Focused On-demand Library for Polyribonucleotide nucleotidyltransferase 1, mitochondrial

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.

We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated by our associate Reaxense.

The library includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

We utilise our cutting-edge, exclusive workflow to develop focused 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:

3'-5' RNA exonuclease OLD35; PNPase old-35; Polynucleotide phosphorylase 1; Polynucleotide phosphorylase-like protein

Alternative UPACC:

Q8TCS8; Q53SU0; Q68CN1; Q7Z7D1; Q8IWX1; Q96T05; Q9BRU3; Q9BVX0


Polyribonucleotide nucleotidyltransferase 1, mitochondrial, also known as PNPase old-35, plays a pivotal role in RNA metabolic processes. It catalyzes the phosphorolysis of single-stranded polyribonucleotides and is a key component of the mitochondrial degradosome complex. This protein is essential for the degradation of non-coding mitochondrial transcripts, the processing and polyadenylation of mitochondrial mRNAs, and the regulation of electron transport chain components.

Therapeutic significance:

PNPase old-35 is implicated in diseases such as Combined oxidative phosphorylation deficiency 13, Deafness, autosomal recessive, 70, and Spinocerebellar ataxia 25. These associations highlight its critical role in mitochondrial function and neurological health, making it a potential target for therapeutic intervention in mitochondrial disorders and neurodegenerative diseases.

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