AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Arginine--tRNA ligase, cytoplasmic

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.

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 utilise our cutting-edge, exclusive workflow to develop focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

It includes comprehensive molecular simulations of the catalytic and allosteric binding pockets and the ensemble virtual screening accounting for their conformational mobility. In the case of designing modulators, the structural changes induced by reaction intermediates are taken into account to leverage 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.

partner

Reaxense

upacc

P54136

UPID:

SYRC_HUMAN

Alternative names:

Arginyl-tRNA synthetase

Alternative UPACC:

P54136; B2RBS9; Q53GY4; Q9BWA1

Background:

Arginine--tRNA ligase, cytoplasmic, also known as Arginyl-tRNA synthetase, plays a crucial role in protein synthesis. It is part of a larger complex that ensures the correct amino acids are attached to their corresponding tRNAs, a fundamental process for accurate protein production. Additionally, it influences the secretion of AIMP1 and the generation of the inflammatory cytokine EMAP2, highlighting its importance in inflammatory responses.

Therapeutic significance:

The protein is linked to Leukodystrophy, hypomyelinating, 9, a severe neurodegenerative disorder. This association underscores the protein's potential as a target for therapeutic intervention in treating or managing this debilitating disease. Understanding the role of Arginine--tRNA ligase, cytoplasmic could open doors to potential therapeutic strategies.

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