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 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 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.


Our high-tech, dedicated method is applied to construct targeted libraries for enzymes.


 

Fig. 1. The screening 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.


Key features that set our library apart include:


  • The Receptor.AI platform integrates extensive information about the target protein, such as historical experiments, academic research, known ligands, and structural insights, thereby increasing the likelihood of identifying highly relevant compounds.

  • The platform’s sophisticated molecular simulations are designed to discover potential binding sites, ensuring that our focused library is optimal for the discovery of allosteric inhibitors and binders for cryptic pockets.

  • With over 50 customisable AI models, verified through extensive testing in commercial drug discovery and research, Receptor.AI is efficient, reliable, and precise. These models are essential in the production of our focused libraries.

  • Receptor.AI not only produces focused libraries but also provides full services and solutions at every stage of preclinical drug discovery, with a success-based pricing structure that aligns our interests with the success of your project.


PARTNER
Receptor.AI
 
UPACC
Q9UHB4

UPID:
NDOR1_HUMAN

ALTERNATIVE NAMES:
NADPH-dependent FMN and FAD-containing oxidoreductase; Novel reductase 1

ALTERNATIVE UPACC:
Q9UHB4; D3YTG6; D3YTH9; Q5VSG4; Q86US9; Q96BC6

BACKGROUND:
The protein NADPH-dependent diflavin oxidoreductase 1, with alternative names such as NADPH-dependent FMN and FAD-containing oxidoreductase and Novel reductase 1, is a central component of the CIA machinery. It efficiently transfers electrons to CIAPIN1's [2Fe-2S] cluster, playing a crucial role in the assembly of cytosolic iron-sulfur cluster proteins and potentially in Fe/S cluster repair. Its ability to activate methionine synthase/MTR underscores its importance in metabolic pathways.

THERAPEUTIC SIGNIFICANCE:
Exploring the functionalities of NADPH-dependent diflavin oxidoreductase 1 offers a promising avenue for developing novel therapeutic interventions.

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