Focused On-demand Library for Ribonucleoside-diphosphate reductase subunit M2 B

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 carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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.

Our high-tech, dedicated method is applied to construct 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.

Key features that set our library apart include:

  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.
  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.
  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.
  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.







Alternative names:

TP53-inducible ribonucleotide reductase M2 B; p53-inducible ribonucleotide reductase small subunit 2-like protein

Alternative UPACC:

Q7LG56; B4E2N4; Q17R22; Q75PQ6; Q75PQ7; Q75PY8; Q75PY9; Q86YE3; Q9NPD6; Q9NTD8; Q9NUW3


The Ribonucleoside-diphosphate reductase subunit M2 B, also known as TP53-inducible ribonucleotide reductase M2 B, plays a crucial role in cell survival by repairing damaged DNA in a p53/TP53-dependent manner. It is essential for supplying deoxyribonucleotides for DNA repair in cells arrested at G1 or G2 phases and contains an iron-tyrosyl free radical center required for catalysis.

Therapeutic significance:

This protein's involvement in mitochondrial DNA depletion syndromes 8A and 8B, progressive external ophthalmoplegia, and rod-cone dystrophy highlights its potential as a target for therapeutic strategies aimed at mitigating mitochondrial dysfunction and related diseases.

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