Focused On-demand Library for Ribonucleoside-diphosphate reductase large subunit

Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

Our detailed focused library is generated on demand with advanced virtual screening and parameter assessment technology powered by the Receptor.AI drug discovery platform. This method surpasses traditional approaches, delivering compounds of better quality with enhanced activity, selectivity, and safety.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. 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 screening workflow of Receptor.AI

The method includes detailed molecular simulations of the catalytic and allosteric binding pockets, along with ensemble virtual screening that considers their conformational flexibility. In the design of modulators, structural changes induced by reaction intermediates are taken into account to enhance activity and selectivity.


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
P23921

UPID:
RIR1_HUMAN

ALTERNATIVE NAMES:
Ribonucleoside-diphosphate reductase subunit M1; Ribonucleotide reductase large subunit

ALTERNATIVE UPACC:
P23921; Q9UNN2

BACKGROUND:
Ribonucleoside-diphosphate reductase subunit M1, alternatively known as the Ribonucleotide reductase large subunit, is essential for DNA synthesis. It ensures the availability of deoxyribonucleotides, necessary precursors for DNA replication and repair, by catalyzing their biosynthesis from ribonucleotides.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of Ribonucleoside-diphosphate reductase subunit M1 offers a pathway to innovative therapeutic approaches. Given its indispensable role in DNA synthesis, targeting this protein could lead to breakthroughs in cancer therapy, exploiting the dependency of rapidly dividing cancer cells on DNA replication.

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