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.


We carefully select specific compounds from a vast collection of over 60 billion molecules in virtual chemical space. Reaxense helps in synthesizing and delivering these compounds.


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 employ our advanced, specialised process to create targeted 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
Q96EN8

UPID:
MOCOS_HUMAN

ALTERNATIVE NAMES:
Molybdenum cofactor sulfurtransferase

ALTERNATIVE UPACC:
Q96EN8; Q53GP5; Q8N3A4; Q9NWM7

BACKGROUND:
Molybdenum cofactor sulfurase, with its alternative name Molybdenum cofactor sulfurtransferase, is essential for the sulfation of the molybdenum cofactor. This sulfation is a critical step for the proper function of enzymes such as xanthine dehydrogenase and aldehyde oxidase, which play significant roles in the metabolism of purines and various xenobiotics.

THERAPEUTIC SIGNIFICANCE:
Disruption in the function of this protein leads to Xanthinuria 2, marked by reduced uric acid levels and the formation of xanthine stones. The exploration of Molybdenum cofactor sulfurase's role offers promising avenues for the development of novel treatments for this and potentially other related metabolic disorders.

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