Focused On-demand Library for Zinc phosphodiesterase ELAC protein 2

Details

Focused On-demand Libraries - Receptor.AI 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.


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


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 employ our advanced, specialised process to create targeted libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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
Q9BQ52

UPID:
RNZ2_HUMAN

ALTERNATIVE NAMES:
ElaC homolog protein 2; Heredity prostate cancer protein 2; Ribonuclease Z 2; tRNA 3 endonuclease 2; tRNase Z 2

ALTERNATIVE UPACC:
Q9BQ52; B4DPL9; Q6IA94; Q9HAS8; Q9HAS9; Q9NVT1

BACKGROUND:
The ELAC2 protein, alternatively named Ribonuclease Z 2, is pivotal in tRNA maturation, specifically in the mitochondrial environment. It ensures the proper processing of tRNA by excising 3'-trailers, a step critical for the initiation of RNA processing and ribosome assembly. Its association with mitochondrial DNA complexes underscores its significance in cellular metabolism.

THERAPEUTIC SIGNIFICANCE:
Given its involvement in hereditary prostate cancer and mitochondrial dysfunction disorders like combined oxidative phosphorylation deficiency 17, ELAC2 represents a promising target for therapeutic intervention. Exploring ELAC2's functions could open doors to potential therapeutic strategies.

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