Focused On-demand Libraries - Receptor.AI 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.


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 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.


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
Q9P2T1

UPID:
GMPR2_HUMAN

ALTERNATIVE NAMES:
Guanosine 5'-monophosphate oxidoreductase 2

ALTERNATIVE UPACC:
Q9P2T1; D3DS66; Q567T0; Q6IAJ8; Q86T14

BACKGROUND:
The enzyme GMP reductase 2, with alternative name Guanosine 5'-monophosphate oxidoreductase 2, is integral to the conversion of nucleobase, nucleoside, and nucleotide derivatives of G to A nucleotides. It ensures the balance of A and G nucleotides within cells, according to multiple studies (e.g., PubMed:12009299, PubMed:12669231). Additionally, it has a role in cellular differentiation, indicating its significance in the regulation of cellular processes.

THERAPEUTIC SIGNIFICANCE:
Exploring the function of GMP reductase 2 holds promise for unveiling new therapeutic avenues. Given its critical role in nucleotide balance and influence on cellular differentiation, targeting this enzyme could lead to innovative treatments that harness its biological functions.

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