AI-ACCELERATED DRUG DISCOVERY

Focused On-demand Library for Molybdenum cofactor sulfurase

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.

The compounds are cherry-picked from the vast virtual chemical space of over 60B molecules. The synthesis and delivery of compounds is facilitated by our partner 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

Q96EN8

UPID:

MOCOS_HUMAN

Alternative names:

Molybdenum cofactor sulfurtransferase

Alternative UPACC:

Q96EN8; Q53GP5; Q8N3A4; Q9NWM7

Background:

Molybdenum cofactor sulfurase, also known as Molybdenum cofactor sulfurtransferase, plays a pivotal role in human metabolism through its sulfurating activity on the molybdenum cofactor. This process is crucial for the activation of enzymes like xanthine dehydrogenase and aldehyde oxidase, which are involved in purine metabolism and the detoxification of drugs and toxins, respectively.

Therapeutic significance:

The protein's malfunction is directly linked to Xanthinuria type 2, a rare metabolic disorder characterized by excessive xanthine in urine and a propensity for xanthine stone formation. Understanding the role of Molybdenum cofactor sulfurase could open doors to potential therapeutic strategies for this condition.

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