AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Queuine tRNA-ribosyltransferase catalytic subunit 1

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.

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.

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.

partner

Reaxense

upacc

Q9BXR0

UPID:

TGT_HUMAN

Alternative names:

Guanine insertion enzyme; tRNA-guanine transglycosylase

Alternative UPACC:

Q9BXR0; B4DFM7; Q96BQ4; Q9BXQ9

Background:

Queuine tRNA-ribosyltransferase catalytic subunit 1, also known as Guanine insertion enzyme or tRNA-guanine transglycosylase, plays a pivotal role in the modification of tRNA. It catalyzes the replacement of guanine with queuine at the wobble position of tRNA, facilitating the production of the hypermodified nucleoside queuosine. This enzymatic action is crucial for the accurate translation of genetic information into proteins.

Therapeutic significance:

Understanding the role of Queuine tRNA-ribosyltransferase catalytic subunit 1 could open doors to potential therapeutic strategies. Its involvement in the fundamental process of protein synthesis highlights its potential as a target for drug discovery, aiming to modulate protein production in various diseases.

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