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

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.

From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Our collaborator, Reaxense, aids in their synthesis and provision.

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 employ our advanced, specialised process to create 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.

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

Q7LG56

UPID:

RIR2B_HUMAN

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

Background:

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.