Focused On-demand Libraries - Receptor.AI 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.


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 Reaxense.


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.


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


 

Fig. 1. The screening 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
Receptor.AI
 
UPACC
O43813

UPID:
LANC1_HUMAN

ALTERNATIVE NAMES:
40 kDa erythrocyte membrane protein; LanC-like protein 1

ALTERNATIVE UPACC:
O43813

BACKGROUND:
The Glutathione S-transferase LANCL1 enzyme, recognized for its alternative names such as 40 kDa erythrocyte membrane protein and LanC-like protein 1, is integral to the body's antioxidant defenses. It achieves this by facilitating the conjugation of glutathione to artificial substrates, thereby playing a key role in neutralizing oxidative stress in neurons during development and under stress conditions. The protein's function in EPS8 signaling and its capacity to bind glutathione further underscore its biological significance.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Glutathione S-transferase LANCL1 offers a promising avenue for identifying novel therapeutic approaches. Given its critical role in managing oxidative stress and supporting neuronal health, targeting LANCL1 could lead to innovative treatments for diseases where oxidative damage is a contributing factor.

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