AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Argininosuccinate lyase

Available from Reaxense
Predicted by Alphafold

Focused On-demand Libraries - Reaxense Collaboration

Explore the Potential with AI-Driven Innovation

The specialised, focused library is developed on demand with the most recent virtual screening and parameter assessment technology, guided by the Receptor.AI drug discovery platform. This approach exceeds the capabilities of traditional methods and offers compounds with higher 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.

In the library, a selection of top modulators is provided, each marked with 38 ADME-Tox and 32 parameters related to physicochemical properties and drug-likeness. Also, every compound comes with its best docking poses, affinity scores, and activity scores, providing a comprehensive overview.

We use our state-of-the-art dedicated workflow for designing focused libraries for enzymes.

 Fig. 1. The sreening workflow of Receptor.AI

The procedure entails thorough molecular simulations of the catalytic and allosteric binding pockets, accompanied by ensemble virtual screening that factors in their conformational flexibility. When developing modulators, the structural modifications brought about by reaction intermediates are factored in to optimize 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

P04424

UPID:

ARLY_HUMAN

Alternative names:

Arginosuccinase

Alternative UPACC:

P04424; E7EMI0; E9PE48; Q6LDS5; Q96HS2

Background:

Argininosuccinate lyase, also known as Arginosuccinase, plays a pivotal role in the urea cycle by catalyzing the reversible cleavage of L-argininosuccinate to fumarate and L-arginine. This reaction is crucial for hepatic nitrogen detoxification and de novo L-arginine synthesis in nonhepatic tissues. The protein forms part of the citrulline-nitric oxide cycle, creating tissue-specific multiprotein complexes essential for cell-autonomous L-arginine synthesis and nitric oxide production.

Therapeutic significance:

Argininosuccinate lyase is directly implicated in Argininosuccinic aciduria, an autosomal recessive disorder characterized by a spectrum of symptoms including mental and physical retardation, liver enlargement, and skin lesions. The disease's variability among patients is linked to the functional diversity of the mutant protein, highlighting the protein's therapeutic potential in devising targeted treatments for this urea cycle disorder.

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