Focused On-demand Libraries - Receptor.AI Collaboration


Explore the Potential with AI-Driven Innovation

The focused library is created on demand with the latest virtual screening and parameter assessment technology, supported by the Receptor.AI drug discovery platform. This method is more effective than traditional methods and results in higher-quality compounds with better activity, selectivity, and safety.


We pick out particular compounds from an extensive virtual database of more than 60 billion molecules. The preparation and shipment of these compounds are facilitated 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.


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


Several key aspects differentiate our library:


  • Receptor.AI compiles an all-encompassing dataset on the target protein, including historical experiments, literature data, known ligands, and structural insights, maximising the chances of prioritising the most pertinent compounds.

  • The platform employs state-of-the-art molecular simulations to identify potential binding sites, ensuring the focused library is primed for discovering allosteric inhibitors and binders of concealed pockets.

  • Over 50 customisable AI models, thoroughly evaluated in various drug discovery endeavours and research projects, make Receptor.AI both efficient and accurate. This technology is integral to the development of our focused libraries.

  • In addition to generating focused libraries, Receptor.AI offers a full range of services and solutions for every step of preclinical drug discovery, with a pricing model based on success, thereby reducing risk and promoting joint project success.


PARTNER
Receptor.AI
 
UPACC
Q5VT66

UPID:
MARC1_HUMAN

ALTERNATIVE NAMES:
Molybdenum cofactor sulfurase C-terminal domain-containing protein 1

ALTERNATIVE UPACC:
Q5VT66; A8K447; B2D078; Q5VVS9; Q5VVT0; Q5VVT1; Q8N9P5; Q96FN8; Q9H6C7

BACKGROUND:
The protein Mitochondrial amidoxime-reducing component 1, with its alternative name Molybdenum cofactor sulfurase C-terminal domain-containing protein 1, is integral to the body's metabolic cycles. It is involved in the reduction of N-oxygenated molecules and plays a significant role in increasing drug bioavailability through the reduction of N-hydroxylated prodrugs. Additionally, it may regulate endogenous nitric oxide levels and biosynthesis through mitochondrial N(omega)-hydroxy-L-arginine (NOHA) reduction.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of Mitochondrial amidoxime-reducing component 1 unveils new avenues for developing therapeutic strategies.

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