AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Queuine tRNA-ribosyltransferase accessory subunit 2

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.

Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by our partner Reaxense.

Contained in the library are leading modulators, each labelled with 38 ADME-Tox and 32 physicochemical and drug-likeness qualities. In addition, each compound is illustrated with its optimal docking poses, affinity scores, and activity scores, giving a complete picture.

Our top-notch dedicated system is used to design specialised libraries.

 Fig. 1. The sreening workflow of Receptor.AI

Our strategy employs molecular simulations to explore an extensive range of proteins, capturing their dynamics both individually and within complexes with other proteins. Through ensemble virtual screening, we address proteins' conformational mobility, uncovering key binding sites at both functional regions and remote allosteric locations. This comprehensive investigation ensures a thorough assessment of all potential mechanisms of action, with the goal of discovering innovative therapeutic targets and lead molecules across across diverse biological functions.

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

Q9H974

UPID:

QTRT2_HUMAN

Alternative names:

Queuine tRNA-ribosyltransferase domain-containing protein 1

Alternative UPACC:

Q9H974; A6NGE9; B7Z472; B7Z5R2; J3KR78; Q6IA59

Background:

Queuine tRNA-ribosyltransferase accessory subunit 2, also known as Queuine tRNA-ribosyltransferase domain-containing protein 1, plays a pivotal role in the modification of tRNA. This protein is a non-catalytic subunit of the TGT complex, essential for the base-exchange of guanine with queuine at the anticodon wobble position in tRNAs. This modification results in the formation of the hypermodified nucleoside queuosine, crucial for the proper function of tRNA-Asp, -Asn, -His, and -Tyr.

Therapeutic significance:

Understanding the role of Queuine tRNA-ribosyltransferase accessory subunit 2 could open doors to potential therapeutic strategies.

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