Focused On-demand Libraries - Receptor.AI 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.


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.


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.


Our top-notch dedicated system is used to design specialised libraries for enzymes.


 

Fig. 1. The screening workflow of Receptor.AI

This approach involves comprehensive molecular simulations of the catalytic and allosteric binding pockets and ensemble virtual screening that accounts for their conformational flexibility. In the case of designing modulators, the structural adjustments caused by reaction intermediates are considered to improve activity and selectivity.


Our library is unique due to several crucial aspects:


  • Receptor.AI compiles all relevant data on the target protein, such as past experimental results, literature findings, known ligands, and structural data, thereby enhancing the likelihood of focusing on the most significant compounds.

  • By utilizing advanced molecular simulations, the platform is adept at locating potential binding sites, rendering the compounds in the focused library well-suited for unearthing allosteric inhibitors and binders for hidden pockets.

  • The platform is supported by more than 50 highly specialized AI models, all of which have been rigorously tested and validated in diverse drug discovery and research programs. Its design emphasizes efficiency, reliability, and accuracy, crucial for producing focused libraries.

  • Receptor.AI extends beyond just creating focused libraries; it offers a complete spectrum of services and solutions during the preclinical drug discovery phase, with a success-dependent pricing strategy that reduces risk and fosters shared success in the project.


PARTNER
Receptor.AI
 
UPACC
P46952

UPID:
3HAO_HUMAN

ALTERNATIVE NAMES:
3-hydroxyanthranilate oxygenase; 3-hydroxyanthranilic acid dioxygenase

ALTERNATIVE UPACC:
P46952; A6NE56; B4DIN2; Q53QZ7; Q8N6N9

BACKGROUND:
3-Hydroxyanthranilate 3,4-dioxygenase, identified by the protein accession number P46952, is pivotal in the metabolism of tryptophan, leading to the production of NAD+ through the kynurenine pathway. Its enzymatic activity involves the transformation of 3-hydroxyanthranilate into 2-amino-3-carboxymuconate semialdehyde, facilitating quinolinate synthesis.

THERAPEUTIC SIGNIFICANCE:
Given its critical role in a rare congenital disorder characterized by multiple organ defects, targeting 3-hydroxyanthranilate 3,4-dioxygenase offers a promising avenue for the development of novel treatments. The enzyme's involvement in disease pathways highlights the importance of further research into its functions and mechanisms.

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