Focused On-demand Library for Probable tRNA(His) guanylyltransferase

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.

We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Our partner Reaxense helps in synthesizing and delivering these compounds.

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 utilise our cutting-edge, exclusive workflow to develop 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.

Our library distinguishes itself through several key aspects:

  • The Receptor.AI platform integrates all available data about the target protein, including past experiments, literature data, known ligands, structural information and more. This consolidated approach maximises the probability of prioritising highly relevant compounds.
  • The platform uses sophisticated molecular simulations to identify possible binding sites so that the compounds in the focused library are suitable for discovering allosteric inhibitors and the binders for cryptic pockets.
  • The platform integrates over 50 highly customisable AI models, which are thoroughly tested and validated on a multitude of commercial drug discovery programs and research projects. It is designed to be efficient, reliable and accurate. All this power is utilised when producing the focused libraries.
  • In addition to producing the focused libraries, Receptor.AI provides services and end-to-end solutions at every stage of preclinical drug discovery. The pricing model is success-based, which reduces your risks and leverages the mutual benefits of the project's success.







Alternative names:

Induced in high glucose-1; Interphase cytoplasmic foci protein 45; tRNA-histidine guanylyltransferase

Alternative UPACC:

Q9NWX6; D3DQJ5; Q53G12; Q7L5R3; Q9H0S2


The Probable tRNA(His) guanylyltransferase, also known as Induced in high glucose-1, Interphase cytoplasmic foci protein 45, and tRNA-histidine guanylyltransferase, plays a crucial role in protein synthesis fidelity. It adds a GMP to the 5'-end of tRNA(His) post-transcription, essential for tRNA recognition. Additionally, it acts as a guanyl-nucleotide exchange factor for MFN1 and MFN2, regulating mitochondrial fusion and contributing to cell survival under oxidative stress.

Therapeutic significance:

Linked to Spinocerebellar ataxia, autosomal recessive, 28, this protein's understanding could pave the way for innovative therapeutic strategies targeting mitochondrial dysfunction and protein synthesis anomalies.

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