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.


Our selection of compounds is from a large virtual library of over 60 billion molecules. The production and distribution of these compounds are managed by Reaxense.


The library features a range of promising modulators, each detailed with 38 ADME-Tox and 32 physicochemical and drug-likeness parameters. Plus, each compound is presented with its ideal docking poses, affinity scores, and activity scores, ensuring a thorough insight.


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


 

Fig. 1. The screening workflow of Receptor.AI

Utilising molecular simulations, our approach thoroughly examines a wide array of proteins, tracking their conformational changes individually and within complexes. Ensemble virtual screening enables us to address conformational flexibility, revealing essential binding sites at functional regions and allosteric locations. Our rigorous analysis guarantees that no potential mechanism of action is overlooked, aiming to uncover new therapeutic targets and lead compounds across diverse biological functions.


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
Q9BVP2

UPID:
GNL3_HUMAN

ALTERNATIVE NAMES:
E2-induced gene 3 protein; Novel nucleolar protein 47; Nucleolar GTP-binding protein 3; Nucleostemin

ALTERNATIVE UPACC:
Q9BVP2; B2RDC1; Q5PU80; Q96SV6; Q96SV7; Q9UJY0

BACKGROUND:
Nucleostemin, identified by its key role in stem cell biology, stabilizes MDM2 to prevent its degradation, crucial for cell proliferation. Known variably as E2-induced gene 3 protein, Novel nucleolar protein 47, and Nucleolar GTP-binding protein 3, it underscores the complexity of cellular maintenance.

THERAPEUTIC SIGNIFICANCE:
Exploring the functions of Nucleostemin offers a promising avenue for developing new therapeutic approaches.

Looking for more information on this library or underlying technology? Fill out the form below and we will be in touch with all the details you need.