AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Poly(A) RNA polymerase, mitochondrial

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense 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.

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.

The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.

We use our state-of-the-art dedicated workflow for designing 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.

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

Reaxense

upacc

Q9NVV4

UPID:

PAPD1_HUMAN

Alternative names:

PAP-associated domain-containing protein 1; Polynucleotide adenylyltransferase; Terminal uridylyltransferase 1; mtPAP

Alternative UPACC:

Q9NVV4; D3DRX0; Q659E3; Q6P7E5; Q9HA74

Background:

Poly(A) RNA polymerase, mitochondrial (mtPAP), also known as PAP-associated domain-containing protein 1, plays a crucial role in the maturation of mitochondrial mRNA transcripts. It is responsible for adding the 3' poly(A) tail to mitochondrial transcripts, a process vital for mRNA stability and translation. mtPAP exhibits higher activity with ATP and UTP, indicating its preference for these nucleotides in vitro. Additionally, it is implicated in the degradation of replication-dependent histone mRNA, suggesting a broader role in RNA metabolism.

Therapeutic significance:

The association of mtPAP with Spastic ataxia 4, an autosomal recessive neurodegenerative disease, underscores its therapeutic significance. Mutations in mtPAP lead to defects in mitochondrial mRNA maturation, manifesting in severe neurological symptoms. Understanding mtPAP's function could pave the way for novel therapeutic strategies targeting mitochondrial diseases and neurodegeneration.

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