canonical purines from RNA and DNA precursor pools.

Therapeutic significance:

The enzyme's deficiency is linked to Inosine triphosphate pyrophosphohydrolase deficiency, characterized by abnormal accumulation of inosine triphosphate in erythrocytes, and Developmental and epileptic encephalopathy 35, a severe early-onset epilepsy. Understanding the enzyme's role could lead to novel therapeutic strategies for these conditions, highlighting its potential in drug discovery.

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