Focused On-demand Library for Glutathione S-transferase LANCL1

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

This comprehensive focused library is produced on demand with state-of-the-art virtual screening and parameter assessment technology driven by Receptor.AI drug discovery platform. This approach outperforms traditional methods and provides higher-quality compounds with superior 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 includes a list of the most effective modulators, each annotated with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Furthermore, each compound is shown with its optimal docking poses, affinity scores, and activity scores, offering a detailed summary.

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.

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:

40 kDa erythrocyte membrane protein; LanC-like protein 1

Alternative UPACC:



Glutathione S-transferase LANCL1, also known as the 40 kDa erythrocyte membrane protein or LanC-like protein 1, plays a crucial role in cellular defense mechanisms. It functions by catalyzing the conjugation of glutathione (GSH) to various substrates, including 1-chloro-2,4-dinitrobenzene and p-nitrophenyl acetate. This process is vital for mitigating neuronal oxidative stress, supporting normal postnatal development, and responding to oxidative challenges through the GSH antioxidant defense mechanism. Additionally, LANCL1 may influence EPS8 signaling and has a known affinity for binding glutathione.

Therapeutic significance:

Understanding the role of Glutathione S-transferase LANCL1 could open doors to potential therapeutic strategies. Its involvement in antioxidant defense and stress response mechanisms highlights its potential as a target for developing treatments aimed at neurological conditions characterized by oxidative stress.

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