AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Zinc phosphodiesterase ELAC protein 1

Available from Reaxense
Predicted by Alphafold

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.

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 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.

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

 Fig. 1. The sreening 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.

Our library stands out due to several important features:

  • The Receptor.AI platform compiles comprehensive data on the target protein, encompassing previous experiments, literature, known ligands, structural details, and more, leading to a higher chance of selecting the most relevant compounds.
  • Advanced molecular simulations on the platform help pinpoint potential binding sites, making the compounds in our focused library ideal for finding allosteric inhibitors and targeting cryptic pockets.
  • Receptor.AI boasts over 50 tailor-made AI models, rigorously tested and proven in various drug discovery projects and research initiatives. They are crafted for efficacy, dependability, and precision, all of which are key in creating our focused libraries.
  • Beyond creating focused libraries, Receptor.AI offers comprehensive services and complete solutions throughout the preclinical drug discovery phase. Our success-based pricing model minimises risk and maximises the mutual benefits of the project's success.

partner

Reaxense

upacc

Q9H777

UPID:

RNZ1_HUMAN

Alternative names:

Deleted in Ma29; ElaC homolog protein 1; Ribonuclease Z 1; tRNA 3 endonuclease 1; tRNase Z 1

Alternative UPACC:

Q9H777; Q9NS99

Background:

Zinc phosphodiesterase ELAC protein 1, also known as Deleted in Ma29, ElaC homolog protein 1, Ribonuclease Z 1, tRNA 3 endonuclease 1, and tRNase Z 1, plays a crucial role in cellular processes. It functions as a zinc phosphodiesterase with tRNA 3'-processing endonuclease activity, specifically involved in tRNA repair. This protein acts downstream of the ribosome-associated quality control (RQC) pathway, removing a 2',3'-cyclic phosphate from tRNAs after cleavage by ANKZF1, with subsequent processing by TRNT1.

Therapeutic significance:

Understanding the role of Zinc phosphodiesterase ELAC protein 1 could open doors to potential therapeutic strategies.

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