Focused On-demand Library for Non-secretory ribonuclease

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.


From a virtual chemical space containing more than 60 billion molecules, we precisely choose certain compounds. Reaxense aids in their synthesis and provision.


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.


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
P10153

UPID:
RNAS2_HUMAN

ALTERNATIVE NAMES:
Eosinophil-derived neurotoxin; RNase UpI-2; Ribonuclease 2; Ribonuclease US

ALTERNATIVE UPACC:
P10153; Q52M39; Q9H2B7; Q9UCG7

BACKGROUND:
Non-secretory ribonuclease, known for its alternative names such as Eosinophil-derived neurotoxin and Ribonuclease US, plays a crucial role in the biological system. It is a pyrimidine specific nuclease, with a slight preference for U, and possesses cytotoxic and helminthotoxic properties. Its selective chemotaxis for dendritic cells underlines its potential in immunological responses.

THERAPEUTIC SIGNIFICANCE:
The exploration of Non-secretory ribonuclease's functions could lead to groundbreaking therapeutic approaches. Given its diverse biological activities and its interaction with dendritic cells, it holds significant promise for the development of innovative medical treatments.

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